Merge pull request 'feat: Daily CB P&L 기준을 당일 시작 평가금액으로 변경 (#207)' (#227) from feature/issue-207-daily-cb-pnl into main

Reviewed-on: #227

.env.example

@@ -1,36 +1,82 @@
+# ============================================================
+# The Ouroboros — Environment Configuration
+# ============================================================
+# Copy this file to .env and fill in your values.
+# Lines starting with # are comments.
+
+# ============================================================
 # Korea Investment Securities API
+# ============================================================
 KIS_APP_KEY=your_app_key_here
 KIS_APP_SECRET=your_app_secret_here
 KIS_ACCOUNT_NO=12345678-01
-KIS_BASE_URL=https://openapivts.koreainvestment.com:9443
 
+# Paper trading (VTS): https://openapivts.koreainvestment.com:29443
+# Live trading:        https://openapi.koreainvestment.com:9443
+KIS_BASE_URL=https://openapivts.koreainvestment.com:29443
+
+# ============================================================
+# Trading Mode
+# ============================================================
+# paper = 모의투자 (safe for testing), live = 실전투자 (real money)
+MODE=paper
+
+# daily = batch per session, realtime = per-stock continuous scan
+TRADE_MODE=daily
+
+# Comma-separated market codes: KR, US, JP, HK, CN, VN
+ENABLED_MARKETS=KR,US
+
+# Simulated USD cash for paper (VTS) overseas trading.
+# VTS overseas balance API often returns 0; this value is used as fallback.
+# Set to 0 to disable fallback (not used in live mode).
+PAPER_OVERSEAS_CASH=50000.0
+
+# ============================================================
 # Google Gemini
+# ============================================================
 GEMINI_API_KEY=your_gemini_api_key_here
-GEMINI_MODEL=gemini-pro
+# Recommended: gemini-2.0-flash-exp or gemini-1.5-pro
+GEMINI_MODEL=gemini-2.0-flash-exp
 
+# ============================================================
 # Risk Management
+# ============================================================
 CIRCUIT_BREAKER_PCT=-3.0
 FAT_FINGER_PCT=30.0
 CONFIDENCE_THRESHOLD=80
 
+# ============================================================
 # Database
+# ============================================================
 DB_PATH=data/trade_logs.db
 
-# Rate Limiting (requests per second for KIS API)
+# ============================================================
-# Reduced to 5.0 to avoid "초당 거래건수 초과" errors (EGW00201)
+# Rate Limiting
-RATE_LIMIT_RPS=5.0
+# ============================================================
+# KIS API real limit is ~2 RPS. Keep at 2.0 for maximum safety.
+# Increasing this risks EGW00201 "초당 거래건수 초과" errors.
+RATE_LIMIT_RPS=2.0
 
-# Trading Mode (paper / live)
+# ============================================================
-MODE=paper
+# External Data APIs (optional)
-
+# ============================================================
-# External Data APIs (optional — for enhanced decision-making)
 # NEWS_API_KEY=your_news_api_key_here
 # NEWS_API_PROVIDER=alphavantage
 # MARKET_DATA_API_KEY=your_market_data_key_here
 
+# ============================================================
 # Telegram Notifications (optional)
+# ============================================================
 # Get bot token from @BotFather on Telegram
 # Get chat ID from @userinfobot or your chat
 # TELEGRAM_BOT_TOKEN=1234567890:ABCdefGHIjklMNOpqrsTUVwxyz
 # TELEGRAM_CHAT_ID=123456789
 # TELEGRAM_ENABLED=true
+
+# ============================================================
+# Dashboard (optional)
+# ============================================================
+# DASHBOARD_ENABLED=false
+# DASHBOARD_HOST=127.0.0.1
+# DASHBOARD_PORT=8080

CLAUDE.md

@@ -94,6 +94,7 @@ Smart Scanner runs in `TRADE_MODE=realtime` only. Daily mode uses static watchli
 - **[Testing](docs/testing.md)** — Test structure, coverage requirements, writing tests
 - **[Agent Policies](docs/agents.md)** — Prime directives, constraints, prohibited actions
 - **[Requirements Log](docs/requirements-log.md)** — User requirements and feedback tracking
+- **[Live Trading Checklist](docs/live-trading-checklist.md)** — 모의→실전 전환 체크리스트
 
 ## Core Principles
 
@@ -170,7 +171,7 @@ Markets auto-detected based on timezone and enabled in `ENABLED_MARKETS` env var
 - `src/core/risk_manager.py` is **READ-ONLY** — changes require human approval
 - Circuit breaker at -3.0% P&L — may only be made **stricter**
 - Fat-finger protection: max 30% of cash per order — always enforced
-- Confidence < 80 → force HOLD — cannot be weakened
+- Confidence 임계값 (market_outlook별, 낮출 수 없음): BEARISH ≥ 90, NEUTRAL/기본 ≥ 80, BULLISH ≥ 75
 - All code changes → corresponding tests → coverage ≥ 80%
 
 ## Contributing

docs/commands.md

@@ -192,6 +192,27 @@ When `TELEGRAM_COMMANDS_ENABLED=true` (default), the bot accepts these interacti
 
 Commands are only processed from the authorized `TELEGRAM_CHAT_ID`.
 
+## KIS API TR_ID 참조 문서
+
+**TR_ID를 추가하거나 수정할 때 반드시 공식 문서를 먼저 확인할 것.**
+
+공식 문서: `docs/한국투자증권_오픈API_전체문서_20260221_030000.xlsx`
+
+> ⚠️ 커뮤니티 블로그, GitHub 예제 등 비공식 자료의 TR_ID는 오래되거나 틀릴 수 있음.
+> 실제로 `VTTT1006U`(미국 매도 — 잘못됨)가 오랫동안 코드에 남아있던 사례가 있음 (Issue #189).
+
+### 주요 TR_ID 목록
+
+| 구분 | 모의투자 TR_ID | 실전투자 TR_ID | 시트명 |
+|------|---------------|---------------|--------|
+| 해외주식 매수 (미국) | `VTTT1002U` | `TTTT1002U` | 해외주식 주문 |
+| 해외주식 매도 (미국) | `VTTT1001U` | `TTTT1006U` | 해외주식 주문 |
+
+새로운 TR_ID가 필요할 때:
+1. 위 xlsx 파일에서 해당 거래 유형의 시트를 찾는다.
+2. 모의투자(`VTTT`) / 실전투자(`TTTT`) 컬럼을 구분하여 정확한 값을 사용한다.
+3. 코드에 출처 주석을 남긴다: `# Source: 한국투자증권_오픈API_전체문서 — '<시트명>' 시트`
+
 ## Environment Setup
 
 ```bash

docs/live-trading-checklist.md

@@ -0,0 +1,131 @@
+# 실전 전환 체크리스트
+
+모의 거래(paper)에서 실전(live)으로 전환하기 전에 아래 항목을 **순서대로** 모두 확인하세요.
+
+---
+
+## 1. 사전 조건
+
+### 1-1. KIS OpenAPI 실전 계좌 준비
+- [ ] 한국투자증권 계좌 개설 완료 (일반 위탁 계좌)
+- [ ] OpenAPI 실전 사용 신청 (KIS 홈페이지 → Open API → 서비스 신청)
+- [ ] 실전용 APP_KEY / APP_SECRET 발급 완료
+- [ ] KIS_ACCOUNT_NO 형식 확인: `XXXXXXXX-XX` (8자리-2자리)
+
+### 1-2. 리스크 파라미터 검토
+- [ ] `CIRCUIT_BREAKER_PCT` 확인: 기본값 -3.0% (더 엄격하게 조정 권장)
+- [ ] `FAT_FINGER_PCT` 확인: 기본값 30.0% (1회 주문 최대 잔고 대비 %)
+- [ ] `CONFIDENCE_THRESHOLD` 확인: BEARISH ≥ 90, NEUTRAL ≥ 80, BULLISH ≥ 75
+- [ ] 초기 투자금 결정 및 해외 주식 운용 한도 설정
+
+### 1-3. 시스템 요건
+- [ ] 커버리지 80% 이상 유지 확인: `pytest --cov=src`
+- [ ] 타입 체크 통과: `mypy src/ --strict`
+- [ ] Lint 통과: `ruff check src/ tests/`
+
+---
+
+## 2. 환경 설정
+
+### 2-1. `.env` 파일 수정
+
+```bash
+# 1. KIS 실전 URL로 변경 (모의: openapivts 포트 29443)
+KIS_BASE_URL=https://openapi.koreainvestment.com:9443
+
+# 2. 실전 APP_KEY / APP_SECRET으로 교체
+KIS_APP_KEY=<실전_APP_KEY>
+KIS_APP_SECRET=<실전_APP_SECRET>
+KIS_ACCOUNT_NO=<실전_계좌번호>
+
+# 3. 모드를 live로 변경
+MODE=live
+
+# 4. PAPER_OVERSEAS_CASH 비활성화 (live 모드에선 무시되지만 명시적으로 0 설정)
+PAPER_OVERSEAS_CASH=0
+```
+
+> ⚠️ `KIS_BASE_URL` 포트 주의:
+> - **모의(VTS)**: `https://openapivts.koreainvestment.com:29443`
+> - **실전**: `https://openapi.koreainvestment.com:9443`
+
+### 2-2. TR_ID 자동 분기 확인
+
+아래 TR_ID는 `MODE` 값에 따라 코드에서 **자동으로 선택**됩니다.
+별도 설정 불필요하나, 문제 발생 시 아래 표를 참조하세요.
+
+| 구분 | 모의 TR_ID | 실전 TR_ID |
+|------|-----------|-----------|
+| 국내 잔고 조회 | `VTTC8434R` | `TTTC8434R` |
+| 국내 현금 매수 | `VTTC0012U` | `TTTC0012U` |
+| 국내 현금 매도 | `VTTC0011U` | `TTTC0011U` |
+| 해외 잔고 조회 | `VTTS3012R` | `TTTS3012R` |
+| 해외 매수 | `VTTT1002U` | `TTTT1002U` |
+| 해외 매도 | `VTTT1001U` | `TTTT1006U` |
+
+> **출처**: `docs/한국투자증권_오픈API_전체문서_20260221_030000.xlsx` (공식 문서 기준)
+
+---
+
+## 3. 최종 확인
+
+### 3-1. 실전 시작 전 점검
+- [ ] DB 백업 완료: `data/trade_logs.db` → `data/backups/`
+- [ ] Telegram 알림 설정 확인 (실전에서는 알림이 더욱 중요)
+- [ ] 소액으로 첫 거래 진행 후 TR_ID/계좌 정상 동작 확인
+
+### 3-2. 실행 명령
+
+```bash
+# 실전 모드로 실행
+python -m src.main --mode=live
+
+# 대시보드 함께 실행 (별도 터미널에서 모니터링)
+python -m src.main --mode=live --dashboard
+```
+
+### 3-3. 실전 시작 직후 확인 사항
+- [ ] 로그에 `MODE=live` 출력 확인
+- [ ] 첫 잔고 조회 성공 (ConnectionError 없음)
+- [ ] Telegram 알림 수신 확인 ("System started")
+- [ ] 첫 주문 후 KIS 앱에서 체결 내역 확인
+
+---
+
+## 4. 비상 정지 방법
+
+### 즉각 정지
+```bash
+# 터미널에서 Ctrl+C (정상 종료 트리거)
+# 또는 Telegram 봇 명령:
+/stop
+```
+
+### Circuit Breaker 발동 시
+- CB가 발동되면 자동으로 거래 중단 및 Telegram 알림 전송
+- CB 임계값: `CIRCUIT_BREAKER_PCT` (기본 -3.0%)
+- **임계값은 엄격하게만 조정 가능** (더 낮은 음수 값으로만 변경)
+
+---
+
+## 5. 롤백 절차
+
+실전 전환 후 문제 발생 시:
+
+```bash
+# 1. 즉시 .env에서 MODE=paper로 복원
+# 2. 재시작
+python -m src.main --mode=paper
+
+# 3. DB에서 최근 거래 확인
+sqlite3 data/trade_logs.db "SELECT * FROM trades ORDER BY id DESC LIMIT 20;"
+```
+
+---
+
+## 관련 문서
+
+- [시스템 아키텍처](architecture.md)
+- [워크플로우 가이드](workflow.md)
+- [재해 복구](disaster_recovery.md)
+- [Agent 제약 조건](agents.md)

docs/requirements-log.md

@@ -7,6 +7,32 @@
 
 ---
 
+## 2026-02-21
+
+### 거래 상태 확인 중 발견된 버그 (#187)
+
+- 거래 상태 점검 요청 → SELL 주문(손절/익절)이 Fat Finger에 막혀 전혀 실행 안 됨 발견
+- **#187 (Critical)**: SELL 주문에서 Fat Finger 오탐 — `order_amount/total_cash > 30%`가 SELL에도 적용되어 대형 포지션 매도 불가
+  - JELD stop-loss -6.20% → 차단, RXT take-profit +46.13% → 차단
+  - 수정: SELL은 `check_circuit_breaker`만 호출, `validate_order`(Fat Finger 포함) 미호출
+
+---
+
+## 2026-02-20
+
+### 지속적 모니터링 및 개선점 도출 (이슈 #178~#182)
+
+- Dashboard 포함해서 실행하며 간헐적 문제 모니터링 및 개선점 자동 도출 요청
+- 모니터링 결과 발견된 이슈 목록:
+  - **#178**: uvicorn 미설치 → dashboard 미작동 + 오해의 소지 있는 시작 로그 → uvicorn 설치 완료
+  - **#179 (Critical)**: 잔액 부족 주문 실패 후 매 사이클마다 무한 재시도 (MLECW 20분 이상 반복)
+  - **#180**: 다중 인스턴스 실행 시 Telegram 409 충돌
+  - **#181**: implied_rsi 공식 포화 문제 (change_rate≥12.5% → RSI=100)
+  - **#182 (Critical)**: 보유 종목이 SmartScanner 변동성 필터에 걸려 SELL 신호 미생성 → SELL 체결 0건, 잔고 소진
+- 요구사항: 모니터링 자동화 및 주기적 개선점 리포트 도출
+
+---
+
 ## 2026-02-05
 
 ### API 효율화
@@ -165,3 +191,104 @@
 **효과:**
 - 국내/해외 스캐너 기준이 변동성 중심으로 일관화
 - 고변동 구간에서 자동 익스포저 축소, 저변동 구간에서 과소진입 완화
+
+## 2026-02-18
+
+### KIS 해외 랭킹 API 404 에러 수정
+
+**배경:**
+- KIS 해외주식 랭킹 API(`fetch_overseas_rankings`)가 모든 거래소에서 HTTP 404를 반환
+- Smart Scanner가 해외 시장 후보 종목을 찾지 못해 거래가 전혀 실행되지 않음
+
+**근본 원인:**
+- TR_ID, API 경로, 거래소 코드가 모두 KIS 공식 문서와 불일치
+
+**구현 결과:**
+- `src/config.py`: TR_ID/Path 기본값을 KIS 공식 스펙으로 수정
+- `src/broker/overseas.py`: 랭킹 API 전용 거래소 코드 매핑 추가 (NASD→NAS, NYSE→NYS, AMEX→AMS), 올바른 API 파라미터 사용
+- `tests/test_overseas_broker.py`: 19개 단위 테스트 추가
+
+**효과:**
+- 해외 시장 랭킹 스캔이 정상 동작하여 Smart Scanner가 후보 종목 탐지 가능
+
+### Gemini prompt_override 미적용 버그 수정
+
+**배경:**
+- `run_overnight` 실행 시 모든 시장에서 Playbook 생성 실패 (`JSONDecodeError`)
+- defensive playbook으로 폴백되어 모든 종목이 HOLD 처리
+
+**근본 원인:**
+- `pre_market_planner.py`가 `market_data["prompt_override"]`에 Playbook 전용 프롬프트를 넣어 `gemini.decide()` 호출
+- `gemini_client.py`의 `decide()` 메서드가 `prompt_override` 키를 전혀 확인하지 않고 항상 일반 트레이드 결정 프롬프트 생성
+- Gemini가 Playbook JSON 대신 일반 트레이드 결정을 반환하여 파싱 실패
+
+**구현 결과:**
+- `src/brain/gemini_client.py`: `decide()` 메서드에서 `prompt_override` 우선 사용 로직 추가
+- `tests/test_brain.py`: 3개 테스트 추가 (override 전달, optimization 우회, 미지정 시 기존 동작 유지)
+
+**이슈/PR:** #143
+
+### 미국장 거래 미실행 근본 원인 분석 및 수정 (자율 실행 세션)
+
+**배경:**
+- 사용자 요청: "미국장 열면 프로그램 돌려서 거래 한 번도 못 한 거 꼭 원인 찾아서 해결해줘"
+- 프로그램을 미국장 개장(9:30 AM EST) 전부터 실행하여 실시간 로그를 분석
+
+**발견된 근본 원인 #1: Defensive Playbook — BUY 조건 없음**
+
+- Gemini free tier (20 RPD) 소진 → `generate_playbook()` 실패 → `_defensive_playbook()` 폴백
+- Defensive playbook은 `price_change_pct_below: -3.0 → SELL` 조건만 존재, BUY 조건 없음
+- ScenarioEngine이 항상 HOLD 반환 → 거래 0건
+
+**수정 #1 (PR #146, Issue #145):**
+- `src/strategy/pre_market_planner.py`: `_smart_fallback_playbook()` 메서드 추가
+  - 스캐너 signal 기반 BUY 조건 생성: `momentum → volume_ratio_above`, `oversold → rsi_below`
+  - 기존 defensive stop-loss SELL 조건 유지
+- Gemini 실패 시 defensive → smart fallback으로 전환
+- 테스트 10개 추가
+
+**발견된 근본 원인 #2: 가격 API 거래소 코드 불일치 + VTS 잔고 API 오류**
+
+실제 로그:
+```
+Scenario matched for MRNX: BUY (confidence=80)  ✓
+Decision for EWUS (NYSE American): BUY (confidence=80)  ✓
+Skip BUY APLZ (NYSE American): no affordable quantity (cash=0.00, price=0.00)  ✗
+```
+
+- `get_overseas_price()`: `NASD`/`NYSE`/`AMEX` 전송 → API가 `NAS`/`NYS`/`AMS` 기대 → 빈 응답 → `price=0`
+- `VTTS3012R` 잔고 API: "ERROR : INPUT INVALID_CHECK_ACNO" → `total_cash=0`
+- 결과: `_determine_order_quantity()` 가 0 반환 → 주문 건너뜀
+
+**수정 #2 (PR #148, Issue #147):**
+- `src/broker/overseas.py`: `_PRICE_EXCHANGE_MAP = _RANKING_EXCHANGE_MAP` 추가, 가격 API에 매핑 적용
+- `src/config.py`: `PAPER_OVERSEAS_CASH: float = Field(default=50000.0)` — paper 모드 시뮬레이션 잔고
+- `src/main.py`: 잔고 0일 때 PAPER_OVERSEAS_CASH 폴백, 가격 0일 때 candidate.price 폴백
+- 테스트 8개 추가
+
+**효과:**
+- BUY 결정 → 실제 주문 전송까지의 파이프라인이 완전히 동작
+- Paper 모드에서 KIS VTS 해외 잔고 API 오류에 관계없이 시뮬레이션 거래 가능
+
+**이슈/PR:** #145, #146, #147, #148
+
+### 해외주식 시장가 주문 거부 수정 (Fix #3, 연속 발견)
+
+**배경:**
+- Fix #147 적용 후 주문 전송 시작 → KIS VTS가 거부: "지정가만 가능한 상품입니다"
+
+**근본 원인:**
+- `trading_cycle()`, `run_daily_session()` 양쪽에서 `send_overseas_order(price=0.0)` 하드코딩
+- `price=0` → `ORD_DVSN="01"` (시장가) 전송 → KIS VTS 거부
+- Fix #147에서 이미 `current_price`를 올바르게 계산했으나 주문 시 미사용
+
+**구현 결과:**
+- `src/main.py`: 두 곳에서 `price=0.0` → `price=current_price`/`price=stock_data["current_price"]`
+- `tests/test_main.py`: 회귀 테스트 `test_overseas_buy_order_uses_limit_price` 추가
+
+**최종 확인 로그:**
+```
+Order result: 모의투자 매수주문이 완료 되었습니다.  ✓
+```
+
+**이슈/PR:** #149, #150

scripts/morning_report.sh

@@ -0,0 +1,54 @@
+#!/usr/bin/env bash
+# Morning summary for overnight run logs.
+
+set -euo pipefail
+
+LOG_DIR="${LOG_DIR:-data/overnight}"
+
+if [ ! -d "$LOG_DIR" ]; then
+    echo "로그 디렉터리가 없습니다: $LOG_DIR"
+    exit 1
+fi
+
+latest_run="$(ls -1t "$LOG_DIR"/run_*.log 2>/dev/null | head -n 1 || true)"
+latest_watchdog="$(ls -1t "$LOG_DIR"/watchdog_*.log 2>/dev/null | head -n 1 || true)"
+
+if [ -z "$latest_run" ]; then
+    echo "run 로그가 없습니다: $LOG_DIR/run_*.log"
+    exit 1
+fi
+
+echo "Overnight report"
+echo "- run log: $latest_run"
+if [ -n "$latest_watchdog" ]; then
+    echo "- watchdog log: $latest_watchdog"
+fi
+
+start_line="$(head -n 1 "$latest_run" || true)"
+end_line="$(tail -n 1 "$latest_run" || true)"
+
+info_count="$(rg -c '"level": "INFO"' "$latest_run" || true)"
+warn_count="$(rg -c '"level": "WARNING"' "$latest_run" || true)"
+error_count="$(rg -c '"level": "ERROR"' "$latest_run" || true)"
+critical_count="$(rg -c '"level": "CRITICAL"' "$latest_run" || true)"
+traceback_count="$(rg -c 'Traceback' "$latest_run" || true)"
+
+echo "- start: ${start_line:-N/A}"
+echo "- end:   ${end_line:-N/A}"
+echo "- INFO: ${info_count:-0}"
+echo "- WARNING: ${warn_count:-0}"
+echo "- ERROR: ${error_count:-0}"
+echo "- CRITICAL: ${critical_count:-0}"
+echo "- Traceback: ${traceback_count:-0}"
+
+if [ -n "$latest_watchdog" ]; then
+    watchdog_errors="$(rg -c '\[ERROR\]' "$latest_watchdog" || true)"
+    echo "- watchdog ERROR: ${watchdog_errors:-0}"
+    echo ""
+    echo "최근 watchdog 로그:"
+    tail -n 5 "$latest_watchdog" || true
+fi
+
+echo ""
+echo "최근 앱 로그:"
+tail -n 20 "$latest_run" || true

scripts/run_overnight.sh

@@ -0,0 +1,87 @@
+#!/usr/bin/env bash
+# Start The Ouroboros overnight with logs and watchdog.
+
+set -euo pipefail
+
+LOG_DIR="${LOG_DIR:-data/overnight}"
+CHECK_INTERVAL="${CHECK_INTERVAL:-30}"
+TMUX_AUTO="${TMUX_AUTO:-true}"
+TMUX_ATTACH="${TMUX_ATTACH:-true}"
+TMUX_SESSION_PREFIX="${TMUX_SESSION_PREFIX:-ouroboros_overnight}"
+
+if [ -z "${APP_CMD:-}" ]; then
+    if [ -x ".venv/bin/python" ]; then
+        PYTHON_BIN=".venv/bin/python"
+    elif command -v python3 >/dev/null 2>&1; then
+        PYTHON_BIN="python3"
+    elif command -v python >/dev/null 2>&1; then
+        PYTHON_BIN="python"
+    else
+        echo ".venv/bin/python 또는 python3/python 실행 파일을 찾을 수 없습니다."
+        exit 1
+    fi
+
+    dashboard_port="${DASHBOARD_PORT:-8080}"
+
+    APP_CMD="DASHBOARD_PORT=$dashboard_port $PYTHON_BIN -m src.main --mode=paper --dashboard"
+fi
+
+mkdir -p "$LOG_DIR"
+
+timestamp="$(date +"%Y%m%d_%H%M%S")"
+RUN_LOG="$LOG_DIR/run_${timestamp}.log"
+WATCHDOG_LOG="$LOG_DIR/watchdog_${timestamp}.log"
+PID_FILE="$LOG_DIR/app.pid"
+WATCHDOG_PID_FILE="$LOG_DIR/watchdog.pid"
+
+if [ -f "$PID_FILE" ]; then
+    old_pid="$(cat "$PID_FILE" || true)"
+    if [ -n "$old_pid" ] && kill -0 "$old_pid" 2>/dev/null; then
+        echo "앱이 이미 실행 중입니다. pid=$old_pid"
+        exit 1
+    fi
+fi
+
+echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] starting: $APP_CMD" | tee -a "$RUN_LOG"
+nohup bash -lc "$APP_CMD" >>"$RUN_LOG" 2>&1 &
+app_pid=$!
+echo "$app_pid" > "$PID_FILE"
+
+echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] app pid=$app_pid" | tee -a "$RUN_LOG"
+
+nohup env PID_FILE="$PID_FILE" LOG_FILE="$WATCHDOG_LOG" CHECK_INTERVAL="$CHECK_INTERVAL" \
+    bash scripts/watchdog.sh >/dev/null 2>&1 &
+watchdog_pid=$!
+echo "$watchdog_pid" > "$WATCHDOG_PID_FILE"
+
+cat <<EOF
+시작 완료
+- app pid: $app_pid
+- watchdog pid: $watchdog_pid
+- app log: $RUN_LOG
+- watchdog log: $WATCHDOG_LOG
+
+실시간 확인:
+tail -f "$RUN_LOG"
+tail -f "$WATCHDOG_LOG"
+EOF
+
+if [ "$TMUX_AUTO" = "true" ]; then
+    if ! command -v tmux >/dev/null 2>&1; then
+        echo "tmux를 찾지 못해 자동 세션 생성은 건너뜁니다."
+        exit 0
+    fi
+
+    session_name="${TMUX_SESSION_PREFIX}_${timestamp}"
+    window_name="overnight"
+    tmux new-session -d -s "$session_name" -n "$window_name" "tail -f '$RUN_LOG'"
+    tmux split-window -t "${session_name}:${window_name}" -v "tail -f '$WATCHDOG_LOG'"
+    tmux select-layout -t "${session_name}:${window_name}" even-vertical
+
+    echo "tmux session 생성: $session_name"
+    echo "수동 접속: tmux attach -t $session_name"
+
+    if [ -z "${TMUX:-}" ] && [ "$TMUX_ATTACH" = "true" ]; then
+        tmux attach -t "$session_name"
+    fi
+fi

scripts/stop_overnight.sh

@@ -0,0 +1,76 @@
+#!/usr/bin/env bash
+# Stop The Ouroboros overnight app/watchdog/tmux session.
+
+set -euo pipefail
+
+LOG_DIR="${LOG_DIR:-data/overnight}"
+PID_FILE="$LOG_DIR/app.pid"
+WATCHDOG_PID_FILE="$LOG_DIR/watchdog.pid"
+TMUX_SESSION_PREFIX="${TMUX_SESSION_PREFIX:-ouroboros_overnight}"
+KILL_TIMEOUT="${KILL_TIMEOUT:-5}"
+
+stop_pid() {
+    local name="$1"
+    local pid="$2"
+
+    if [ -z "$pid" ]; then
+        echo "$name PID가 비어 있습니다."
+        return 1
+    fi
+
+    if ! kill -0 "$pid" 2>/dev/null; then
+        echo "$name 프로세스가 이미 종료됨 (pid=$pid)"
+        return 0
+    fi
+
+    kill "$pid" 2>/dev/null || true
+    for _ in $(seq 1 "$KILL_TIMEOUT"); do
+        if ! kill -0 "$pid" 2>/dev/null; then
+            echo "$name 종료됨 (pid=$pid)"
+            return 0
+        fi
+        sleep 1
+    done
+
+    kill -9 "$pid" 2>/dev/null || true
+    if ! kill -0 "$pid" 2>/dev/null; then
+        echo "$name 강제 종료됨 (pid=$pid)"
+        return 0
+    fi
+
+    echo "$name 종료 실패 (pid=$pid)"
+    return 1
+}
+
+status=0
+
+if [ -f "$WATCHDOG_PID_FILE" ]; then
+    watchdog_pid="$(cat "$WATCHDOG_PID_FILE" || true)"
+    stop_pid "watchdog" "$watchdog_pid" || status=1
+    rm -f "$WATCHDOG_PID_FILE"
+else
+    echo "watchdog pid 파일 없음: $WATCHDOG_PID_FILE"
+fi
+
+if [ -f "$PID_FILE" ]; then
+    app_pid="$(cat "$PID_FILE" || true)"
+    stop_pid "app" "$app_pid" || status=1
+    rm -f "$PID_FILE"
+else
+    echo "app pid 파일 없음: $PID_FILE"
+fi
+
+if command -v tmux >/dev/null 2>&1; then
+    sessions="$(tmux ls 2>/dev/null | awk -F: -v p="$TMUX_SESSION_PREFIX" '$1 ~ "^" p "_" {print $1}')"
+    if [ -n "$sessions" ]; then
+        while IFS= read -r s; do
+            [ -z "$s" ] && continue
+            tmux kill-session -t "$s" 2>/dev/null || true
+            echo "tmux 세션 종료: $s"
+        done <<< "$sessions"
+    else
+        echo "종료할 tmux 세션 없음 (prefix=${TMUX_SESSION_PREFIX}_)"
+    fi
+fi
+
+exit "$status"

scripts/watchdog.sh

@@ -0,0 +1,42 @@
+#!/usr/bin/env bash
+# Simple watchdog for The Ouroboros process.
+
+set -euo pipefail
+
+PID_FILE="${PID_FILE:-data/overnight/app.pid}"
+LOG_FILE="${LOG_FILE:-data/overnight/watchdog.log}"
+CHECK_INTERVAL="${CHECK_INTERVAL:-30}"
+STATUS_EVERY="${STATUS_EVERY:-10}"
+
+mkdir -p "$(dirname "$LOG_FILE")"
+
+log() {
+    printf '%s %s\n' "$(date -u +"%Y-%m-%dT%H:%M:%SZ")" "$1" | tee -a "$LOG_FILE"
+}
+
+if [ ! -f "$PID_FILE" ]; then
+    log "[ERROR] pid file not found: $PID_FILE"
+    exit 1
+fi
+
+PID="$(cat "$PID_FILE")"
+if [ -z "$PID" ]; then
+    log "[ERROR] pid file is empty: $PID_FILE"
+    exit 1
+fi
+
+log "[INFO] watchdog started (pid=$PID, interval=${CHECK_INTERVAL}s)"
+
+count=0
+while true; do
+    if kill -0 "$PID" 2>/dev/null; then
+        count=$((count + 1))
+        if [ $((count % STATUS_EVERY)) -eq 0 ]; then
+            log "[INFO] process alive (pid=$PID)"
+        fi
+    else
+        log "[ERROR] process stopped (pid=$PID)"
+        exit 1
+    fi
+    sleep "$CHECK_INTERVAL"
+done

src/analysis/smart_scanner.py

@@ -175,7 +175,7 @@ class SmartVolatilityScanner:
                 liquidity_score = volume_rank_bonus.get(stock_code, 0.0)
                 score = min(100.0, volatility_score + liquidity_score)
                 signal = "momentum" if change_rate >= 0 else "oversold"
-                implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 4.0)))
+                implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 2.0)))
 
                 candidates.append(
                     ScanCandidate(
@@ -282,7 +282,7 @@ class SmartVolatilityScanner:
             liquidity_score = volume_rank_bonus.get(stock_code, 0.0)
             score = min(100.0, volatility_score + liquidity_score)
             signal = "momentum" if change_rate >= 0 else "oversold"
-            implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 4.0)))
+            implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 2.0)))
             candidates.append(
                 ScanCandidate(
                     stock_code=stock_code,
@@ -315,6 +315,11 @@ class SmartVolatilityScanner:
             logger.info("Overseas scanner: no symbol universe for %s", market.name)
             return []
 
+        logger.info(
+            "Overseas scanner: scanning %d fallback symbols for %s",
+            len(symbols),
+            market.name,
+        )
         candidates: list[ScanCandidate] = []
         for stock_code in symbols:
             try:
@@ -333,7 +338,7 @@ class SmartVolatilityScanner:
 
                 score = min(volatility_pct / 10.0, 1.0) * 100.0
                 signal = "momentum" if change_rate >= 0 else "oversold"
-                implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 4.0)))
+                implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 2.0)))
                 candidates.append(
                     ScanCandidate(
                         stock_code=stock_code,
@@ -350,6 +355,11 @@ class SmartVolatilityScanner:
                 logger.warning("Failed to analyze overseas %s: %s", stock_code, exc)
             except Exception as exc:
                 logger.error("Unexpected error analyzing overseas %s: %s", stock_code, exc)
+        logger.info(
+            "Overseas symbol fallback scan found %d candidates for %s",
+            len(candidates),
+            market.name,
+        )
         return candidates
 
     def get_stock_codes(self, candidates: list[ScanCandidate]) -> list[str]:

src/brain/gemini_client.py

@@ -410,8 +410,10 @@ class GeminiClient:
                     cached=True,
                 )
 
-        # Build optimized prompt
+        # Build prompt (prompt_override takes priority for callers like pre_market_planner)
-        if self._enable_optimization:
+        if "prompt_override" in market_data:
+            prompt = market_data["prompt_override"]
+        elif self._enable_optimization:
             prompt = self._optimizer.build_compressed_prompt(market_data)
         else:
             prompt = await self.build_prompt(market_data, news_sentiment)

src/broker/kis_api.py

@@ -20,6 +20,39 @@ _KIS_VTS_HOST = "openapivts.koreainvestment.com"
 logger = logging.getLogger(__name__)
 
 
+def kr_tick_unit(price: float) -> int:
+    """Return KRX tick size for the given price level.
+
+    KRX price tick rules (domestic stocks):
+        price < 2,000        →   1원
+        2,000  ≤ price < 5,000     →   5원
+        5,000  ≤ price < 20,000    →  10원
+        20,000 ≤ price < 50,000    →  50원
+        50,000 ≤ price < 200,000   → 100원
+        200,000 ≤ price < 500,000  → 500원
+        500,000 ≤ price            → 1,000원
+    """
+    if price < 2_000:
+        return 1
+    if price < 5_000:
+        return 5
+    if price < 20_000:
+        return 10
+    if price < 50_000:
+        return 50
+    if price < 200_000:
+        return 100
+    if price < 500_000:
+        return 500
+    return 1_000
+
+
+def kr_round_down(price: float) -> int:
+    """Round *down* price to the nearest KRX tick unit."""
+    tick = kr_tick_unit(price)
+    return int(price // tick * tick)
+
+
 class LeakyBucket:
     """Simple leaky-bucket rate limiter for async code."""
 
@@ -104,12 +137,14 @@ class KISBroker:
             time_since_last_attempt = now - self._last_refresh_attempt
             if time_since_last_attempt < self._refresh_cooldown:
                 remaining = self._refresh_cooldown - time_since_last_attempt
-                error_msg = (
+                # Do not fail fast here. If token is unavailable, upstream calls
-                    f"Token refresh on cooldown. "
+                # will all fail for up to a minute and scanning returns no trades.
-                    f"Retry in {remaining:.1f}s (KIS allows 1/minute)"
+                logger.warning(
+                    "Token refresh on cooldown. Waiting %.1fs before retry (KIS allows 1/minute)",
+                    remaining,
                 )
-                logger.warning(error_msg)
+                await asyncio.sleep(remaining)
-                raise ConnectionError(error_msg)
+                now = asyncio.get_event_loop().time()
 
             logger.info("Refreshing KIS access token")
             self._last_refresh_attempt = now
@@ -196,12 +231,64 @@ class KISBroker:
         except (TimeoutError, aiohttp.ClientError) as exc:
             raise ConnectionError(f"Network error fetching orderbook: {exc}") from exc
 
+    async def get_current_price(
+        self, stock_code: str
+    ) -> tuple[float, float, float]:
+        """Fetch current price data for a domestic stock.
+
+        Uses the ``inquire-price`` API (FHKST01010100), which works in both
+        real and VTS environments and returns the actual last-traded price.
+
+        Returns:
+            (current_price, prdy_ctrt, frgn_ntby_qty)
+            - current_price: Last traded price in KRW.
+            - prdy_ctrt: Day change rate (%).
+            - frgn_ntby_qty: Foreigner net buy quantity.
+        """
+        await self._rate_limiter.acquire()
+        session = self._get_session()
+
+        headers = await self._auth_headers("FHKST01010100")
+        params = {
+            "FID_COND_MRKT_DIV_CODE": "J",
+            "FID_INPUT_ISCD": stock_code,
+        }
+        url = f"{self._base_url}/uapi/domestic-stock/v1/quotations/inquire-price"
+
+        def _f(val: str | None) -> float:
+            try:
+                return float(val or "0")
+            except ValueError:
+                return 0.0
+
+        try:
+            async with session.get(url, headers=headers, params=params) as resp:
+                if resp.status != 200:
+                    text = await resp.text()
+                    raise ConnectionError(
+                        f"get_current_price failed ({resp.status}): {text}"
+                    )
+                data = await resp.json()
+                out = data.get("output", {})
+                return (
+                    _f(out.get("stck_prpr")),
+                    _f(out.get("prdy_ctrt")),
+                    _f(out.get("frgn_ntby_qty")),
+                )
+        except (TimeoutError, aiohttp.ClientError) as exc:
+            raise ConnectionError(
+                f"Network error fetching current price: {exc}"
+            ) from exc
+
     async def get_balance(self) -> dict[str, Any]:
         """Fetch current account balance and holdings."""
         await self._rate_limiter.acquire()
         session = self._get_session()
 
-        headers = await self._auth_headers("VTTC8434R")  # 모의투자 잔고조회
+        # TR_ID: 실전 TTTC8434R, 모의 VTTC8434R
+        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '국내주식 잔고조회' 시트
+        tr_id = "TTTC8434R" if self._settings.MODE == "live" else "VTTC8434R"
+        headers = await self._auth_headers(tr_id)
         params = {
             "CANO": self._account_no,
             "ACNT_PRDT_CD": self._product_cd,
@@ -246,14 +333,30 @@ class KISBroker:
         await self._rate_limiter.acquire()
         session = self._get_session()
 
-        tr_id = "VTTC0802U" if order_type == "BUY" else "VTTC0801U"
+        # TR_ID: 실전 BUY=TTTC0012U SELL=TTTC0011U, 모의 BUY=VTTC0012U SELL=VTTC0011U
+        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '주식주문(현금)' 시트
+        # ※ TTTC0802U/VTTC0802U는 미수매수(증거금40% 계좌 전용) — 현금주문에 사용 금지
+        if self._settings.MODE == "live":
+            tr_id = "TTTC0012U" if order_type == "BUY" else "TTTC0011U"
+        else:
+            tr_id = "VTTC0012U" if order_type == "BUY" else "VTTC0011U"
+
+        # KRX requires limit orders to be rounded down to the tick unit.
+        # ORD_DVSN: "00"=지정가, "01"=시장가
+        if price > 0:
+            ord_dvsn = "00"  # 지정가
+            ord_price = kr_round_down(price)
+        else:
+            ord_dvsn = "01"  # 시장가
+            ord_price = 0
+
         body = {
             "CANO": self._account_no,
             "ACNT_PRDT_CD": self._product_cd,
             "PDNO": stock_code,
-            "ORD_DVSN": "01" if price > 0 else "06",  # 01=지정가, 06=시장가
+            "ORD_DVSN": ord_dvsn,
             "ORD_QTY": str(quantity),
-            "ORD_UNPR": str(price),
+            "ORD_UNPR": str(ord_price),
         }
 
         hash_key = await self._get_hash_key(body)
@@ -302,26 +405,46 @@ class KISBroker:
         await self._rate_limiter.acquire()
         session = self._get_session()
 
-        # TR_ID for volume ranking
+        if ranking_type == "volume":
-        tr_id = "FHPST01710000" if ranking_type == "volume" else "FHPST01710100"
+            # 거래량순위: FHPST01710000 / /quotations/volume-rank
+            tr_id = "FHPST01710000"
+            url = f"{self._base_url}/uapi/domestic-stock/v1/quotations/volume-rank"
+            params: dict[str, str] = {
+                "FID_COND_MRKT_DIV_CODE": "J",
+                "FID_COND_SCR_DIV_CODE": "20171",
+                "FID_INPUT_ISCD": "0000",
+                "FID_DIV_CLS_CODE": "0",
+                "FID_BLNG_CLS_CODE": "0",
+                "FID_TRGT_CLS_CODE": "111111111",
+                "FID_TRGT_EXLS_CLS_CODE": "0000000000",
+                "FID_INPUT_PRICE_1": "0",
+                "FID_INPUT_PRICE_2": "0",
+                "FID_VOL_CNT": "0",
+                "FID_INPUT_DATE_1": "",
+            }
+        else:
+            # 등락률순위: FHPST01700000 / /ranking/fluctuation (소문자 파라미터)
+            tr_id = "FHPST01700000"
+            url = f"{self._base_url}/uapi/domestic-stock/v1/ranking/fluctuation"
+            params = {
+                "fid_cond_mrkt_div_code": "J",
+                "fid_cond_scr_div_code": "20170",
+                "fid_input_iscd": "0000",
+                "fid_rank_sort_cls_code": "0000",
+                "fid_input_cnt_1": str(limit),
+                "fid_prc_cls_code": "0",
+                "fid_input_price_1": "0",
+                "fid_input_price_2": "0",
+                "fid_vol_cnt": "0",
+                "fid_trgt_cls_code": "0",
+                "fid_trgt_exls_cls_code": "0",
+                "fid_div_cls_code": "0",
+                "fid_rsfl_rate1": "0",
+                "fid_rsfl_rate2": "0",
+            }
+
         headers = await self._auth_headers(tr_id)
 
-        params = {
-            "FID_COND_MRKT_DIV_CODE": "J",  # Stock/ETF/ETN
-            "FID_COND_SCR_DIV_CODE": "20001",  # Volume surge
-            "FID_INPUT_ISCD": "0000",  # All stocks
-            "FID_DIV_CLS_CODE": "0",  # All types
-            "FID_BLNG_CLS_CODE": "0",
-            "FID_TRGT_CLS_CODE": "111111111",
-            "FID_TRGT_EXLS_CLS_CODE": "000000",
-            "FID_INPUT_PRICE_1": "0",
-            "FID_INPUT_PRICE_2": "0",
-            "FID_VOL_CNT": "0",
-            "FID_INPUT_DATE_1": "",
-        }
-
-        url = f"{self._base_url}/uapi/domestic-stock/v1/quotations/volume-rank"
-
         try:
             async with session.get(url, headers=headers, params=params) as resp:
                 if resp.status != 200:

src/broker/overseas.py

@@ -12,6 +12,24 @@ from src.broker.kis_api import KISBroker
 logger = logging.getLogger(__name__)
 
 
+# Ranking API uses different exchange codes than order/quote APIs.
+_RANKING_EXCHANGE_MAP: dict[str, str] = {
+    "NASD": "NAS",
+    "NYSE": "NYS",
+    "AMEX": "AMS",
+    "SEHK": "HKS",
+    "SHAA": "SHS",
+    "SZAA": "SZS",
+    "HSX": "HSX",
+    "HNX": "HNX",
+    "TSE": "TSE",
+}
+
+# Price inquiry API (HHDFS00000300) uses the same short exchange codes as rankings.
+# NASD → NAS, NYSE → NYS, AMEX → AMS (confirmed: AMEX returns empty, AMS returns price).
+_PRICE_EXCHANGE_MAP: dict[str, str] = _RANKING_EXCHANGE_MAP
+
+
 class OverseasBroker:
     """KIS Overseas Stock API wrapper that reuses KISBroker infrastructure."""
 
@@ -44,9 +62,11 @@ class OverseasBroker:
         session = self._broker._get_session()
 
         headers = await self._broker._auth_headers("HHDFS00000300")
+        # Map internal exchange codes to the short form expected by the price API.
+        price_excd = _PRICE_EXCHANGE_MAP.get(exchange_code, exchange_code)
         params = {
             "AUTH": "",
-            "EXCD": exchange_code,
+            "EXCD": price_excd,
             "SYMB": stock_code,
         }
         url = f"{self._broker._base_url}/uapi/overseas-price/v1/quotations/price"
@@ -70,7 +90,7 @@ class OverseasBroker:
         ranking_type: str = "fluctuation",
         limit: int = 30,
     ) -> list[dict[str, Any]]:
-        """Fetch overseas rankings (price change or volume amount).
+        """Fetch overseas rankings (price change or volume surge).
 
         Ranking API specs may differ by account/product. Endpoint paths and
         TR_IDs are configurable via settings and can be overridden in .env.
@@ -81,47 +101,63 @@ class OverseasBroker:
         await self._broker._rate_limiter.acquire()
         session = self._broker._get_session()
 
+        ranking_excd = _RANKING_EXCHANGE_MAP.get(exchange_code, exchange_code)
+
         if ranking_type == "volume":
             tr_id = self._broker._settings.OVERSEAS_RANKING_VOLUME_TR_ID
             path = self._broker._settings.OVERSEAS_RANKING_VOLUME_PATH
+            params: dict[str, str] = {
+                "AUTH": "",
+                "EXCD": ranking_excd,
+                "MIXN": "0",
+                "VOL_RANG": "0",
+            }
         else:
             tr_id = self._broker._settings.OVERSEAS_RANKING_FLUCT_TR_ID
             path = self._broker._settings.OVERSEAS_RANKING_FLUCT_PATH
+            params = {
+                "AUTH": "",
+                "EXCD": ranking_excd,
+                "NDAY": "0",
+                "GUBN": "1",
+                "VOL_RANG": "0",
+            }
 
         headers = await self._broker._auth_headers(tr_id)
         url = f"{self._broker._base_url}{path}"
 
-        # Try common param variants used by KIS overseas quotation APIs.
+        try:
-        param_variants = [
+            async with session.get(url, headers=headers, params=params) as resp:
-            {"AUTH": "", "EXCD": exchange_code, "NREC": str(max(limit, 30))},
+                if resp.status != 200:
-            {"AUTH": "", "OVRS_EXCG_CD": exchange_code, "NREC": str(max(limit, 30))},
-            {"AUTH": "", "EXCD": exchange_code},
-            {"AUTH": "", "OVRS_EXCG_CD": exchange_code},
-        ]
-
-        last_error: str | None = None
-        for params in param_variants:
-            try:
-                async with session.get(url, headers=headers, params=params) as resp:
                     text = await resp.text()
-                    if resp.status != 200:
+                    if resp.status == 404:
-                        last_error = f"HTTP {resp.status}: {text}"
+                        logger.warning(
-                        continue
+                            "Overseas ranking endpoint unavailable (404) for %s/%s; "
+                            "using symbol fallback scan",
+                            exchange_code,
+                            ranking_type,
+                        )
+                        return []
+                    raise ConnectionError(
+                        f"fetch_overseas_rankings failed ({resp.status}): {text}"
+                    )
 
-                    data = await resp.json()
+                data = await resp.json()
-                    rows = self._extract_ranking_rows(data)
+                rows = self._extract_ranking_rows(data)
-                    if rows:
+                if rows:
-                        return rows[:limit]
+                    return rows[:limit]
 
-                    # keep trying another param variant if response has no usable rows
+                logger.debug(
-                    last_error = f"empty output (keys={list(data.keys())})"
+                    "Overseas ranking returned empty for %s/%s (keys=%s)",
-            except (TimeoutError, aiohttp.ClientError) as exc:
+                    exchange_code,
-                last_error = str(exc)
+                    ranking_type,
-                continue
+                    list(data.keys()),
-
+                )
-        raise ConnectionError(
+                return []
-            f"fetch_overseas_rankings failed for {exchange_code}/{ranking_type}: {last_error}"
+        except (TimeoutError, aiohttp.ClientError) as exc:
-        )
+            raise ConnectionError(
+                f"Network error fetching overseas rankings: {exc}"
+            ) from exc
 
     async def get_overseas_balance(self, exchange_code: str) -> dict[str, Any]:
         """
@@ -139,8 +175,12 @@ class OverseasBroker:
         await self._broker._rate_limiter.acquire()
         session = self._broker._get_session()
 
-        # Virtual trading TR_ID for overseas balance inquiry
+        # TR_ID: 실전 TTTS3012R, 모의 VTTS3012R
-        headers = await self._broker._auth_headers("VTTS3012R")
+        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 잔고조회' 시트
+        balance_tr_id = (
+            "TTTS3012R" if self._broker._settings.MODE == "live" else "VTTS3012R"
+        )
+        headers = await self._broker._auth_headers(balance_tr_id)
         params = {
             "CANO": self._broker._account_no,
             "ACNT_PRDT_CD": self._broker._product_cd,
@@ -193,8 +233,12 @@ class OverseasBroker:
         await self._broker._rate_limiter.acquire()
         session = self._broker._get_session()
 
-        # Virtual trading TR_IDs for overseas orders
+        # TR_ID: 실전 BUY=TTTT1002U SELL=TTTT1006U, 모의 BUY=VTTT1002U SELL=VTTT1001U
-        tr_id = "VTTT1002U" if order_type == "BUY" else "VTTT1006U"
+        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 주문' 시트
+        if self._broker._settings.MODE == "live":
+            tr_id = "TTTT1002U" if order_type == "BUY" else "TTTT1006U"
+        else:
+            tr_id = "VTTT1002U" if order_type == "BUY" else "VTTT1001U"
 
         body = {
             "CANO": self._broker._account_no,
@@ -221,14 +265,27 @@ class OverseasBroker:
                         f"send_overseas_order failed ({resp.status}): {text}"
                     )
                 data = await resp.json()
-                logger.info(
+                rt_cd = data.get("rt_cd", "")
-                    "Overseas order submitted",
+                msg1 = data.get("msg1", "")
-                    extra={
+                if rt_cd == "0":
-                        "exchange": exchange_code,
+                    logger.info(
-                        "stock_code": stock_code,
+                        "Overseas order submitted",
-                        "action": order_type,
+                        extra={
-                    },
+                            "exchange": exchange_code,
-                )
+                            "stock_code": stock_code,
+                            "action": order_type,
+                        },
+                    )
+                else:
+                    logger.warning(
+                        "Overseas order rejected (rt_cd=%s): %s [%s %s %s qty=%d]",
+                        rt_cd,
+                        msg1,
+                        order_type,
+                        stock_code,
+                        exchange_code,
+                        quantity,
+                    )
                 return data
         except (TimeoutError, aiohttp.ClientError) as exc:
             raise ConnectionError(

src/config.py

@@ -13,11 +13,11 @@ class Settings(BaseSettings):
     KIS_APP_KEY: str
     KIS_APP_SECRET: str
     KIS_ACCOUNT_NO: str  # format: "XXXXXXXX-XX"
-    KIS_BASE_URL: str = "https://openapivts.koreainvestment.com:9443"
+    KIS_BASE_URL: str = "https://openapivts.koreainvestment.com:29443"
 
     # Google Gemini
     GEMINI_API_KEY: str
-    GEMINI_MODEL: str = "gemini-pro"
+    GEMINI_MODEL: str = "gemini-2.0-flash"
 
     # External Data APIs (optional — for data-driven decisions)
     NEWS_API_KEY: str | None = None
@@ -55,6 +55,11 @@ class Settings(BaseSettings):
     # Trading mode
     MODE: str = Field(default="paper", pattern="^(paper|live)$")
 
+    # Simulated USD cash for VTS (paper) overseas trading.
+    # KIS VTS overseas balance API returns errors for most accounts.
+    # This value is used as a fallback when the balance API returns 0 in paper mode.
+    PAPER_OVERSEAS_CASH: float = Field(default=50000.0, ge=0.0)
+
     # Trading frequency mode (daily = batch API calls, realtime = per-stock calls)
     TRADE_MODE: str = Field(default="daily", pattern="^(daily|realtime)$")
     DAILY_SESSIONS: int = Field(default=4, ge=1, le=10)
@@ -88,16 +93,26 @@ class Settings(BaseSettings):
     TELEGRAM_COMMANDS_ENABLED: bool = True
     TELEGRAM_POLLING_INTERVAL: float = 1.0  # seconds
 
+    # Telegram notification type filters (granular control)
+    # circuit_breaker is always sent regardless — safety-critical
+    TELEGRAM_NOTIFY_TRADES: bool = True           # BUY/SELL execution alerts
+    TELEGRAM_NOTIFY_MARKET_OPEN_CLOSE: bool = True  # Market open/close alerts
+    TELEGRAM_NOTIFY_FAT_FINGER: bool = True       # Fat-finger rejection alerts
+    TELEGRAM_NOTIFY_SYSTEM_EVENTS: bool = True    # System start/shutdown alerts
+    TELEGRAM_NOTIFY_PLAYBOOK: bool = True         # Playbook generated/failed alerts
+    TELEGRAM_NOTIFY_SCENARIO_MATCH: bool = True   # Scenario matched alerts (most frequent)
+    TELEGRAM_NOTIFY_ERRORS: bool = True           # Error alerts
+
     # Overseas ranking API (KIS endpoint/TR_ID may vary by account/product)
     # Override these from .env if your account uses different specs.
     OVERSEAS_RANKING_ENABLED: bool = True
-    OVERSEAS_RANKING_FLUCT_TR_ID: str = "HHDFS76200100"
+    OVERSEAS_RANKING_FLUCT_TR_ID: str = "HHDFS76290000"
-    OVERSEAS_RANKING_VOLUME_TR_ID: str = "HHDFS76200200"
+    OVERSEAS_RANKING_VOLUME_TR_ID: str = "HHDFS76270000"
     OVERSEAS_RANKING_FLUCT_PATH: str = (
-        "/uapi/overseas-price/v1/quotations/inquire-updown-rank"
+        "/uapi/overseas-stock/v1/ranking/updown-rate"
     )
     OVERSEAS_RANKING_VOLUME_PATH: str = (
-        "/uapi/overseas-price/v1/quotations/inquire-volume-rank"
+        "/uapi/overseas-stock/v1/ranking/volume-surge"
     )
 
     # Dashboard (optional)

src/dashboard/app.py

@@ -3,8 +3,9 @@
 from __future__ import annotations
 
 import json
+import os
 import sqlite3
-from datetime import UTC, datetime
+from datetime import UTC, datetime, timezone
 from pathlib import Path
 from typing import Any
 
@@ -79,6 +80,35 @@ def create_dashboard_app(db_path: str) -> FastAPI:
                 total_pnl += market_status[market]["total_pnl"]
                 total_decisions += market_status[market]["decision_count"]
 
+            cb_threshold = float(os.getenv("CIRCUIT_BREAKER_PCT", "-3.0"))
+            pnl_pct_rows = conn.execute(
+                """
+                SELECT key, value
+                FROM system_metrics
+                WHERE key LIKE 'portfolio_pnl_pct_%'
+                ORDER BY updated_at DESC
+                LIMIT 20
+                """
+            ).fetchall()
+            current_pnl_pct: float | None = None
+            if pnl_pct_rows:
+                values = [
+                    json.loads(row["value"]).get("pnl_pct")
+                    for row in pnl_pct_rows
+                    if json.loads(row["value"]).get("pnl_pct") is not None
+                ]
+                if values:
+                    current_pnl_pct = round(min(values), 4)
+
+            if current_pnl_pct is None:
+                cb_status = "unknown"
+            elif current_pnl_pct <= cb_threshold:
+                cb_status = "tripped"
+            elif current_pnl_pct <= cb_threshold + 1.0:
+                cb_status = "warning"
+            else:
+                cb_status = "ok"
+
             return {
                 "date": today,
                 "markets": market_status,
@@ -87,6 +117,11 @@ def create_dashboard_app(db_path: str) -> FastAPI:
                     "total_pnl": round(total_pnl, 2),
                     "decision_count": total_decisions,
                 },
+                "circuit_breaker": {
+                    "threshold_pct": cb_threshold,
+                    "current_pnl_pct": current_pnl_pct,
+                    "status": cb_status,
+                },
             }
 
     @app.get("/api/playbook/{date_str}")
@@ -259,6 +294,50 @@ def create_dashboard_app(db_path: str) -> FastAPI:
                 )
             return {"market": market, "count": len(decisions), "decisions": decisions}
 
+    @app.get("/api/pnl/history")
+    def get_pnl_history(
+        days: int = Query(default=30, ge=1, le=365),
+        market: str = Query("all"),
+    ) -> dict[str, Any]:
+        """Return daily P&L history for charting."""
+        with _connect(db_path) as conn:
+            if market == "all":
+                rows = conn.execute(
+                    """
+                    SELECT DATE(timestamp) AS date,
+                           SUM(pnl) AS daily_pnl,
+                           COUNT(*) AS trade_count
+                    FROM trades
+                    WHERE pnl IS NOT NULL
+                      AND DATE(timestamp) >= DATE('now', ?)
+                    GROUP BY DATE(timestamp)
+                    ORDER BY DATE(timestamp)
+                    """,
+                    (f"-{days} days",),
+                ).fetchall()
+            else:
+                rows = conn.execute(
+                    """
+                    SELECT DATE(timestamp) AS date,
+                           SUM(pnl) AS daily_pnl,
+                           COUNT(*) AS trade_count
+                    FROM trades
+                    WHERE pnl IS NOT NULL
+                      AND market = ?
+                      AND DATE(timestamp) >= DATE('now', ?)
+                    GROUP BY DATE(timestamp)
+                    ORDER BY DATE(timestamp)
+                    """,
+                    (market, f"-{days} days"),
+                ).fetchall()
+            return {
+                "days": days,
+                "market": market,
+                "labels": [row["date"] for row in rows],
+                "pnl": [round(float(row["daily_pnl"]), 2) for row in rows],
+                "trades": [int(row["trade_count"]) for row in rows],
+            }
+
     @app.get("/api/scenarios/active")
     def get_active_scenarios(
         market: str = Query("US"),
@@ -297,12 +376,68 @@ def create_dashboard_app(db_path: str) -> FastAPI:
                 )
             return {"market": market, "date": date_str, "count": len(matches), "matches": matches}
 
+    @app.get("/api/positions")
+    def get_positions() -> dict[str, Any]:
+        """Return all currently open positions (last trade per symbol is BUY)."""
+        with _connect(db_path) as conn:
+            rows = conn.execute(
+                """
+                SELECT stock_code, market, exchange_code,
+                       price AS entry_price, quantity, timestamp AS entry_time,
+                       decision_id
+                FROM (
+                    SELECT stock_code, market, exchange_code, price, quantity,
+                           timestamp, decision_id, action,
+                           ROW_NUMBER() OVER (
+                               PARTITION BY stock_code, market
+                               ORDER BY timestamp DESC
+                           ) AS rn
+                    FROM trades
+                )
+                WHERE rn = 1 AND action = 'BUY'
+                ORDER BY entry_time DESC
+                """
+            ).fetchall()
+
+            now = datetime.now(timezone.utc)
+            positions = []
+            for row in rows:
+                entry_time_str = row["entry_time"]
+                try:
+                    entry_dt = datetime.fromisoformat(entry_time_str.replace("Z", "+00:00"))
+                    held_seconds = int((now - entry_dt).total_seconds())
+                    held_hours = held_seconds // 3600
+                    held_minutes = (held_seconds % 3600) // 60
+                    if held_hours >= 1:
+                        held_display = f"{held_hours}h {held_minutes}m"
+                    else:
+                        held_display = f"{held_minutes}m"
+                except (ValueError, TypeError):
+                    held_display = "--"
+
+                positions.append(
+                    {
+                        "stock_code": row["stock_code"],
+                        "market": row["market"],
+                        "exchange_code": row["exchange_code"],
+                        "entry_price": row["entry_price"],
+                        "quantity": row["quantity"],
+                        "entry_time": entry_time_str,
+                        "held": held_display,
+                        "decision_id": row["decision_id"],
+                    }
+                )
+
+            return {"count": len(positions), "positions": positions}
+
     return app
 
 
 def _connect(db_path: str) -> sqlite3.Connection:
     conn = sqlite3.connect(db_path)
     conn.row_factory = sqlite3.Row
+    conn.execute("PRAGMA journal_mode=WAL")
+    conn.execute("PRAGMA busy_timeout=8000")
     return conn
 
 

src/dashboard/static/index.html

@@ -1,9 +1,10 @@
 <!doctype html>
-<html lang="en">
+<html lang="ko">
   <head>
     <meta charset="UTF-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <title>The Ouroboros Dashboard</title>
+    <script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script>
     <style>
       :root {
         --bg: #0b1724;
@@ -11,51 +12,760 @@
         --fg: #e6eef7;
         --muted: #9fb3c8;
         --accent: #3cb371;
+        --red: #e05555;
+        --warn: #e8a040;
+        --border: #28455f;
       }
+      * { box-sizing: border-box; margin: 0; padding: 0; }
       body {
-        margin: 0;
         font-family: ui-monospace, SFMono-Regular, Menlo, monospace;
         background: radial-gradient(circle at top left, #173b58, var(--bg));
         color: var(--fg);
+        min-height: 100vh;
+        font-size: 13px;
       }
-      .wrap {
+      .wrap { max-width: 1100px; margin: 0 auto; padding: 20px 16px; }
-        max-width: 900px;
+
-        margin: 48px auto;
+      /* Header */
-        padding: 0 16px;
+      header {
+        display: flex;
+        align-items: center;
+        justify-content: space-between;
+        margin-bottom: 20px;
+        padding-bottom: 12px;
+        border-bottom: 1px solid var(--border);
       }
+      header h1 { font-size: 18px; color: var(--accent); letter-spacing: 0.5px; }
+      .header-right { display: flex; align-items: center; gap: 12px; color: var(--muted); font-size: 12px; }
+      .refresh-btn {
+        background: none; border: 1px solid var(--border); color: var(--muted);
+        padding: 4px 10px; border-radius: 6px; cursor: pointer; font-family: inherit;
+        font-size: 12px; transition: border-color 0.2s;
+      }
+      .refresh-btn:hover { border-color: var(--accent); color: var(--accent); }
+
+      /* CB Gauge */
+      .cb-gauge-wrap {
+        display: flex; align-items: center; gap: 8px;
+        font-size: 11px; color: var(--muted);
+      }
+      .cb-dot {
+        width: 8px; height: 8px; border-radius: 50%; flex-shrink: 0;
+      }
+      .cb-dot.ok      { background: var(--accent); }
+      .cb-dot.warning { background: var(--warn); animation: pulse-warn 1.2s ease-in-out infinite; }
+      .cb-dot.tripped { background: var(--red);  animation: pulse-warn 0.6s ease-in-out infinite; }
+      .cb-dot.unknown { background: var(--border); }
+      @keyframes pulse-warn {
+        0%, 100% { opacity: 1; }
+        50%       { opacity: 0.35; }
+      }
+      .cb-bar-wrap { width: 64px; height: 5px; background: rgba(255,255,255,0.08); border-radius: 3px; overflow: hidden; }
+      .cb-bar-fill { height: 100%; border-radius: 3px; transition: width 0.4s, background 0.4s; }
+
+      /* Summary cards */
+      .cards { display: grid; grid-template-columns: repeat(4, 1fr); gap: 12px; margin-bottom: 20px; }
+      @media (max-width: 700px) { .cards { grid-template-columns: repeat(2, 1fr); } }
       .card {
-        background: color-mix(in oklab, var(--panel), black 12%);
+        background: var(--panel);
-        border: 1px solid #28455f;
+        border: 1px solid var(--border);
-        border-radius: 12px;
+        border-radius: 10px;
-        padding: 20px;
+        padding: 16px;
       }
-      h1 {
+      .card-label { color: var(--muted); font-size: 11px; margin-bottom: 6px; text-transform: uppercase; letter-spacing: 0.5px; }
-        margin-top: 0;
+      .card-value { font-size: 22px; font-weight: 700; }
+      .card-sub { color: var(--muted); font-size: 11px; margin-top: 4px; }
+      .positive { color: var(--accent); }
+      .negative { color: var(--red); }
+      .neutral { color: var(--fg); }
+
+      /* Chart panel */
+      .chart-panel {
+        background: var(--panel);
+        border: 1px solid var(--border);
+        border-radius: 10px;
+        padding: 16px;
+        margin-bottom: 20px;
       }
-      code {
+      .panel-header {
-        color: var(--accent);
+        display: flex;
+        align-items: center;
+        justify-content: space-between;
+        margin-bottom: 16px;
       }
-      li {
+      .panel-title { font-size: 13px; color: var(--muted); font-weight: 600; }
-        margin: 6px 0;
+      .chart-container { position: relative; height: 180px; }
-        color: var(--muted);
+      .chart-error { color: var(--muted); text-align: center; padding: 40px 0; font-size: 12px; }
+
+      /* Days selector */
+      .days-selector { display: flex; gap: 4px; }
+      .day-btn {
+        background: none; border: 1px solid var(--border); color: var(--muted);
+        padding: 3px 8px; border-radius: 4px; cursor: pointer; font-family: inherit; font-size: 11px;
       }
+      .day-btn.active { border-color: var(--accent); color: var(--accent); background: rgba(60, 179, 113, 0.08); }
+
+      /* Decisions panel */
+      .decisions-panel {
+        background: var(--panel);
+        border: 1px solid var(--border);
+        border-radius: 10px;
+        padding: 16px;
+      }
+      .market-tabs { display: flex; gap: 6px; flex-wrap: wrap; }
+      .tab-btn {
+        background: none; border: 1px solid var(--border); color: var(--muted);
+        padding: 4px 10px; border-radius: 6px; cursor: pointer; font-family: inherit; font-size: 11px;
+      }
+      .tab-btn.active { border-color: var(--accent); color: var(--accent); background: rgba(60, 179, 113, 0.08); }
+      .decisions-table { width: 100%; border-collapse: collapse; margin-top: 14px; }
+      .decisions-table th {
+        text-align: left; color: var(--muted); font-size: 11px; font-weight: 600;
+        padding: 6px 8px; border-bottom: 1px solid var(--border); white-space: nowrap;
+      }
+      .decisions-table td {
+        padding: 8px 8px; border-bottom: 1px solid rgba(40, 69, 95, 0.5);
+        vertical-align: middle; white-space: nowrap;
+      }
+      .decisions-table tr:last-child td { border-bottom: none; }
+      .decisions-table tr:hover td { background: rgba(255,255,255,0.02); }
+      .badge {
+        display: inline-block; padding: 2px 7px; border-radius: 4px;
+        font-size: 11px; font-weight: 700; letter-spacing: 0.5px;
+      }
+      .badge-buy { background: rgba(60, 179, 113, 0.15); color: var(--accent); }
+      .badge-sell { background: rgba(224, 85, 85, 0.15); color: var(--red); }
+      .badge-hold { background: rgba(159, 179, 200, 0.12); color: var(--muted); }
+      .conf-bar-wrap { display: flex; align-items: center; gap: 6px; min-width: 90px; }
+      .conf-bar { flex: 1; height: 6px; background: rgba(255,255,255,0.08); border-radius: 3px; overflow: hidden; }
+      .conf-fill { height: 100%; border-radius: 3px; background: var(--accent); transition: width 0.3s; }
+      .conf-val { color: var(--muted); font-size: 11px; min-width: 26px; text-align: right; }
+      .rationale-cell { max-width: 200px; overflow: hidden; text-overflow: ellipsis; color: var(--muted); }
+      .empty-row td { text-align: center; color: var(--muted); padding: 24px; }
+
+      /* Positions panel */
+      .positions-panel {
+        background: var(--panel);
+        border: 1px solid var(--border);
+        border-radius: 10px;
+        padding: 16px;
+        margin-bottom: 20px;
+      }
+      .positions-table { width: 100%; border-collapse: collapse; margin-top: 14px; }
+      .positions-table th {
+        text-align: left; color: var(--muted); font-size: 11px; font-weight: 600;
+        padding: 6px 8px; border-bottom: 1px solid var(--border); white-space: nowrap;
+      }
+      .positions-table td {
+        padding: 8px 8px; border-bottom: 1px solid rgba(40, 69, 95, 0.5);
+        vertical-align: middle; white-space: nowrap;
+      }
+      .positions-table tr:last-child td { border-bottom: none; }
+      .positions-table tr:hover td { background: rgba(255,255,255,0.02); }
+      .pos-empty { color: var(--muted); text-align: center; padding: 20px 0; font-size: 12px; }
+      .pos-count {
+        display: inline-block; background: rgba(60, 179, 113, 0.12);
+        color: var(--accent); font-size: 11px; font-weight: 700;
+        padding: 2px 8px; border-radius: 10px; margin-left: 8px;
+      }
+
+      /* Spinner */
+      .spinner { display: inline-block; width: 12px; height: 12px; border: 2px solid var(--border); border-top-color: var(--accent); border-radius: 50%; animation: spin 0.8s linear infinite; }
+      @keyframes spin { to { transform: rotate(360deg); } }
+
+      /* Generic panel */
+      .panel {
+        background: var(--panel);
+        border: 1px solid var(--border);
+        border-radius: 10px;
+        padding: 16px;
+        margin-top: 20px;
+      }
+
+      /* Playbook panel - details/summary accordion */
+      .playbook-panel details { border: 1px solid var(--border); border-radius: 4px; margin-bottom: 6px; }
+      .playbook-panel summary { padding: 8px 12px; cursor: pointer; font-weight: 600; background: var(--bg); color: var(--fg); }
+      .playbook-panel summary:hover { color: var(--accent); }
+      .playbook-panel pre { margin: 0; padding: 12px; background: var(--bg); overflow-x: auto;
+                            font-size: 11px; color: #a0c4ff; white-space: pre-wrap; }
+
+      /* Scorecard KPI card grid */
+      .scorecard-grid { display: grid; grid-template-columns: repeat(auto-fill, minmax(140px, 1fr)); gap: 10px; }
+      .kpi-card { background: var(--bg); border: 1px solid var(--border); border-radius: 6px; padding: 12px; text-align: center; }
+      .kpi-card .kpi-label { font-size: 11px; color: var(--muted); margin-bottom: 4px; }
+      .kpi-card .kpi-value { font-size: 20px; font-weight: 700; color: var(--fg); }
+
+      /* Scenarios table */
+      .scenarios-table { width: 100%; border-collapse: collapse; font-size: 13px; }
+      .scenarios-table th { background: var(--bg); padding: 8px; text-align: left; border-bottom: 1px solid var(--border);
+                            color: var(--muted); font-size: 11px; font-weight: 600; white-space: nowrap; }
+      .scenarios-table td { padding: 7px 8px; border-bottom: 1px solid rgba(40,69,95,0.5); }
+      .scenarios-table tr:hover td { background: rgba(255,255,255,0.02); }
+
+      /* Context table */
+      .context-table { width: 100%; border-collapse: collapse; font-size: 12px; }
+      .context-table th { background: var(--bg); padding: 8px; text-align: left; border-bottom: 1px solid var(--border);
+                          color: var(--muted); font-size: 11px; font-weight: 600; white-space: nowrap; }
+      .context-table td { padding: 6px 8px; border-bottom: 1px solid rgba(40,69,95,0.5); vertical-align: top; }
+      .context-value { max-height: 60px; overflow-y: auto; color: #a0c4ff; word-break: break-all; }
+
+      /* Common panel select controls */
+      .panel-controls { display: flex; gap: 8px; align-items: center; flex-wrap: wrap; }
+      .panel-controls select, .panel-controls input[type="number"] {
+        background: var(--bg); color: var(--fg); border: 1px solid var(--border);
+        border-radius: 4px; padding: 4px 8px; font-size: 13px; font-family: inherit;
+      }
+      .panel-date { color: var(--muted); font-size: 12px; }
+      .empty-msg { color: var(--muted); text-align: center; padding: 20px 0; font-size: 12px; }
     </style>
   </head>
   <body>
     <div class="wrap">
-      <div class="card">
+      <!-- Header -->
-        <h1>The Ouroboros Dashboard API</h1>
+      <header>
-        <p>Use the following endpoints:</p>
+        <h1>&#x1F40D; The Ouroboros</h1>
-        <ul>
+        <div class="header-right">
-          <li><code>/api/status</code></li>
+          <div class="cb-gauge-wrap" id="cb-gauge" title="Circuit Breaker">
-          <li><code>/api/playbook/{date}?market=KR</code></li>
+            <span class="cb-dot unknown" id="cb-dot"></span>
-          <li><code>/api/scorecard/{date}?market=KR</code></li>
+            <span id="cb-label">CB --</span>
-          <li><code>/api/performance?market=all</code></li>
+            <div class="cb-bar-wrap">
-          <li><code>/api/context/{layer}</code></li>
+              <div class="cb-bar-fill" id="cb-bar" style="width:0%;background:var(--accent)"></div>
-          <li><code>/api/decisions?market=KR</code></li>
+            </div>
-          <li><code>/api/scenarios/active?market=US</code></li>
+          </div>
-        </ul>
+          <span id="last-updated">--</span>
+          <button class="refresh-btn" onclick="refreshAll()">&#x21BA; 새로고침</button>
+        </div>
+      </header>
+
+      <!-- Summary cards -->
+      <div class="cards">
+        <div class="card">
+          <div class="card-label">오늘 거래</div>
+          <div class="card-value neutral" id="card-trades">--</div>
+          <div class="card-sub" id="card-trades-sub">거래 건수</div>
+        </div>
+        <div class="card">
+          <div class="card-label">오늘 P&amp;L</div>
+          <div class="card-value" id="card-pnl">--</div>
+          <div class="card-sub" id="card-pnl-sub">실현 손익</div>
+        </div>
+        <div class="card">
+          <div class="card-label">승률</div>
+          <div class="card-value neutral" id="card-winrate">--</div>
+          <div class="card-sub">전체 누적</div>
+        </div>
+        <div class="card">
+          <div class="card-label">누적 거래</div>
+          <div class="card-value neutral" id="card-total">--</div>
+          <div class="card-sub">전체 기간</div>
+        </div>
+      </div>
+
+      <!-- Open Positions -->
+      <div class="positions-panel">
+        <div class="panel-header">
+          <span class="panel-title">
+            현재 보유 포지션
+            <span class="pos-count" id="positions-count">0</span>
+          </span>
+        </div>
+        <table class="positions-table">
+          <thead>
+            <tr>
+              <th>종목</th>
+              <th>시장</th>
+              <th>수량</th>
+              <th>진입가</th>
+              <th>보유 시간</th>
+            </tr>
+          </thead>
+          <tbody id="positions-body">
+            <tr><td colspan="5" class="pos-empty"><span class="spinner"></span></td></tr>
+          </tbody>
+        </table>
+      </div>
+
+      <!-- P&L Chart -->
+      <div class="chart-panel">
+        <div class="panel-header">
+          <span class="panel-title">P&amp;L 추이</span>
+          <div class="days-selector">
+            <button class="day-btn active" data-days="7" onclick="selectDays(this)">7일</button>
+            <button class="day-btn" data-days="30" onclick="selectDays(this)">30일</button>
+            <button class="day-btn" data-days="90" onclick="selectDays(this)">90일</button>
+          </div>
+        </div>
+        <div class="chart-container">
+          <canvas id="pnl-chart"></canvas>
+          <div class="chart-error" id="chart-error" style="display:none">데이터 없음</div>
+        </div>
+      </div>
+
+      <!-- Decisions log -->
+      <div class="decisions-panel">
+        <div class="panel-header">
+          <span class="panel-title">최근 결정 로그</span>
+          <div class="market-tabs" id="market-tabs">
+            <button class="tab-btn active" data-market="KR" onclick="selectMarket(this)">KR</button>
+            <button class="tab-btn" data-market="US_NASDAQ" onclick="selectMarket(this)">US_NASDAQ</button>
+            <button class="tab-btn" data-market="US_NYSE" onclick="selectMarket(this)">US_NYSE</button>
+            <button class="tab-btn" data-market="JP" onclick="selectMarket(this)">JP</button>
+            <button class="tab-btn" data-market="HK" onclick="selectMarket(this)">HK</button>
+          </div>
+        </div>
+        <table class="decisions-table">
+          <thead>
+            <tr>
+              <th>시각</th>
+              <th>종목</th>
+              <th>액션</th>
+              <th>신뢰도</th>
+              <th>사유</th>
+            </tr>
+          </thead>
+          <tbody id="decisions-body">
+            <tr class="empty-row"><td colspan="5"><span class="spinner"></span></td></tr>
+          </tbody>
+        </table>
+      </div>
+
+      <!-- playbook panel -->
+      <div class="panel playbook-panel">
+        <div class="panel-header">
+          <span class="panel-title">&#x1F4CB; 프리마켓 플레이북</span>
+          <div class="panel-controls">
+            <select id="pb-market-select" onchange="fetchPlaybook()">
+              <option value="KR">KR</option>
+              <option value="US_NASDAQ">US_NASDAQ</option>
+              <option value="US_NYSE">US_NYSE</option>
+            </select>
+            <span id="pb-date" class="panel-date"></span>
+          </div>
+        </div>
+        <div id="playbook-content"><p class="empty-msg">데이터 없음</p></div>
+      </div>
+
+      <!-- scorecard panel -->
+      <div class="panel">
+        <div class="panel-header">
+          <span class="panel-title">&#x1F4CA; 일간 스코어카드</span>
+          <div class="panel-controls">
+            <select id="sc-market-select" onchange="fetchScorecard()">
+              <option value="KR">KR</option>
+              <option value="US_NASDAQ">US_NASDAQ</option>
+            </select>
+            <span id="sc-date" class="panel-date"></span>
+          </div>
+        </div>
+        <div id="scorecard-grid" class="scorecard-grid"><p class="empty-msg">데이터 없음</p></div>
+      </div>
+
+      <!-- scenarios panel -->
+      <div class="panel">
+        <div class="panel-header">
+          <span class="panel-title">&#x1F3AF; 활성 시나리오 매칭</span>
+          <div class="panel-controls">
+            <select id="scen-market-select" onchange="fetchScenarios()">
+              <option value="KR">KR</option>
+              <option value="US_NASDAQ">US_NASDAQ</option>
+            </select>
+          </div>
+        </div>
+        <div id="scenarios-content"><p class="empty-msg">데이터 없음</p></div>
+      </div>
+
+      <!-- context layer panel -->
+      <div class="panel">
+        <div class="panel-header">
+          <span class="panel-title">&#x1F9E0; 컨텍스트 트리</span>
+          <div class="panel-controls">
+            <select id="ctx-layer-select" onchange="fetchContext()">
+              <option value="L7_REALTIME">L7_REALTIME</option>
+              <option value="L6_DAILY">L6_DAILY</option>
+              <option value="L5_WEEKLY">L5_WEEKLY</option>
+              <option value="L4_MONTHLY">L4_MONTHLY</option>
+              <option value="L3_QUARTERLY">L3_QUARTERLY</option>
+              <option value="L2_YEARLY">L2_YEARLY</option>
+              <option value="L1_LIFETIME">L1_LIFETIME</option>
+            </select>
+            <input id="ctx-limit" type="number" value="20" min="1" max="200"
+                   style="width:60px;" onchange="fetchContext()">
+          </div>
+        </div>
+        <div id="context-content"><p class="empty-msg">데이터 없음</p></div>
       </div>
     </div>
+
+    <script>
+      let pnlChart = null;
+      let currentDays = 7;
+      let currentMarket = 'KR';
+
+      function fmt(dt) {
+        try {
+          const d = new Date(dt);
+          return d.toLocaleTimeString('ko-KR', { hour: '2-digit', minute: '2-digit', hour12: false });
+        } catch { return dt || '--'; }
+      }
+
+      function fmtPnl(v) {
+        if (v === null || v === undefined) return '--';
+        const n = parseFloat(v);
+        const cls = n > 0 ? 'positive' : n < 0 ? 'negative' : 'neutral';
+        const sign = n > 0 ? '+' : '';
+        return `<span class="${cls}">${sign}${n.toFixed(2)}</span>`;
+      }
+
+      function badge(action) {
+        const a = (action || '').toUpperCase();
+        const cls = a === 'BUY' ? 'badge-buy' : a === 'SELL' ? 'badge-sell' : 'badge-hold';
+        return `<span class="badge ${cls}">${a}</span>`;
+      }
+
+      function confBar(conf) {
+        const pct = Math.min(Math.max(conf || 0, 0), 100);
+        return `<div class="conf-bar-wrap">
+          <div class="conf-bar"><div class="conf-fill" style="width:${pct}%"></div></div>
+          <span class="conf-val">${pct}</span>
+        </div>`;
+      }
+
+      function fmtPrice(v, market) {
+        if (v === null || v === undefined) return '--';
+        const n = parseFloat(v);
+        const sym = market === 'KR' ? '₩' : market === 'JP' ? '¥' : market === 'HK' ? 'HK$' : '$';
+        return sym + n.toLocaleString('en-US', { minimumFractionDigits: 0, maximumFractionDigits: 4 });
+      }
+
+      async function fetchPositions() {
+        const tbody = document.getElementById('positions-body');
+        const countEl = document.getElementById('positions-count');
+        try {
+          const r = await fetch('/api/positions');
+          if (!r.ok) throw new Error('fetch failed');
+          const d = await r.json();
+          countEl.textContent = d.count ?? 0;
+          if (!d.positions || d.positions.length === 0) {
+            tbody.innerHTML = '<tr><td colspan="5" class="pos-empty">현재 보유 중인 포지션 없음</td></tr>';
+            return;
+          }
+          tbody.innerHTML = d.positions.map(p => `
+            <tr>
+              <td><strong>${p.stock_code || '--'}</strong></td>
+              <td><span style="color:var(--muted);font-size:11px">${p.market || '--'}</span></td>
+              <td>${p.quantity ?? '--'}</td>
+              <td>${fmtPrice(p.entry_price, p.market)}</td>
+              <td style="color:var(--muted);font-size:11px">${p.held || '--'}</td>
+            </tr>
+          `).join('');
+        } catch {
+          tbody.innerHTML = '<tr><td colspan="5" class="pos-empty">데이터 로드 실패</td></tr>';
+        }
+      }
+
+      function renderCbGauge(cb) {
+        if (!cb) return;
+        const dot = document.getElementById('cb-dot');
+        const label = document.getElementById('cb-label');
+        const bar = document.getElementById('cb-bar');
+
+        const status = cb.status || 'unknown';
+        const threshold = cb.threshold_pct ?? -3.0;
+        const current = cb.current_pnl_pct;
+
+        // dot color
+        dot.className = `cb-dot ${status}`;
+
+        // label
+        if (current !== null && current !== undefined) {
+          const sign = current > 0 ? '+' : '';
+          label.textContent = `CB ${sign}${current.toFixed(2)}%`;
+        } else {
+          label.textContent = 'CB --';
+        }
+
+        // bar: fill = how much of the threshold has been consumed (0%=safe, 100%=tripped)
+        const colorMap = { ok: 'var(--accent)', warning: 'var(--warn)', tripped: 'var(--red)', unknown: 'var(--border)' };
+        bar.style.background = colorMap[status] || 'var(--border)';
+        if (current !== null && current !== undefined && threshold < 0) {
+          const fillPct = Math.min(Math.max((current / threshold) * 100, 0), 100);
+          bar.style.width = `${fillPct}%`;
+        } else {
+          bar.style.width = '0%';
+        }
+      }
+
+      async function fetchStatus() {
+        try {
+          const r = await fetch('/api/status');
+          if (!r.ok) return;
+          const d = await r.json();
+          const t = d.totals || {};
+          document.getElementById('card-trades').textContent = t.trade_count ?? '--';
+          const pnlEl = document.getElementById('card-pnl');
+          const pnlV = t.total_pnl;
+          if (pnlV !== undefined) {
+            const n = parseFloat(pnlV);
+            const sign = n > 0 ? '+' : '';
+            pnlEl.textContent = `${sign}${n.toFixed(2)}`;
+            pnlEl.className = `card-value ${n > 0 ? 'positive' : n < 0 ? 'negative' : 'neutral'}`;
+          }
+          document.getElementById('card-pnl-sub').textContent = `결정 ${t.decision_count ?? 0}건`;
+          renderCbGauge(d.circuit_breaker);
+        } catch {}
+      }
+
+      async function fetchPerformance() {
+        try {
+          const r = await fetch('/api/performance?market=all');
+          if (!r.ok) return;
+          const d = await r.json();
+          const c = d.combined || {};
+          document.getElementById('card-winrate').textContent = c.win_rate !== undefined ? `${c.win_rate}%` : '--';
+          document.getElementById('card-total').textContent = c.total_trades ?? '--';
+        } catch {}
+      }
+
+      async function fetchPnlHistory(days) {
+        try {
+          const r = await fetch(`/api/pnl/history?days=${days}`);
+          if (!r.ok) throw new Error('fetch failed');
+          const d = await r.json();
+          renderChart(d);
+        } catch {
+          document.getElementById('chart-error').style.display = 'block';
+        }
+      }
+
+      function renderChart(data) {
+        const errEl = document.getElementById('chart-error');
+        if (!data.labels || data.labels.length === 0) {
+          errEl.style.display = 'block';
+          return;
+        }
+        errEl.style.display = 'none';
+
+        const colors = data.pnl.map(v => v >= 0 ? 'rgba(60,179,113,0.75)' : 'rgba(224,85,85,0.75)');
+        const borderColors = data.pnl.map(v => v >= 0 ? '#3cb371' : '#e05555');
+
+        if (pnlChart) { pnlChart.destroy(); pnlChart = null; }
+        const ctx = document.getElementById('pnl-chart').getContext('2d');
+        pnlChart = new Chart(ctx, {
+          type: 'bar',
+          data: {
+            labels: data.labels,
+            datasets: [{
+              label: 'Daily P&L',
+              data: data.pnl,
+              backgroundColor: colors,
+              borderColor: borderColors,
+              borderWidth: 1,
+              borderRadius: 3,
+            }]
+          },
+          options: {
+            responsive: true,
+            maintainAspectRatio: false,
+            plugins: {
+              legend: { display: false },
+              tooltip: {
+                callbacks: {
+                  label: ctx => {
+                    const v = ctx.parsed.y;
+                    const sign = v >= 0 ? '+' : '';
+                    const trades = data.trades[ctx.dataIndex];
+                    return [`P&L: ${sign}${v.toFixed(2)}`, `거래: ${trades}건`];
+                  }
+                }
+              }
+            },
+            scales: {
+              x: {
+                ticks: { color: '#9fb3c8', font: { size: 10 }, maxRotation: 0 },
+                grid: { color: 'rgba(40,69,95,0.4)' }
+              },
+              y: {
+                ticks: { color: '#9fb3c8', font: { size: 10 } },
+                grid: { color: 'rgba(40,69,95,0.4)' }
+              }
+            }
+          }
+        });
+      }
+
+      async function fetchDecisions(market) {
+        const tbody = document.getElementById('decisions-body');
+        tbody.innerHTML = '<tr class="empty-row"><td colspan="5"><span class="spinner"></span></td></tr>';
+        try {
+          const r = await fetch(`/api/decisions?market=${market}&limit=50`);
+          if (!r.ok) throw new Error('fetch failed');
+          const d = await r.json();
+          if (!d.decisions || d.decisions.length === 0) {
+            tbody.innerHTML = '<tr class="empty-row"><td colspan="5">결정 로그 없음</td></tr>';
+            return;
+          }
+          tbody.innerHTML = d.decisions.map(dec => `
+            <tr>
+              <td>${fmt(dec.timestamp)}</td>
+              <td>${dec.stock_code || '--'}</td>
+              <td>${badge(dec.action)}</td>
+              <td>${confBar(dec.confidence)}</td>
+              <td class="rationale-cell" title="${(dec.rationale || '').replace(/"/g, '&quot;')}">${dec.rationale || '--'}</td>
+            </tr>
+          `).join('');
+        } catch {
+          tbody.innerHTML = '<tr class="empty-row"><td colspan="5">데이터 로드 실패</td></tr>';
+        }
+      }
+
+      function selectDays(btn) {
+        document.querySelectorAll('.day-btn').forEach(b => b.classList.remove('active'));
+        btn.classList.add('active');
+        currentDays = parseInt(btn.dataset.days, 10);
+        fetchPnlHistory(currentDays);
+      }
+
+      function selectMarket(btn) {
+        document.querySelectorAll('.tab-btn').forEach(b => b.classList.remove('active'));
+        btn.classList.add('active');
+        currentMarket = btn.dataset.market;
+        fetchDecisions(currentMarket);
+      }
+
+      function todayStr() {
+        return new Date().toISOString().slice(0, 10);
+      }
+
+      function esc(s) {
+        return String(s ?? '').replace(/&/g, '&amp;').replace(/</g, '&lt;').replace(/>/g, '&gt;').replace(/"/g, '&quot;');
+      }
+
+      async function fetchJSON(url) {
+        const r = await fetch(url);
+        if (!r.ok) throw new Error(`HTTP ${r.status}`);
+        return r.json();
+      }
+
+      async function fetchPlaybook() {
+        const market = document.getElementById('pb-market-select').value;
+        const date = todayStr();
+        document.getElementById('pb-date').textContent = date;
+        const el = document.getElementById('playbook-content');
+        try {
+          const data = await fetchJSON(`/api/playbook/${date}?market=${market}`);
+          const stocks = data.stock_playbooks ?? [];
+          if (stocks.length === 0) {
+            el.innerHTML = '<p class="empty-msg">오늘 플레이북 없음</p>';
+            return;
+          }
+          el.innerHTML = stocks.map(sp =>
+            `<details><summary>${esc(sp.stock_code ?? '?')} — ${esc(sp.signal ?? '')}</summary>` +
+            `<pre>${esc(JSON.stringify(sp, null, 2))}</pre></details>`
+          ).join('');
+        } catch {
+          el.innerHTML = '<p class="empty-msg">플레이북 없음 (오늘 미생성 또는 API 오류)</p>';
+        }
+      }
+
+      async function fetchScorecard() {
+        const market = document.getElementById('sc-market-select').value;
+        const date = todayStr();
+        document.getElementById('sc-date').textContent = date;
+        const el = document.getElementById('scorecard-grid');
+        try {
+          const data = await fetchJSON(`/api/scorecard/${date}?market=${market}`);
+          const sc = data.scorecard ?? {};
+          const entries = Object.entries(sc);
+          if (entries.length === 0) {
+            el.innerHTML = '<p class="empty-msg">스코어카드 없음</p>';
+            return;
+          }
+          el.className = 'scorecard-grid';
+          el.innerHTML = entries.map(([k, v]) => `
+            <div class="kpi-card">
+              <div class="kpi-label">${esc(k)}</div>
+              <div class="kpi-value">${typeof v === 'number' ? v.toFixed(2) : esc(String(v))}</div>
+            </div>`).join('');
+        } catch {
+          el.innerHTML = '<p class="empty-msg">스코어카드 없음 (오늘 미생성 또는 API 오류)</p>';
+        }
+      }
+
+      async function fetchScenarios() {
+        const market = document.getElementById('scen-market-select').value;
+        const date = todayStr();
+        const el = document.getElementById('scenarios-content');
+        try {
+          const data = await fetchJSON(`/api/scenarios/active?market=${market}&date_str=${date}&limit=50`);
+          const matches = data.matches ?? [];
+          if (matches.length === 0) {
+            el.innerHTML = '<p class="empty-msg">활성 시나리오 없음</p>';
+            return;
+          }
+          el.innerHTML = `<table class="scenarios-table">
+            <thead><tr><th>종목</th><th>신호</th><th>신뢰도</th><th>매칭 조건</th></tr></thead>
+            <tbody>${matches.map(m => `
+              <tr>
+                <td>${esc(m.stock_code)}</td>
+                <td>${esc(m.signal ?? '-')}</td>
+                <td>${esc(m.confidence ?? '-')}</td>
+                <td><code style="font-size:11px">${esc(JSON.stringify(m.scenario_match ?? {}))}</code></td>
+              </tr>`).join('')}
+            </tbody></table>`;
+        } catch {
+          el.innerHTML = '<p class="empty-msg">데이터 없음</p>';
+        }
+      }
+
+      async function fetchContext() {
+        const layer = document.getElementById('ctx-layer-select').value;
+        const limit = Math.min(Math.max(parseInt(document.getElementById('ctx-limit').value, 10) || 20, 1), 200);
+        const el = document.getElementById('context-content');
+        try {
+          const data = await fetchJSON(`/api/context/${layer}?limit=${limit}`);
+          const entries = data.entries ?? [];
+          if (entries.length === 0) {
+            el.innerHTML = '<p class="empty-msg">컨텍스트 없음</p>';
+            return;
+          }
+          el.innerHTML = `<table class="context-table">
+            <thead><tr><th>timeframe</th><th>key</th><th>value</th><th>updated</th></tr></thead>
+            <tbody>${entries.map(e => `
+              <tr>
+                <td>${esc(e.timeframe)}</td>
+                <td>${esc(e.key)}</td>
+                <td><div class="context-value">${esc(JSON.stringify(e.value ?? e.raw_value))}</div></td>
+                <td style="font-size:11px;color:var(--muted)">${esc((e.updated_at ?? '').slice(0, 16))}</td>
+              </tr>`).join('')}
+            </tbody></table>`;
+        } catch {
+          el.innerHTML = '<p class="empty-msg">데이터 없음</p>';
+        }
+      }
+
+      async function refreshAll() {
+        document.getElementById('last-updated').textContent = '업데이트 중...';
+        await Promise.all([
+          fetchStatus(),
+          fetchPerformance(),
+          fetchPositions(),
+          fetchPnlHistory(currentDays),
+          fetchDecisions(currentMarket),
+          fetchPlaybook(),
+          fetchScorecard(),
+          fetchScenarios(),
+          fetchContext(),
+        ]);
+        const now = new Date();
+        const timeStr = now.toLocaleTimeString('ko-KR', { hour: '2-digit', minute: '2-digit', second: '2-digit', hour12: false });
+        document.getElementById('last-updated').textContent = `마지막 업데이트: ${timeStr}`;
+      }
+
+      // Initial load
+      refreshAll();
+
+      // Auto-refresh every 30 seconds
+      setInterval(refreshAll, 30000);
+    </script>
   </body>
 </html>

src/db.py

@@ -14,6 +14,11 @@ def init_db(db_path: str) -> sqlite3.Connection:
     if db_path != ":memory:":
         Path(db_path).parent.mkdir(parents=True, exist_ok=True)
     conn = sqlite3.connect(db_path)
+    # Enable WAL mode for concurrent read/write (dashboard + trading loop).
+    # WAL does not apply to in-memory databases.
+    if db_path != ":memory:":
+        conn.execute("PRAGMA journal_mode=WAL")
+        conn.execute("PRAGMA busy_timeout=5000")
     conn.execute(
         """
         CREATE TABLE IF NOT EXISTS trades (
@@ -28,12 +33,13 @@ def init_db(db_path: str) -> sqlite3.Connection:
             pnl REAL DEFAULT 0.0,
             market TEXT DEFAULT 'KR',
             exchange_code TEXT DEFAULT 'KRX',
-            decision_id TEXT
+            decision_id TEXT,
+            mode TEXT DEFAULT 'paper'
         )
         """
     )
 
-    # Migration: Add market and exchange_code columns if they don't exist
+    # Migration: Add columns if they don't exist (backward-compatible schema upgrades)
     cursor = conn.execute("PRAGMA table_info(trades)")
     columns = {row[1] for row in cursor.fetchall()}
 
@@ -45,6 +51,8 @@ def init_db(db_path: str) -> sqlite3.Connection:
         conn.execute("ALTER TABLE trades ADD COLUMN selection_context TEXT")
     if "decision_id" not in columns:
         conn.execute("ALTER TABLE trades ADD COLUMN decision_id TEXT")
+    if "mode" not in columns:
+        conn.execute("ALTER TABLE trades ADD COLUMN mode TEXT DEFAULT 'paper'")
 
     # Context tree tables for multi-layered memory management
     conn.execute(
@@ -131,6 +139,25 @@ def init_db(db_path: str) -> sqlite3.Connection:
     conn.execute(
         "CREATE INDEX IF NOT EXISTS idx_decision_logs_confidence ON decision_logs(confidence)"
     )
+
+    # Index for open-position queries (partition by stock_code, market, ordered by timestamp)
+    conn.execute(
+        "CREATE INDEX IF NOT EXISTS idx_trades_stock_market_ts"
+        " ON trades (stock_code, market, timestamp DESC)"
+    )
+
+    # Lightweight key-value store for trading system runtime metrics (dashboard use only)
+    # Intentionally separate from the AI context tree to preserve separation of concerns.
+    conn.execute(
+        """
+        CREATE TABLE IF NOT EXISTS system_metrics (
+            key        TEXT PRIMARY KEY,
+            value      TEXT NOT NULL,
+            updated_at TEXT NOT NULL
+        )
+        """
+    )
+
     conn.commit()
     return conn
 
@@ -148,6 +175,7 @@ def log_trade(
     exchange_code: str = "KRX",
     selection_context: dict[str, any] | None = None,
     decision_id: str | None = None,
+    mode: str = "paper",
 ) -> None:
     """Insert a trade record into the database.
 
@@ -163,6 +191,8 @@ def log_trade(
         market: Market code
         exchange_code: Exchange code
         selection_context: Scanner selection data (RSI, volume_ratio, signal, score)
+        decision_id: Unique decision identifier for audit linking
+        mode: Trading mode ('paper' or 'live') for data separation
     """
     # Serialize selection context to JSON
     context_json = json.dumps(selection_context) if selection_context else None
@@ -171,9 +201,10 @@ def log_trade(
         """
         INSERT INTO trades (
             timestamp, stock_code, action, confidence, rationale,
-            quantity, price, pnl, market, exchange_code, selection_context, decision_id
+            quantity, price, pnl, market, exchange_code, selection_context, decision_id,
+            mode
         )
-        VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+        VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
         """,
         (
             datetime.now(UTC).isoformat(),
@@ -188,6 +219,7 @@ def log_trade(
             exchange_code,
             context_json,
             decision_id,
+            mode,
         ),
     )
     conn.commit()

src/notifications/telegram_client.py

@@ -4,8 +4,9 @@ import asyncio
 import logging
 import time
 from collections.abc import Awaitable, Callable
-from dataclasses import dataclass
+from dataclasses import dataclass, fields
 from enum import Enum
+from typing import ClassVar
 
 import aiohttp
 
@@ -58,6 +59,45 @@ class LeakyBucket:
                 self._tokens -= 1.0
 
 
+@dataclass
+class NotificationFilter:
+    """Granular on/off flags for each notification type.
+
+    circuit_breaker is intentionally omitted — it is always sent regardless.
+    """
+
+    # Maps user-facing command keys to dataclass field names
+    KEYS: ClassVar[dict[str, str]] = {
+        "trades": "trades",
+        "market": "market_open_close",
+        "fatfinger": "fat_finger",
+        "system": "system_events",
+        "playbook": "playbook",
+        "scenario": "scenario_match",
+        "errors": "errors",
+    }
+
+    trades: bool = True
+    market_open_close: bool = True
+    fat_finger: bool = True
+    system_events: bool = True
+    playbook: bool = True
+    scenario_match: bool = True
+    errors: bool = True
+
+    def set_flag(self, key: str, value: bool) -> bool:
+        """Set a filter flag by user-facing key. Returns False if key is unknown."""
+        field = self.KEYS.get(key.lower())
+        if field is None:
+            return False
+        setattr(self, field, value)
+        return True
+
+    def as_dict(self) -> dict[str, bool]:
+        """Return {user_key: current_value} for display."""
+        return {k: getattr(self, field) for k, field in self.KEYS.items()}
+
+
 @dataclass
 class NotificationMessage:
     """Internal notification message structure."""
@@ -79,6 +119,7 @@ class TelegramClient:
         chat_id: str | None = None,
         enabled: bool = True,
         rate_limit: float = DEFAULT_RATE,
+        notification_filter: NotificationFilter | None = None,
     ) -> None:
         """
         Initialize Telegram client.
@@ -88,12 +129,14 @@ class TelegramClient:
             chat_id: Target chat ID (user or group)
             enabled: Enable/disable notifications globally
             rate_limit: Maximum messages per second
+            notification_filter: Granular per-type on/off flags
         """
         self._bot_token = bot_token
         self._chat_id = chat_id
         self._enabled = enabled
         self._rate_limiter = LeakyBucket(rate=rate_limit)
         self._session: aiohttp.ClientSession | None = None
+        self._filter = notification_filter if notification_filter is not None else NotificationFilter()
 
         if not enabled:
             logger.info("Telegram notifications disabled via configuration")
@@ -118,6 +161,26 @@ class TelegramClient:
         if self._session is not None and not self._session.closed:
             await self._session.close()
 
+    def set_notification(self, key: str, value: bool) -> bool:
+        """Toggle a notification type by user-facing key at runtime.
+
+        Args:
+            key: User-facing key (e.g. "scenario", "market", "all")
+            value: True to enable, False to disable
+
+        Returns:
+            True if key was valid, False if unknown.
+        """
+        if key == "all":
+            for k in NotificationFilter.KEYS:
+                self._filter.set_flag(k, value)
+            return True
+        return self._filter.set_flag(key, value)
+
+    def filter_status(self) -> dict[str, bool]:
+        """Return current per-type filter state keyed by user-facing names."""
+        return self._filter.as_dict()
+
     async def send_message(self, text: str, parse_mode: str = "HTML") -> bool:
         """
         Send a generic text message to Telegram.
@@ -193,6 +256,8 @@ class TelegramClient:
             price: Execution price
             confidence: AI confidence level (0-100)
         """
+        if not self._filter.trades:
+            return
         emoji = "🟢" if action == "BUY" else "🔴"
         message = (
             f"<b>{emoji} {action}</b>\n"
@@ -212,6 +277,8 @@ class TelegramClient:
         Args:
             market_name: Name of the market (e.g., "Korea", "United States")
         """
+        if not self._filter.market_open_close:
+            return
         message = f"<b>Market Open</b>\n{market_name} trading session started"
         await self._send_notification(
             NotificationMessage(priority=NotificationPriority.LOW, message=message)
@@ -225,6 +292,8 @@ class TelegramClient:
             market_name: Name of the market
             pnl_pct: Final P&L percentage for the session
         """
+        if not self._filter.market_open_close:
+            return
         pnl_sign = "+" if pnl_pct >= 0 else ""
         pnl_emoji = "📈" if pnl_pct >= 0 else "📉"
         message = (
@@ -271,6 +340,8 @@ class TelegramClient:
             total_cash: Total available cash
             max_pct: Maximum allowed percentage
         """
+        if not self._filter.fat_finger:
+            return
         attempted_pct = (order_amount / total_cash) * 100 if total_cash > 0 else 0
         message = (
             f"<b>Fat-Finger Protection</b>\n"
@@ -293,6 +364,8 @@ class TelegramClient:
             mode: Trading mode ("paper" or "live")
             enabled_markets: List of enabled market codes
         """
+        if not self._filter.system_events:
+            return
         mode_emoji = "📝" if mode == "paper" else "💰"
         markets_str = ", ".join(enabled_markets)
         message = (
@@ -320,6 +393,8 @@ class TelegramClient:
             scenario_count: Total number of scenarios
             token_count: Gemini token usage for the playbook
         """
+        if not self._filter.playbook:
+            return
         message = (
             f"<b>Playbook Generated</b>\n"
             f"Market: {market}\n"
@@ -347,6 +422,8 @@ class TelegramClient:
             condition_summary: Short summary of the matched condition
             confidence: Scenario confidence (0-100)
         """
+        if not self._filter.scenario_match:
+            return
         message = (
             f"<b>Scenario Matched</b>\n"
             f"Symbol: <code>{stock_code}</code>\n"
@@ -366,6 +443,8 @@ class TelegramClient:
             market: Market code (e.g., "KR", "US")
             reason: Failure reason summary
         """
+        if not self._filter.playbook:
+            return
         message = (
             f"<b>Playbook Failed</b>\n"
             f"Market: {market}\n"
@@ -382,6 +461,8 @@ class TelegramClient:
         Args:
             reason: Reason for shutdown (e.g., "Normal shutdown", "Circuit breaker")
         """
+        if not self._filter.system_events:
+            return
         message = f"<b>System Shutdown</b>\n{reason}"
         priority = (
             NotificationPriority.CRITICAL
@@ -403,6 +484,8 @@ class TelegramClient:
             error_msg: Error message
             context: Error context (e.g., stock code, market)
         """
+        if not self._filter.errors:
+            return
         message = (
             f"<b>Error: {error_type}</b>\n"
             f"Context: {context}\n"
@@ -429,6 +512,7 @@ class TelegramCommandHandler:
         self._client = client
         self._polling_interval = polling_interval
         self._commands: dict[str, Callable[[], Awaitable[None]]] = {}
+        self._commands_with_args: dict[str, Callable[[list[str]], Awaitable[None]]] = {}
         self._last_update_id = 0
         self._polling_task: asyncio.Task[None] | None = None
         self._running = False
@@ -437,7 +521,7 @@ class TelegramCommandHandler:
         self, command: str, handler: Callable[[], Awaitable[None]]
     ) -> None:
         """
-        Register a command handler.
+        Register a command handler (no arguments).
 
         Args:
             command: Command name (without leading slash, e.g., "start")
@@ -446,6 +530,19 @@ class TelegramCommandHandler:
         self._commands[command] = handler
         logger.debug("Registered command handler: /%s", command)
 
+    def register_command_with_args(
+        self, command: str, handler: Callable[[list[str]], Awaitable[None]]
+    ) -> None:
+        """
+        Register a command handler that receives trailing arguments.
+
+        Args:
+            command: Command name (without leading slash, e.g., "notify")
+            handler: Async function receiving list of argument tokens
+        """
+        self._commands_with_args[command] = handler
+        logger.debug("Registered command handler (with args): /%s", command)
+
     async def start_polling(self) -> None:
         """Start long polling for commands."""
         if self._running:
@@ -507,9 +604,19 @@ class TelegramCommandHandler:
             async with session.post(url, json=payload) as resp:
                 if resp.status != 200:
                     error_text = await resp.text()
-                    logger.error(
+                    if resp.status == 409:
-                        "getUpdates API error (status=%d): %s", resp.status, error_text
+                        # Another bot instance is already polling — stop this poller entirely.
-                    )
+                        # Retrying would keep conflicting with the other instance.
+                        self._running = False
+                        logger.warning(
+                            "Telegram conflict (409): another instance is already polling. "
+                            "Disabling Telegram commands for this process. "
+                            "Ensure only one instance of The Ouroboros is running at a time.",
+                        )
+                    else:
+                        logger.error(
+                            "getUpdates API error (status=%d): %s", resp.status, error_text
+                        )
                     return []
 
                 data = await resp.json()
@@ -566,11 +673,14 @@ class TelegramCommandHandler:
             # Remove @botname suffix if present (for group chats)
             command_name = command_parts[0].split("@")[0]
 
-            # Execute handler
+            # Execute handler (args-aware handlers take priority)
-            handler = self._commands.get(command_name)
+            args_handler = self._commands_with_args.get(command_name)
-            if handler:
+            if args_handler:
+                logger.info("Executing command: /%s %s", command_name, command_parts[1:])
+                await args_handler(command_parts[1:])
+            elif command_name in self._commands:
                 logger.info("Executing command: /%s", command_name)
-                await handler()
+                await self._commands[command_name]()
             else:
                 logger.debug("Unknown command: /%s", command_name)
                 await self._client.send_message(

src/strategies/v20260220_210124_evolved.py

@@ -0,0 +1,114 @@
+"""Auto-generated strategy: v20260220_210124
+
+Generated at: 2026-02-20T21:01:24.706847+00:00
+Rationale: Auto-evolved from 6 failures. Primary failure markets: ['US_AMEX', 'US_NYSE', 'US_NASDAQ']. Average loss: -194.69
+"""
+
+from __future__ import annotations
+from typing import Any
+from src.strategies.base import BaseStrategy
+
+
+class Strategy_v20260220_210124(BaseStrategy):
+    """Strategy: v20260220_210124"""
+
+    def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
+        import datetime
+
+        # --- Strategy Constants ---
+        # Minimum price for a stock to be considered for trading (avoids penny stocks)
+        MIN_PRICE = 5.0
+
+        # Momentum signal thresholds (stricter than previous failures)
+        MOMENTUM_PRICE_CHANGE_THRESHOLD = 7.0  # % price change
+        MOMENTUM_VOLUME_RATIO_THRESHOLD = 4.0  # X times average volume
+
+        # Oversold signal thresholds (more conservative)
+        OVERSOLD_RSI_THRESHOLD = 25.0  # RSI value (lower means more oversold)
+
+        # Confidence levels
+        CONFIDENCE_HOLD = 30
+        CONFIDENCE_BUY_OVERSOLD = 65
+        CONFIDENCE_BUY_MOMENTUM = 85
+        CONFIDENCE_BUY_STRONG_MOMENTUM = 90  # For higher-priced stocks with strong momentum
+
+        # Market hours in UTC (9:30 AM ET to 4:00 PM ET)
+        MARKET_OPEN_UTC = datetime.time(14, 30)
+        MARKET_CLOSE_UTC = datetime.time(21, 0)
+
+        # Volatile periods within market hours (UTC) to avoid
+        # First hour after open (14:30 UTC - 15:30 UTC)
+        VOLATILE_OPEN_END_UTC = datetime.time(15, 30)
+        # Last 30 minutes before close (20:30 UTC - 21:00 UTC)
+        VOLATILE_CLOSE_START_UTC = datetime.time(20, 30)
+
+        current_price = market_data.get('current_price')
+        price_change_pct = market_data.get('price_change_pct')
+        volume_ratio = market_data.get('volume_ratio')  # Assumed pre-computed indicator
+        rsi = market_data.get('rsi')                    # Assumed pre-computed indicator
+        timestamp_str = market_data.get('timestamp')
+
+        action = "HOLD"
+        confidence = CONFIDENCE_HOLD
+        rationale = "Initial HOLD: No clear signal or conditions not met."
+
+        # --- 1. Basic Data Validation ---
+        if current_price is None or price_change_pct is None:
+            return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
+                    "rationale": "Insufficient core data (price or price change) to evaluate."}
+
+        # --- 2. Price Filter: Avoid low-priced/penny stocks ---
+        if current_price < MIN_PRICE:
+            return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
+                    "rationale": f"Avoiding low-priced stock (${current_price:.2f} < ${MIN_PRICE:.2f})."}
+
+        # --- 3. Time Filter: Only trade during core market hours ---
+        if timestamp_str:
+            try:
+                dt_object = datetime.datetime.fromisoformat(timestamp_str)
+                current_time_utc = dt_object.time()
+
+                if not (MARKET_OPEN_UTC <= current_time_utc < MARKET_CLOSE_UTC):
+                    return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
+                            "rationale": f"Avoiding trade outside core market hours ({current_time_utc} UTC)."}
+
+                if (MARKET_OPEN_UTC <= current_time_utc < VOLATILE_OPEN_END_UTC) or \
+                   (VOLATILE_CLOSE_START_UTC <= current_time_utc < MARKET_CLOSE_UTC):
+                    return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
+                            "rationale": f"Avoiding trade during volatile market open/close periods ({current_time_utc} UTC)."}
+
+            except ValueError:
+                rationale += " (Warning: Malformed timestamp, time filters skipped)"
+
+        # --- Initialize signal states ---
+        has_momentum_buy_signal = False
+        has_oversold_buy_signal = False
+
+        # --- 4. Evaluate Enhanced Buy Signals ---
+
+        # Momentum Buy Signal
+        if volume_ratio is not None and \
+           price_change_pct > MOMENTUM_PRICE_CHANGE_THRESHOLD and \
+           volume_ratio > MOMENTUM_VOLUME_RATIO_THRESHOLD:
+            has_momentum_buy_signal = True
+            rationale = f"Momentum BUY: Price change {price_change_pct:.2f}%, Volume {volume_ratio:.2f}x."
+            confidence = CONFIDENCE_BUY_MOMENTUM
+            if current_price >= 10.0:
+                confidence = CONFIDENCE_BUY_STRONG_MOMENTUM
+
+        # Oversold Buy Signal
+        if rsi is not None and rsi < OVERSOLD_RSI_THRESHOLD:
+            has_oversold_buy_signal = True
+            if not has_momentum_buy_signal:
+                rationale = f"Oversold BUY: RSI {rsi:.2f}."
+                confidence = CONFIDENCE_BUY_OVERSOLD
+                if current_price >= 10.0:
+                    confidence = min(CONFIDENCE_BUY_OVERSOLD + 5, 80)
+
+        # --- 5. Decision Logic ---
+        if has_momentum_buy_signal:
+            action = "BUY"
+        elif has_oversold_buy_signal:
+            action = "BUY"
+
+        return {"action": action, "confidence": confidence, "rationale": rationale}

src/strategies/v20260220_210159_evolved.py

@@ -0,0 +1,97 @@
+"""Auto-generated strategy: v20260220_210159
+
+Generated at: 2026-02-20T21:01:59.391523+00:00
+Rationale: Auto-evolved from 6 failures. Primary failure markets: ['US_AMEX', 'US_NYSE', 'US_NASDAQ']. Average loss: -194.69
+"""
+
+from __future__ import annotations
+from typing import Any
+from src.strategies.base import BaseStrategy
+
+
+class Strategy_v20260220_210159(BaseStrategy):
+    """Strategy: v20260220_210159"""
+
+    def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
+        import datetime
+
+        current_price = market_data.get('current_price')
+        price_change_pct = market_data.get('price_change_pct')
+        volume_ratio = market_data.get('volume_ratio')
+        rsi = market_data.get('rsi')
+        timestamp_str = market_data.get('timestamp')
+        market_name = market_data.get('market')
+
+        # Default action
+        action = "HOLD"
+        confidence = 0
+        rationale = "No strong signal or conditions not met."
+
+        # --- FAILURE PATTERN AVOIDANCE ---
+
+        # 1. Avoid low-priced/penny stocks
+        MIN_PRICE_THRESHOLD = 5.0  # USD
+        if current_price is not None and current_price < MIN_PRICE_THRESHOLD:
+            rationale = (
+                f"HOLD: Stock price (${current_price:.2f}) is below minimum threshold "
+                f"(${MIN_PRICE_THRESHOLD:.2f}). Past failures consistently involved low-priced stocks."
+            )
+            return {"action": action, "confidence": confidence, "rationale": rationale}
+
+        # 2. Avoid early market hour volatility
+        if timestamp_str:
+            try:
+                dt_obj = datetime.datetime.fromisoformat(timestamp_str)
+                utc_hour = dt_obj.hour
+                utc_minute = dt_obj.minute
+
+                if (utc_hour == 14 and utc_minute < 45) or (utc_hour == 13 and utc_minute >= 30):
+                    rationale = (
+                        f"HOLD: Trading during early market hours (UTC {utc_hour}:{utc_minute}), "
+                        f"a period identified with past failures due to high volatility."
+                    )
+                    return {"action": action, "confidence": confidence, "rationale": rationale}
+            except ValueError:
+                pass
+
+        # --- IMPROVED BUY STRATEGY ---
+
+        # Momentum BUY signal
+        if volume_ratio is not None and price_change_pct is not None:
+            if price_change_pct > 7.0 and volume_ratio > 3.0:
+                action = "BUY"
+                confidence = 70
+                rationale = "Improved BUY: Momentum signal with high volume and above price threshold."
+
+                if market_name == 'US_AMEX':
+                    confidence = max(55, confidence - 5)
+                    rationale += " (Adjusted lower for AMEX market's higher risk profile)."
+                elif market_name == 'US_NASDAQ' and price_change_pct > 20:
+                    confidence = max(50, confidence - 10)
+                    rationale += " (Adjusted lower for aggressive NASDAQ momentum volatility)."
+
+                if price_change_pct > 15.0:
+                    confidence = max(50, confidence - 5)
+                    rationale += " (Caution: Very high daily price change, potential for reversal)."
+
+                return {"action": action, "confidence": confidence, "rationale": rationale}
+
+        # Oversold BUY signal
+        if rsi is not None and price_change_pct is not None:
+            if rsi < 30 and price_change_pct < -3.0:
+                action = "BUY"
+                confidence = 65
+                rationale = "Improved BUY: Oversold signal with recent decline and above price threshold."
+
+                if market_name == 'US_AMEX':
+                    confidence = max(50, confidence - 5)
+                    rationale += " (Adjusted lower for AMEX market's higher risk on oversold assets)."
+
+                if price_change_pct < -10.0:
+                    confidence = max(45, confidence - 10)
+                    rationale += " (Caution: Very steep decline, potential falling knife)."
+
+                return {"action": action, "confidence": confidence, "rationale": rationale}
+
+        # If no specific BUY signal, default to HOLD
+        return {"action": action, "confidence": confidence, "rationale": rationale}

src/strategies/v20260220_210244_evolved.py

@@ -0,0 +1,88 @@
+"""Auto-generated strategy: v20260220_210244
+
+Generated at: 2026-02-20T21:02:44.387355+00:00
+Rationale: Auto-evolved from 6 failures. Primary failure markets: ['US_AMEX', 'US_NYSE', 'US_NASDAQ']. Average loss: -194.69
+"""
+
+from __future__ import annotations
+from typing import Any
+from src.strategies.base import BaseStrategy
+
+
+class Strategy_v20260220_210244(BaseStrategy):
+    """Strategy: v20260220_210244"""
+
+    def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
+        from datetime import datetime
+
+        # Extract required data points safely
+        current_price = market_data.get("current_price")
+        price_change_pct = market_data.get("price_change_pct")
+        volume_ratio = market_data.get("volume_ratio")
+        rsi = market_data.get("rsi")
+        timestamp_str = market_data.get("timestamp")
+        market_name = market_data.get("market")
+        stock_code = market_data.get("stock_code", "UNKNOWN")
+
+        # Default action is HOLD with conservative confidence and rationale
+        action = "HOLD"
+        confidence = 50
+        rationale = f"No strong BUY signal for {stock_code} or awaiting more favorable conditions after avoiding known failure patterns."
+
+        # --- 1. Failure Pattern Avoidance Filters ---
+
+        # A. Avoid low-priced (penny) stocks
+        if current_price is not None and current_price < 5.0:
+            return {
+                "action": "HOLD",
+                "confidence": 50,
+                "rationale": f"AVOID {stock_code}: Stock price (${current_price:.2f}) is below minimum threshold ($5.00) for BUY action. Identified past failures on highly volatile, low-priced stocks."
+            }
+
+        # B. Avoid initiating BUY trades during identified high-volatility hours
+        if timestamp_str:
+            try:
+                trade_hour = datetime.fromisoformat(timestamp_str).hour
+                if trade_hour in [14, 20]:
+                    return {
+                        "action": "HOLD",
+                        "confidence": 50,
+                        "rationale": f"AVOID {stock_code}: Trading during historically volatile hour ({trade_hour} UTC) where previous BUYs resulted in losses. Prefer to observe market stability."
+                    }
+            except ValueError:
+                pass
+
+        # C. Be cautious with extreme momentum spikes
+        if volume_ratio is not None and price_change_pct is not None:
+            if volume_ratio >= 9.0 and price_change_pct >= 15.0:
+                return {
+                    "action": "HOLD",
+                    "confidence": 50,
+                    "rationale": f"AVOID {stock_code}: Extreme short-term momentum detected (price change: +{price_change_pct:.2f}%, volume ratio: {volume_ratio:.1f}x). Historical failures indicate buying into such rapid spikes often leads to reversals."
+                }
+
+        # D. Be cautious with "oversold" signals without further confirmation
+        if rsi is not None and rsi < 30:
+            return {
+                "action": "HOLD",
+                "confidence": 50,
+                "rationale": f"AVOID {stock_code}: Oversold signal (RSI={rsi:.1f}) detected. While often a BUY signal, historical failures on similar 'oversold' trades suggest waiting for stronger confirmation."
+            }
+
+        # --- 2. Improved BUY Signal Generation ---
+        if volume_ratio is not None and 2.0 <= volume_ratio < 9.0 and \
+           price_change_pct is not None and 2.0 <= price_change_pct < 15.0:
+
+            action = "BUY"
+            confidence = 70
+            rationale = f"BUY {stock_code}: Moderate momentum detected (price change: +{price_change_pct:.2f}%, volume ratio: {volume_ratio:.1f}x). Passed filters for price and extreme momentum, avoiding past failure patterns."
+
+            if market_name in ["US_AMEX", "US_NASDAQ"]:
+                confidence = max(60, confidence - 5)
+                rationale += f" Adjusted confidence for {market_name} market characteristics."
+            elif market_name == "US_NYSE":
+                confidence = max(65, confidence)
+
+            confidence = max(50, min(85, confidence))
+
+        return {"action": action, "confidence": confidence, "rationale": rationale}

src/strategy/models.py

@@ -46,6 +46,18 @@ class StockCondition(BaseModel):
 
     The ScenarioEngine evaluates all non-None fields as AND conditions.
     A condition matches only if ALL specified fields are satisfied.
+
+    Technical indicator fields:
+        rsi_below / rsi_above — RSI threshold
+        volume_ratio_above / volume_ratio_below — volume vs previous day
+        price_above / price_below — absolute price level
+        price_change_pct_above / price_change_pct_below — intraday % change
+
+    Position-aware fields (require market_data enrichment from open position):
+        unrealized_pnl_pct_above — matches if unrealized P&L > threshold (e.g. 3.0 → +3%)
+        unrealized_pnl_pct_below — matches if unrealized P&L < threshold (e.g. -2.0 → -2%)
+        holding_days_above — matches if position held for more than N days
+        holding_days_below — matches if position held for fewer than N days
     """
 
     rsi_below: float | None = None
@@ -56,6 +68,10 @@ class StockCondition(BaseModel):
     price_below: float | None = None
     price_change_pct_above: float | None = None
     price_change_pct_below: float | None = None
+    unrealized_pnl_pct_above: float | None = None
+    unrealized_pnl_pct_below: float | None = None
+    holding_days_above: int | None = None
+    holding_days_below: int | None = None
 
     def has_any_condition(self) -> bool:
         """Check if at least one condition field is set."""
@@ -70,6 +86,10 @@ class StockCondition(BaseModel):
                 self.price_below,
                 self.price_change_pct_above,
                 self.price_change_pct_below,
+                self.unrealized_pnl_pct_above,
+                self.unrealized_pnl_pct_below,
+                self.holding_days_above,
+                self.holding_days_below,
             )
         )
 

src/strategy/pre_market_planner.py

@@ -1,7 +1,8 @@
 """Pre-market planner — generates DayPlaybook via Gemini before market open.
 
 One Gemini API call per market per day. Candidates come from SmartVolatilityScanner.
-On failure, returns a defensive playbook (all HOLD, no trades).
+On failure, returns a smart rule-based fallback playbook that uses scanner signals
+(momentum/oversold) to generate BUY conditions, avoiding the all-HOLD problem.
 """
 
 from __future__ import annotations
@@ -74,6 +75,7 @@ class PreMarketPlanner:
         market: str,
         candidates: list[ScanCandidate],
         today: date | None = None,
+        current_holdings: list[dict] | None = None,
     ) -> DayPlaybook:
         """Generate a DayPlaybook for a market using Gemini.
 
@@ -81,6 +83,10 @@ class PreMarketPlanner:
             market: Market code ("KR" or "US")
             candidates: Stock candidates from SmartVolatilityScanner
             today: Override date (defaults to date.today()). Use market-local date.
+            current_holdings: Currently held positions with entry_price and unrealized_pnl_pct.
+                Each dict: {"stock_code": str, "name": str, "qty": int,
+                            "entry_price": float, "unrealized_pnl_pct": float,
+                            "holding_days": int}
 
         Returns:
             DayPlaybook with scenarios. Empty/defensive if no candidates or failure.
@@ -105,6 +111,7 @@ class PreMarketPlanner:
                 context_data,
                 self_market_scorecard,
                 cross_market,
+                current_holdings=current_holdings,
             )
 
             # 3. Call Gemini
@@ -117,7 +124,8 @@ class PreMarketPlanner:
 
             # 4. Parse response
             playbook = self._parse_response(
-                decision.rationale, today, market, candidates, cross_market
+                decision.rationale, today, market, candidates, cross_market,
+                current_holdings=current_holdings,
             )
             playbook_with_tokens = playbook.model_copy(
                 update={"token_count": decision.token_count}
@@ -134,7 +142,7 @@ class PreMarketPlanner:
         except Exception:
             logger.exception("Playbook generation failed for %s", market)
             if self._settings.DEFENSIVE_PLAYBOOK_ON_FAILURE:
-                return self._defensive_playbook(today, market, candidates)
+                return self._smart_fallback_playbook(today, market, candidates, self._settings)
             return self._empty_playbook(today, market)
 
     def build_cross_market_context(
@@ -229,6 +237,7 @@ class PreMarketPlanner:
         context_data: dict[str, Any],
         self_market_scorecard: dict[str, Any] | None,
         cross_market: CrossMarketContext | None,
+        current_holdings: list[dict] | None = None,
     ) -> str:
         """Build a structured prompt for Gemini to generate scenario JSON."""
         max_scenarios = self._settings.MAX_SCENARIOS_PER_STOCK
@@ -240,6 +249,26 @@ class PreMarketPlanner:
             for c in candidates
         )
 
+        holdings_text = ""
+        if current_holdings:
+            lines = []
+            for h in current_holdings:
+                code = h.get("stock_code", "")
+                name = h.get("name", "")
+                qty = h.get("qty", 0)
+                entry_price = h.get("entry_price", 0.0)
+                pnl_pct = h.get("unrealized_pnl_pct", 0.0)
+                holding_days = h.get("holding_days", 0)
+                lines.append(
+                    f"  - {code} ({name}): {qty}주 @ {entry_price:,.0f}, "
+                    f"미실현손익 {pnl_pct:+.2f}%, 보유 {holding_days}일"
+                )
+            holdings_text = (
+                "\n## Current Holdings (보유 중 — SELL/HOLD 전략 고려 필요)\n"
+                + "\n".join(lines)
+                + "\n"
+            )
+
         cross_market_text = ""
         if cross_market:
             cross_market_text = (
@@ -272,10 +301,20 @@ class PreMarketPlanner:
                     for key, value in list(layer_data.items())[:5]:
                         context_text += f"  - {key}: {value}\n"
 
+        holdings_instruction = ""
+        if current_holdings:
+            holding_codes = [h.get("stock_code", "") for h in current_holdings]
+            holdings_instruction = (
+                f"- Also include SELL/HOLD scenarios for held stocks: "
+                f"{', '.join(holding_codes)} "
+                f"(even if not in candidates list)\n"
+            )
+
         return (
             f"You are a pre-market trading strategist for the {market} market.\n"
             f"Generate structured trading scenarios for today.\n\n"
             f"## Candidates (from volatility scanner)\n{candidates_text}\n"
+            f"{holdings_text}"
             f"{self_market_text}"
             f"{cross_market_text}"
             f"{context_text}\n"
@@ -293,7 +332,8 @@ class PreMarketPlanner:
             f'      "stock_code": "...",\n'
             f'      "scenarios": [\n'
             f'        {{\n'
-            f'          "condition": {{"rsi_below": 30, "volume_ratio_above": 2.0}},\n'
+            f'          "condition": {{"rsi_below": 30, "volume_ratio_above": 2.0,'
+            f' "unrealized_pnl_pct_above": 3.0, "holding_days_above": 5}},\n'
             f'          "action": "BUY|SELL|HOLD",\n'
             f'          "confidence": 85,\n'
             f'          "allocation_pct": 10.0,\n'
@@ -307,7 +347,8 @@ class PreMarketPlanner:
             f'}}\n\n'
             f"Rules:\n"
             f"- Max {max_scenarios} scenarios per stock\n"
-            f"- Only use stocks from the candidates list\n"
+            f"- Candidates list is the primary source for BUY candidates\n"
+            f"{holdings_instruction}"
             f"- Confidence 0-100 (80+ for actionable trades)\n"
             f"- stop_loss_pct must be <= 0, take_profit_pct must be >= 0\n"
             f"- Return ONLY the JSON, no markdown fences or explanation\n"
@@ -320,12 +361,19 @@ class PreMarketPlanner:
         market: str,
         candidates: list[ScanCandidate],
         cross_market: CrossMarketContext | None,
+        current_holdings: list[dict] | None = None,
     ) -> DayPlaybook:
         """Parse Gemini's JSON response into a validated DayPlaybook."""
         cleaned = self._extract_json(response_text)
         data = json.loads(cleaned)
 
         valid_codes = {c.stock_code for c in candidates}
+        # Holdings are also valid — AI may generate SELL/HOLD scenarios for them
+        if current_holdings:
+            for h in current_holdings:
+                code = h.get("stock_code", "")
+                if code:
+                    valid_codes.add(code)
 
         # Parse market outlook
         outlook_str = data.get("market_outlook", "neutral")
@@ -389,6 +437,10 @@ class PreMarketPlanner:
                 price_below=cond_data.get("price_below"),
                 price_change_pct_above=cond_data.get("price_change_pct_above"),
                 price_change_pct_below=cond_data.get("price_change_pct_below"),
+                unrealized_pnl_pct_above=cond_data.get("unrealized_pnl_pct_above"),
+                unrealized_pnl_pct_below=cond_data.get("unrealized_pnl_pct_below"),
+                holding_days_above=cond_data.get("holding_days_above"),
+                holding_days_below=cond_data.get("holding_days_below"),
             )
 
             if not condition.has_any_condition():
@@ -470,3 +522,99 @@ class PreMarketPlanner:
                 ),
             ],
         )
+
+    @staticmethod
+    def _smart_fallback_playbook(
+        today: date,
+        market: str,
+        candidates: list[ScanCandidate],
+        settings: Settings,
+    ) -> DayPlaybook:
+        """Rule-based fallback playbook when Gemini is unavailable.
+
+        Uses scanner signals (RSI, volume_ratio) to generate meaningful BUY
+        conditions instead of the all-SELL defensive playbook.  Candidates are
+        already pre-qualified by SmartVolatilityScanner, so we trust their
+        signals and build actionable scenarios from them.
+
+        Scenario logic per candidate:
+        - momentum signal: BUY when volume_ratio exceeds scanner threshold
+        - oversold signal: BUY when RSI is below oversold threshold
+        - always: SELL stop-loss at -3.0% as guard
+        """
+        stock_playbooks = []
+        for c in candidates:
+            scenarios: list[StockScenario] = []
+
+            if c.signal == "momentum":
+                scenarios.append(
+                    StockScenario(
+                        condition=StockCondition(
+                            volume_ratio_above=settings.VOL_MULTIPLIER,
+                        ),
+                        action=ScenarioAction.BUY,
+                        confidence=80,
+                        allocation_pct=10.0,
+                        stop_loss_pct=-3.0,
+                        take_profit_pct=5.0,
+                        rationale=(
+                            f"Rule-based BUY: momentum signal, "
+                            f"volume={c.volume_ratio:.1f}x (fallback planner)"
+                        ),
+                    )
+                )
+            elif c.signal == "oversold":
+                scenarios.append(
+                    StockScenario(
+                        condition=StockCondition(
+                            rsi_below=settings.RSI_OVERSOLD_THRESHOLD,
+                        ),
+                        action=ScenarioAction.BUY,
+                        confidence=80,
+                        allocation_pct=10.0,
+                        stop_loss_pct=-3.0,
+                        take_profit_pct=5.0,
+                        rationale=(
+                            f"Rule-based BUY: oversold signal, "
+                            f"RSI={c.rsi:.0f} (fallback planner)"
+                        ),
+                    )
+                )
+
+            # Always add stop-loss guard
+            scenarios.append(
+                StockScenario(
+                    condition=StockCondition(price_change_pct_below=-3.0),
+                    action=ScenarioAction.SELL,
+                    confidence=90,
+                    stop_loss_pct=-3.0,
+                    rationale="Rule-based stop-loss (fallback planner)",
+                )
+            )
+
+            stock_playbooks.append(
+                StockPlaybook(
+                    stock_code=c.stock_code,
+                    scenarios=scenarios,
+                )
+            )
+
+        logger.info(
+            "Smart fallback playbook for %s: %d stocks with rule-based BUY/SELL conditions",
+            market,
+            len(stock_playbooks),
+        )
+        return DayPlaybook(
+            date=today,
+            market=market,
+            market_outlook=MarketOutlook.NEUTRAL,
+            default_action=ScenarioAction.HOLD,
+            stock_playbooks=stock_playbooks,
+            global_rules=[
+                GlobalRule(
+                    condition="portfolio_pnl_pct < -2.0",
+                    action=ScenarioAction.REDUCE_ALL,
+                    rationale="Defensive: reduce on loss threshold",
+                ),
+            ],
+        )

src/strategy/scenario_engine.py

@@ -206,6 +206,37 @@ class ScenarioEngine:
         if condition.price_change_pct_below is not None:
             checks.append(price_change_pct is not None and price_change_pct < condition.price_change_pct_below)
 
+        # Position-aware conditions
+        unrealized_pnl_pct = self._safe_float(market_data.get("unrealized_pnl_pct"))
+        if condition.unrealized_pnl_pct_above is not None or condition.unrealized_pnl_pct_below is not None:
+            if "unrealized_pnl_pct" not in market_data:
+                self._warn_missing_key("unrealized_pnl_pct")
+        if condition.unrealized_pnl_pct_above is not None:
+            checks.append(
+                unrealized_pnl_pct is not None
+                and unrealized_pnl_pct > condition.unrealized_pnl_pct_above
+            )
+        if condition.unrealized_pnl_pct_below is not None:
+            checks.append(
+                unrealized_pnl_pct is not None
+                and unrealized_pnl_pct < condition.unrealized_pnl_pct_below
+            )
+
+        holding_days = self._safe_float(market_data.get("holding_days"))
+        if condition.holding_days_above is not None or condition.holding_days_below is not None:
+            if "holding_days" not in market_data:
+                self._warn_missing_key("holding_days")
+        if condition.holding_days_above is not None:
+            checks.append(
+                holding_days is not None
+                and holding_days > condition.holding_days_above
+            )
+        if condition.holding_days_below is not None:
+            checks.append(
+                holding_days is not None
+                and holding_days < condition.holding_days_below
+            )
+
         return len(checks) > 0 and all(checks)
 
     def _evaluate_global_condition(
@@ -266,5 +297,9 @@ class ScenarioEngine:
             details["current_price"] = self._safe_float(market_data.get("current_price"))
         if condition.price_change_pct_above is not None or condition.price_change_pct_below is not None:
             details["price_change_pct"] = self._safe_float(market_data.get("price_change_pct"))
+        if condition.unrealized_pnl_pct_above is not None or condition.unrealized_pnl_pct_below is not None:
+            details["unrealized_pnl_pct"] = self._safe_float(market_data.get("unrealized_pnl_pct"))
+        if condition.holding_days_above is not None or condition.holding_days_below is not None:
+            details["holding_days"] = self._safe_float(market_data.get("holding_days"))
 
         return details

tests/test_backup.py

@@ -3,9 +3,11 @@
 from __future__ import annotations
 
 import sqlite3
+import sys
 import tempfile
 from datetime import UTC, datetime, timedelta
 from pathlib import Path
+from unittest.mock import MagicMock, patch
 
 import pytest
 
@@ -363,3 +365,435 @@ class TestHealthMonitor:
         assert "timestamp" in report
         assert "checks" in report
         assert len(report["checks"]) == 3
+
+
+# ---------------------------------------------------------------------------
+# BackupExporter — additional coverage for previously uncovered branches
+# ---------------------------------------------------------------------------
+
+
+@pytest.fixture
+def empty_db(tmp_path: Path) -> Path:
+    """Create a temporary database with NO trade records."""
+    db_path = tmp_path / "empty_trades.db"
+    conn = sqlite3.connect(str(db_path))
+    conn.execute(
+        """CREATE TABLE trades (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            timestamp TEXT NOT NULL,
+            stock_code TEXT NOT NULL,
+            action TEXT NOT NULL,
+            quantity INTEGER NOT NULL,
+            price REAL NOT NULL,
+            confidence INTEGER NOT NULL,
+            rationale TEXT,
+            pnl REAL DEFAULT 0.0
+        )"""
+    )
+    conn.commit()
+    conn.close()
+    return db_path
+
+
+class TestBackupExporterAdditional:
+    """Cover branches missed in the original TestBackupExporter suite."""
+
+    def test_export_all_default_formats(self, temp_db: Path, tmp_path: Path) -> None:
+        """export_all with formats=None must default to JSON+CSV+Parquet path."""
+        exporter = BackupExporter(str(temp_db))
+        # formats=None triggers the default list assignment (line 62)
+        results = exporter.export_all(tmp_path / "out", formats=None, compress=False)
+        # JSON and CSV must always succeed; Parquet needs pyarrow
+        assert ExportFormat.JSON in results
+        assert ExportFormat.CSV in results
+
+    def test_export_all_logs_error_on_failure(
+        self, temp_db: Path, tmp_path: Path
+    ) -> None:
+        """export_all must log an error and continue when one format fails."""
+        exporter = BackupExporter(str(temp_db))
+        # Patch _export_format to raise on JSON, succeed on CSV
+        original = exporter._export_format
+
+        def failing_export(fmt, *args, **kwargs):  # type: ignore[no-untyped-def]
+            if fmt == ExportFormat.JSON:
+                raise RuntimeError("simulated failure")
+            return original(fmt, *args, **kwargs)
+
+        exporter._export_format = failing_export  # type: ignore[method-assign]
+        results = exporter.export_all(
+            tmp_path / "out",
+            formats=[ExportFormat.JSON, ExportFormat.CSV],
+            compress=False,
+        )
+        # JSON failed → not in results; CSV succeeded → in results
+        assert ExportFormat.JSON not in results
+        assert ExportFormat.CSV in results
+
+    def test_export_csv_empty_trades_no_compress(
+        self, empty_db: Path, tmp_path: Path
+    ) -> None:
+        """CSV export with no trades and compress=False must write header row only."""
+        exporter = BackupExporter(str(empty_db))
+        results = exporter.export_all(
+            tmp_path / "out",
+            formats=[ExportFormat.CSV],
+            compress=False,
+        )
+        assert ExportFormat.CSV in results
+        out = results[ExportFormat.CSV]
+        assert out.exists()
+        content = out.read_text()
+        assert "timestamp" in content
+
+    def test_export_csv_empty_trades_compressed(
+        self, empty_db: Path, tmp_path: Path
+    ) -> None:
+        """CSV export with no trades and compress=True must write gzipped header."""
+        import gzip
+
+        exporter = BackupExporter(str(empty_db))
+        results = exporter.export_all(
+            tmp_path / "out",
+            formats=[ExportFormat.CSV],
+            compress=True,
+        )
+        assert ExportFormat.CSV in results
+        out = results[ExportFormat.CSV]
+        assert out.suffix == ".gz"
+        with gzip.open(out, "rt", encoding="utf-8") as f:
+            content = f.read()
+        assert "timestamp" in content
+
+    def test_export_csv_with_data_compressed(
+        self, temp_db: Path, tmp_path: Path
+    ) -> None:
+        """CSV export with data and compress=True must write gzipped rows."""
+        import gzip
+
+        exporter = BackupExporter(str(temp_db))
+        results = exporter.export_all(
+            tmp_path / "out",
+            formats=[ExportFormat.CSV],
+            compress=True,
+        )
+        assert ExportFormat.CSV in results
+        out = results[ExportFormat.CSV]
+        with gzip.open(out, "rt", encoding="utf-8") as f:
+            lines = f.readlines()
+        # Header + 3 data rows
+        assert len(lines) == 4
+
+    def test_export_parquet_raises_import_error_without_pyarrow(
+        self, temp_db: Path, tmp_path: Path
+    ) -> None:
+        """Parquet export must raise ImportError when pyarrow is not installed."""
+        exporter = BackupExporter(str(temp_db))
+        with patch.dict(sys.modules, {"pyarrow": None, "pyarrow.parquet": None}):
+            try:
+                import pyarrow  # noqa: F401
+                pytest.skip("pyarrow is installed; cannot test ImportError path")
+            except ImportError:
+                pass
+            results = exporter.export_all(
+                tmp_path / "out",
+                formats=[ExportFormat.PARQUET],
+                compress=False,
+            )
+            # Parquet export fails gracefully; result dict should not contain it
+            assert ExportFormat.PARQUET not in results
+
+
+# ---------------------------------------------------------------------------
+# CloudStorage — mocked boto3 tests
+# ---------------------------------------------------------------------------
+
+
+@pytest.fixture
+def mock_boto3_module():
+    """Inject a fake boto3 into sys.modules for the duration of the test."""
+    mock = MagicMock()
+    with patch.dict(sys.modules, {"boto3": mock}):
+        yield mock
+
+
+@pytest.fixture
+def s3_config():
+    """Minimal S3Config for tests."""
+    from src.backup.cloud_storage import S3Config
+
+    return S3Config(
+        endpoint_url="http://localhost:9000",
+        access_key="minioadmin",
+        secret_key="minioadmin",
+        bucket_name="test-bucket",
+        region="us-east-1",
+    )
+
+
+class TestCloudStorage:
+    """Test CloudStorage using mocked boto3."""
+
+    def test_init_creates_s3_client(self, mock_boto3_module, s3_config) -> None:
+        """CloudStorage.__init__ must call boto3.client with the correct args."""
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        mock_boto3_module.client.assert_called_once()
+        call_kwargs = mock_boto3_module.client.call_args[1]
+        assert call_kwargs["aws_access_key_id"] == "minioadmin"
+        assert call_kwargs["aws_secret_access_key"] == "minioadmin"
+        assert storage.config == s3_config
+
+    def test_init_raises_if_boto3_missing(self, s3_config) -> None:
+        """CloudStorage.__init__ must raise ImportError when boto3 is absent."""
+        with patch.dict(sys.modules, {"boto3": None}):  # type: ignore[dict-item]
+            with pytest.raises((ImportError, TypeError)):
+                # Re-import to trigger the try/except inside __init__
+                import importlib
+
+                import src.backup.cloud_storage as m
+
+                importlib.reload(m)
+                m.CloudStorage(s3_config)
+
+    def test_upload_file_success(
+        self, mock_boto3_module, s3_config, tmp_path: Path
+    ) -> None:
+        """upload_file must call client.upload_file and return the object key."""
+        from src.backup.cloud_storage import CloudStorage
+
+        test_file = tmp_path / "backup.json.gz"
+        test_file.write_bytes(b"data")
+
+        storage = CloudStorage(s3_config)
+        key = storage.upload_file(test_file, object_key="backups/backup.json.gz")
+
+        assert key == "backups/backup.json.gz"
+        storage.client.upload_file.assert_called_once()
+
+    def test_upload_file_default_key(
+        self, mock_boto3_module, s3_config, tmp_path: Path
+    ) -> None:
+        """upload_file without object_key must use the filename as key."""
+        from src.backup.cloud_storage import CloudStorage
+
+        test_file = tmp_path / "myfile.gz"
+        test_file.write_bytes(b"data")
+
+        storage = CloudStorage(s3_config)
+        key = storage.upload_file(test_file)
+
+        assert key == "myfile.gz"
+
+    def test_upload_file_not_found(
+        self, mock_boto3_module, s3_config, tmp_path: Path
+    ) -> None:
+        """upload_file must raise FileNotFoundError for missing files."""
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        with pytest.raises(FileNotFoundError):
+            storage.upload_file(tmp_path / "nonexistent.gz")
+
+    def test_upload_file_propagates_client_error(
+        self, mock_boto3_module, s3_config, tmp_path: Path
+    ) -> None:
+        """upload_file must re-raise exceptions from the boto3 client."""
+        from src.backup.cloud_storage import CloudStorage
+
+        test_file = tmp_path / "backup.gz"
+        test_file.write_bytes(b"data")
+
+        storage = CloudStorage(s3_config)
+        storage.client.upload_file.side_effect = RuntimeError("network error")
+
+        with pytest.raises(RuntimeError, match="network error"):
+            storage.upload_file(test_file)
+
+    def test_download_file_success(
+        self, mock_boto3_module, s3_config, tmp_path: Path
+    ) -> None:
+        """download_file must call client.download_file and return local path."""
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        dest = tmp_path / "downloads" / "backup.gz"
+
+        result = storage.download_file("backups/backup.gz", dest)
+
+        assert result == dest
+        storage.client.download_file.assert_called_once()
+
+    def test_download_file_propagates_error(
+        self, mock_boto3_module, s3_config, tmp_path: Path
+    ) -> None:
+        """download_file must re-raise exceptions from the boto3 client."""
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        storage.client.download_file.side_effect = RuntimeError("timeout")
+
+        with pytest.raises(RuntimeError, match="timeout"):
+            storage.download_file("key", tmp_path / "dest.gz")
+
+    def test_list_files_returns_objects(
+        self, mock_boto3_module, s3_config
+    ) -> None:
+        """list_files must return parsed file metadata from S3 response."""
+        from datetime import timezone
+
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        storage.client.list_objects_v2.return_value = {
+            "Contents": [
+                {
+                    "Key": "backups/a.gz",
+                    "Size": 1024,
+                    "LastModified": datetime(2026, 1, 1, tzinfo=timezone.utc),
+                    "ETag": '"abc123"',
+                }
+            ]
+        }
+
+        files = storage.list_files(prefix="backups/")
+        assert len(files) == 1
+        assert files[0]["key"] == "backups/a.gz"
+        assert files[0]["size_bytes"] == 1024
+
+    def test_list_files_empty_bucket(
+        self, mock_boto3_module, s3_config
+    ) -> None:
+        """list_files must return empty list when bucket has no objects."""
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        storage.client.list_objects_v2.return_value = {}
+
+        files = storage.list_files()
+        assert files == []
+
+    def test_list_files_propagates_error(
+        self, mock_boto3_module, s3_config
+    ) -> None:
+        """list_files must re-raise exceptions from the boto3 client."""
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        storage.client.list_objects_v2.side_effect = RuntimeError("auth error")
+
+        with pytest.raises(RuntimeError):
+            storage.list_files()
+
+    def test_delete_file_success(
+        self, mock_boto3_module, s3_config
+    ) -> None:
+        """delete_file must call client.delete_object with the correct key."""
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        storage.delete_file("backups/old.gz")
+        storage.client.delete_object.assert_called_once_with(
+            Bucket="test-bucket", Key="backups/old.gz"
+        )
+
+    def test_delete_file_propagates_error(
+        self, mock_boto3_module, s3_config
+    ) -> None:
+        """delete_file must re-raise exceptions from the boto3 client."""
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        storage.client.delete_object.side_effect = RuntimeError("permission denied")
+
+        with pytest.raises(RuntimeError):
+            storage.delete_file("backups/old.gz")
+
+    def test_get_storage_stats_success(
+        self, mock_boto3_module, s3_config
+    ) -> None:
+        """get_storage_stats must aggregate file sizes correctly."""
+        from datetime import timezone
+
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        storage.client.list_objects_v2.return_value = {
+            "Contents": [
+                {
+                    "Key": "a.gz",
+                    "Size": 1024 * 1024,
+                    "LastModified": datetime(2026, 1, 1, tzinfo=timezone.utc),
+                    "ETag": '"x"',
+                },
+                {
+                    "Key": "b.gz",
+                    "Size": 1024 * 1024,
+                    "LastModified": datetime(2026, 1, 2, tzinfo=timezone.utc),
+                    "ETag": '"y"',
+                },
+            ]
+        }
+
+        stats = storage.get_storage_stats()
+        assert stats["total_files"] == 2
+        assert stats["total_size_bytes"] == 2 * 1024 * 1024
+        assert stats["total_size_mb"] == pytest.approx(2.0)
+
+    def test_get_storage_stats_on_error(
+        self, mock_boto3_module, s3_config
+    ) -> None:
+        """get_storage_stats must return error dict without raising on failure."""
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        storage.client.list_objects_v2.side_effect = RuntimeError("no connection")
+
+        stats = storage.get_storage_stats()
+        assert "error" in stats
+        assert stats["total_files"] == 0
+
+    def test_verify_connection_success(
+        self, mock_boto3_module, s3_config
+    ) -> None:
+        """verify_connection must return True when head_bucket succeeds."""
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        result = storage.verify_connection()
+        assert result is True
+
+    def test_verify_connection_failure(
+        self, mock_boto3_module, s3_config
+    ) -> None:
+        """verify_connection must return False when head_bucket raises."""
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        storage.client.head_bucket.side_effect = RuntimeError("no such bucket")
+
+        result = storage.verify_connection()
+        assert result is False
+
+    def test_enable_versioning(
+        self, mock_boto3_module, s3_config
+    ) -> None:
+        """enable_versioning must call put_bucket_versioning."""
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        storage.enable_versioning()
+        storage.client.put_bucket_versioning.assert_called_once()
+
+    def test_enable_versioning_propagates_error(
+        self, mock_boto3_module, s3_config
+    ) -> None:
+        """enable_versioning must re-raise exceptions from the boto3 client."""
+        from src.backup.cloud_storage import CloudStorage
+
+        storage = CloudStorage(s3_config)
+        storage.client.put_bucket_versioning.side_effect = RuntimeError("denied")
+
+        with pytest.raises(RuntimeError):
+            storage.enable_versioning()

tests/test_brain.py

@@ -2,6 +2,10 @@
 
 from __future__ import annotations
 
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
 from src.brain.gemini_client import GeminiClient
 
 # ---------------------------------------------------------------------------
@@ -270,3 +274,97 @@ class TestBatchDecisionParsing:
 
         assert decisions["AAPL"].action == "HOLD"
         assert decisions["AAPL"].confidence == 0
+
+
+# ---------------------------------------------------------------------------
+# Prompt Override (used by pre_market_planner)
+# ---------------------------------------------------------------------------
+
+
+class TestPromptOverride:
+    """decide() must use prompt_override when present in market_data."""
+
+    @pytest.mark.asyncio
+    async def test_prompt_override_is_sent_to_gemini(self, settings):
+        """When prompt_override is in market_data, it should be used as the prompt."""
+        client = GeminiClient(settings)
+
+        custom_prompt = "You are a playbook generator. Return JSON with scenarios."
+
+        mock_response = MagicMock()
+        mock_response.text = '{"action": "HOLD", "confidence": 50, "rationale": "test"}'
+
+        with patch.object(
+            client._client.aio.models,
+            "generate_content",
+            new_callable=AsyncMock,
+            return_value=mock_response,
+        ) as mock_generate:
+            market_data = {
+                "stock_code": "PLANNER",
+                "current_price": 0,
+                "prompt_override": custom_prompt,
+            }
+            await client.decide(market_data)
+
+            # Verify the custom prompt was sent, not a built prompt
+            mock_generate.assert_called_once()
+            actual_prompt = mock_generate.call_args[1].get(
+                "contents", mock_generate.call_args[0][1] if len(mock_generate.call_args[0]) > 1 else None
+            )
+            assert actual_prompt == custom_prompt
+
+    @pytest.mark.asyncio
+    async def test_prompt_override_skips_optimization(self, settings):
+        """prompt_override should bypass prompt optimization."""
+        client = GeminiClient(settings)
+        client._enable_optimization = True
+
+        custom_prompt = "Custom playbook prompt"
+
+        mock_response = MagicMock()
+        mock_response.text = '{"action": "HOLD", "confidence": 50, "rationale": "ok"}'
+
+        with patch.object(
+            client._client.aio.models,
+            "generate_content",
+            new_callable=AsyncMock,
+            return_value=mock_response,
+        ) as mock_generate:
+            market_data = {
+                "stock_code": "PLANNER",
+                "current_price": 0,
+                "prompt_override": custom_prompt,
+            }
+            await client.decide(market_data)
+
+            actual_prompt = mock_generate.call_args[1].get(
+                "contents", mock_generate.call_args[0][1] if len(mock_generate.call_args[0]) > 1 else None
+            )
+            assert actual_prompt == custom_prompt
+
+    @pytest.mark.asyncio
+    async def test_without_prompt_override_uses_build_prompt(self, settings):
+        """Without prompt_override, decide() should use build_prompt as before."""
+        client = GeminiClient(settings)
+
+        mock_response = MagicMock()
+        mock_response.text = '{"action": "HOLD", "confidence": 50, "rationale": "ok"}'
+
+        with patch.object(
+            client._client.aio.models,
+            "generate_content",
+            new_callable=AsyncMock,
+            return_value=mock_response,
+        ) as mock_generate:
+            market_data = {
+                "stock_code": "005930",
+                "current_price": 72000,
+            }
+            await client.decide(market_data)
+
+            actual_prompt = mock_generate.call_args[1].get(
+                "contents", mock_generate.call_args[0][1] if len(mock_generate.call_args[0]) > 1 else None
+            )
+            # Should contain stock code from build_prompt, not be a custom override
+            assert "005930" in actual_prompt

tests/test_broker.py

@@ -3,7 +3,7 @@
 from __future__ import annotations
 
 import asyncio
-from unittest.mock import AsyncMock, patch
+from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
@@ -90,12 +90,12 @@ class TestTokenManagement:
         await broker.close()
 
     @pytest.mark.asyncio
-    async def test_token_refresh_cooldown_prevents_rapid_retries(self, settings):
+    async def test_token_refresh_cooldown_waits_then_retries(self, settings):
-        """Token refresh should enforce cooldown after failure (issue #54)."""
+        """Token refresh should wait out cooldown then retry (issue #54)."""
         broker = KISBroker(settings)
-        broker._refresh_cooldown = 2.0  # Short cooldown for testing
+        broker._refresh_cooldown = 0.1  # Short cooldown for testing
 
-        # First refresh attempt fails with 403 (EGW00133)
+        # All attempts fail with 403 (EGW00133)
         mock_resp_403 = AsyncMock()
         mock_resp_403.status = 403
         mock_resp_403.text = AsyncMock(
@@ -109,8 +109,8 @@ class TestTokenManagement:
             with pytest.raises(ConnectionError, match="Token refresh failed"):
                 await broker._ensure_token()
 
-            # Second attempt within cooldown should fail with cooldown error
+            # Second attempt within cooldown should wait then retry (and still get 403)
-            with pytest.raises(ConnectionError, match="Token refresh on cooldown"):
+            with pytest.raises(ConnectionError, match="Token refresh failed"):
                 await broker._ensure_token()
 
         await broker.close()
@@ -296,3 +296,432 @@ class TestHashKey:
                 mock_acquire.assert_called_once()
 
         await broker.close()
+
+
+# ---------------------------------------------------------------------------
+# fetch_market_rankings — TR_ID, path, params (issue #155)
+# ---------------------------------------------------------------------------
+
+
+def _make_ranking_mock(items: list[dict]) -> AsyncMock:
+    """Build a mock HTTP response returning ranking items."""
+    mock_resp = AsyncMock()
+    mock_resp.status = 200
+    mock_resp.json = AsyncMock(return_value={"output": items})
+    mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+    mock_resp.__aexit__ = AsyncMock(return_value=False)
+    return mock_resp
+
+
+class TestFetchMarketRankings:
+    """Verify correct TR_ID, API path, and params per ranking_type (issue #155)."""
+
+    @pytest.fixture
+    def broker(self, settings) -> KISBroker:
+        b = KISBroker(settings)
+        b._access_token = "tok"
+        b._token_expires_at = float("inf")
+        b._rate_limiter.acquire = AsyncMock()
+        return b
+
+    @pytest.mark.asyncio
+    async def test_volume_uses_correct_tr_id_and_path(self, broker: KISBroker) -> None:
+        mock_resp = _make_ranking_mock([])
+        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
+            await broker.fetch_market_rankings(ranking_type="volume")
+
+        call_kwargs = mock_get.call_args
+        url = call_kwargs[0][0] if call_kwargs[0] else call_kwargs[1].get("url", "")
+        headers = call_kwargs[1].get("headers", {})
+        params = call_kwargs[1].get("params", {})
+
+        assert "volume-rank" in url
+        assert headers.get("tr_id") == "FHPST01710000"
+        assert params.get("FID_COND_SCR_DIV_CODE") == "20171"
+        assert params.get("FID_TRGT_EXLS_CLS_CODE") == "0000000000"
+
+    @pytest.mark.asyncio
+    async def test_fluctuation_uses_correct_tr_id_and_path(self, broker: KISBroker) -> None:
+        mock_resp = _make_ranking_mock([])
+        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
+            await broker.fetch_market_rankings(ranking_type="fluctuation")
+
+        call_kwargs = mock_get.call_args
+        url = call_kwargs[0][0] if call_kwargs[0] else call_kwargs[1].get("url", "")
+        headers = call_kwargs[1].get("headers", {})
+        params = call_kwargs[1].get("params", {})
+
+        assert "ranking/fluctuation" in url
+        assert headers.get("tr_id") == "FHPST01700000"
+        assert params.get("fid_cond_scr_div_code") == "20170"
+
+    @pytest.mark.asyncio
+    async def test_volume_returns_parsed_rows(self, broker: KISBroker) -> None:
+        items = [
+            {
+                "mksc_shrn_iscd": "005930",
+                "hts_kor_isnm": "삼성전자",
+                "stck_prpr": "75000",
+                "acml_vol": "10000000",
+                "prdy_ctrt": "2.5",
+                "vol_inrt": "150",
+            }
+        ]
+        mock_resp = _make_ranking_mock(items)
+        with patch("aiohttp.ClientSession.get", return_value=mock_resp):
+            result = await broker.fetch_market_rankings(ranking_type="volume")
+
+        assert len(result) == 1
+        assert result[0]["stock_code"] == "005930"
+        assert result[0]["price"] == 75000.0
+        assert result[0]["change_rate"] == 2.5
+
+
+# ---------------------------------------------------------------------------
+# KRX tick unit / round-down helpers (issue #157)
+# ---------------------------------------------------------------------------
+
+
+from src.broker.kis_api import kr_tick_unit, kr_round_down  # noqa: E402
+
+
+class TestKrTickUnit:
+    """kr_tick_unit and kr_round_down must implement KRX price tick rules."""
+
+    @pytest.mark.parametrize(
+        "price, expected_tick",
+        [
+            (1999, 1),
+            (2000, 5),
+            (4999, 5),
+            (5000, 10),
+            (19999, 10),
+            (20000, 50),
+            (49999, 50),
+            (50000, 100),
+            (199999, 100),
+            (200000, 500),
+            (499999, 500),
+            (500000, 1000),
+            (1000000, 1000),
+        ],
+    )
+    def test_tick_unit_boundaries(self, price: int, expected_tick: int) -> None:
+        assert kr_tick_unit(price) == expected_tick
+
+    @pytest.mark.parametrize(
+        "price, expected_rounded",
+        [
+            (188150, 188100),   # 100원 단위, 50원 잔여 → 내림
+            (188100, 188100),   # 이미 정렬됨
+            (75050, 75000),     # 100원 단위, 50원 잔여 → 내림
+            (49950, 49950),     # 50원 단위 정렬됨
+            (49960, 49950),     # 50원 단위, 10원 잔여 → 내림
+            (1999, 1999),       # 1원 단위 → 그대로
+            (5003, 5000),       # 10원 단위, 3원 잔여 → 내림
+        ],
+    )
+    def test_round_down_to_tick(self, price: int, expected_rounded: int) -> None:
+        assert kr_round_down(price) == expected_rounded
+
+
+# ---------------------------------------------------------------------------
+# get_current_price (issue #157)
+# ---------------------------------------------------------------------------
+
+
+class TestGetCurrentPrice:
+    """get_current_price must use inquire-price API and return (price, change, foreigner)."""
+
+    @pytest.fixture
+    def broker(self, settings) -> KISBroker:
+        b = KISBroker(settings)
+        b._access_token = "tok"
+        b._token_expires_at = float("inf")
+        b._rate_limiter.acquire = AsyncMock()
+        return b
+
+    @pytest.mark.asyncio
+    async def test_returns_correct_fields(self, broker: KISBroker) -> None:
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(
+            return_value={
+                "rt_cd": "0",
+                "output": {
+                    "stck_prpr": "188600",
+                    "prdy_ctrt": "3.97",
+                    "frgn_ntby_qty": "12345",
+                },
+            }
+        )
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
+            price, change_pct, foreigner = await broker.get_current_price("005930")
+
+        assert price == 188600.0
+        assert change_pct == 3.97
+        assert foreigner == 12345.0
+
+        call_kwargs = mock_get.call_args
+        url = call_kwargs[0][0] if call_kwargs[0] else call_kwargs[1].get("url", "")
+        headers = call_kwargs[1].get("headers", {})
+        assert "inquire-price" in url
+        assert headers.get("tr_id") == "FHKST01010100"
+
+    @pytest.mark.asyncio
+    async def test_http_error_raises_connection_error(self, broker: KISBroker) -> None:
+        mock_resp = AsyncMock()
+        mock_resp.status = 500
+        mock_resp.text = AsyncMock(return_value="Internal Server Error")
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        with patch("aiohttp.ClientSession.get", return_value=mock_resp):
+            with pytest.raises(ConnectionError, match="get_current_price failed"):
+                await broker.get_current_price("005930")
+
+
+# ---------------------------------------------------------------------------
+# send_order tick rounding and ORD_DVSN (issue #157)
+# ---------------------------------------------------------------------------
+
+
+class TestSendOrderTickRounding:
+    """send_order must apply KRX tick rounding and correct ORD_DVSN codes."""
+
+    @pytest.fixture
+    def broker(self, settings) -> KISBroker:
+        b = KISBroker(settings)
+        b._access_token = "tok"
+        b._token_expires_at = float("inf")
+        b._rate_limiter.acquire = AsyncMock()
+        return b
+
+    @pytest.mark.asyncio
+    async def test_limit_order_rounds_down_to_tick(self, broker: KISBroker) -> None:
+        """Price 188150 (not on 100-won tick) must be rounded to 188100."""
+        mock_hash = AsyncMock()
+        mock_hash.status = 200
+        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
+        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
+        mock_hash.__aexit__ = AsyncMock(return_value=False)
+
+        mock_order = AsyncMock()
+        mock_order.status = 200
+        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
+        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
+        mock_order.__aexit__ = AsyncMock(return_value=False)
+
+        with patch(
+            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
+        ) as mock_post:
+            await broker.send_order("005930", "BUY", 1, price=188150)
+
+        order_call = mock_post.call_args_list[1]
+        body = order_call[1].get("json", {})
+        assert body["ORD_UNPR"] == "188100"  # rounded down
+        assert body["ORD_DVSN"] == "00"       # 지정가
+
+    @pytest.mark.asyncio
+    async def test_limit_order_ord_dvsn_is_00(self, broker: KISBroker) -> None:
+        """send_order with price>0 must use ORD_DVSN='00' (지정가)."""
+        mock_hash = AsyncMock()
+        mock_hash.status = 200
+        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
+        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
+        mock_hash.__aexit__ = AsyncMock(return_value=False)
+
+        mock_order = AsyncMock()
+        mock_order.status = 200
+        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
+        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
+        mock_order.__aexit__ = AsyncMock(return_value=False)
+
+        with patch(
+            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
+        ) as mock_post:
+            await broker.send_order("005930", "BUY", 1, price=50000)
+
+        order_call = mock_post.call_args_list[1]
+        body = order_call[1].get("json", {})
+        assert body["ORD_DVSN"] == "00"
+
+    @pytest.mark.asyncio
+    async def test_market_order_ord_dvsn_is_01(self, broker: KISBroker) -> None:
+        """send_order with price=0 must use ORD_DVSN='01' (시장가)."""
+        mock_hash = AsyncMock()
+        mock_hash.status = 200
+        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
+        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
+        mock_hash.__aexit__ = AsyncMock(return_value=False)
+
+        mock_order = AsyncMock()
+        mock_order.status = 200
+        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
+        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
+        mock_order.__aexit__ = AsyncMock(return_value=False)
+
+        with patch(
+            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
+        ) as mock_post:
+            await broker.send_order("005930", "SELL", 1, price=0)
+
+        order_call = mock_post.call_args_list[1]
+        body = order_call[1].get("json", {})
+        assert body["ORD_DVSN"] == "01"
+
+
+# ---------------------------------------------------------------------------
+# TR_ID live/paper branching (issues #201, #202, #203)
+# ---------------------------------------------------------------------------
+
+
+class TestTRIDBranchingDomestic:
+    """get_balance and send_order must use correct TR_ID for live vs paper mode."""
+
+    def _make_broker(self, settings, mode: str) -> KISBroker:
+        from src.config import Settings
+
+        s = Settings(
+            KIS_APP_KEY=settings.KIS_APP_KEY,
+            KIS_APP_SECRET=settings.KIS_APP_SECRET,
+            KIS_ACCOUNT_NO=settings.KIS_ACCOUNT_NO,
+            GEMINI_API_KEY=settings.GEMINI_API_KEY,
+            DB_PATH=":memory:",
+            ENABLED_MARKETS="KR",
+            MODE=mode,
+        )
+        b = KISBroker(s)
+        b._access_token = "tok"
+        b._token_expires_at = float("inf")
+        b._rate_limiter.acquire = AsyncMock()
+        return b
+
+    @pytest.mark.asyncio
+    async def test_get_balance_paper_uses_vttc8434r(self, settings) -> None:
+        broker = self._make_broker(settings, "paper")
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(
+            return_value={"output1": [], "output2": {}}
+        )
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
+            await broker.get_balance()
+
+        headers = mock_get.call_args[1].get("headers", {})
+        assert headers["tr_id"] == "VTTC8434R"
+
+    @pytest.mark.asyncio
+    async def test_get_balance_live_uses_tttc8434r(self, settings) -> None:
+        broker = self._make_broker(settings, "live")
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(
+            return_value={"output1": [], "output2": {}}
+        )
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
+            await broker.get_balance()
+
+        headers = mock_get.call_args[1].get("headers", {})
+        assert headers["tr_id"] == "TTTC8434R"
+
+    @pytest.mark.asyncio
+    async def test_send_order_buy_paper_uses_vttc0012u(self, settings) -> None:
+        broker = self._make_broker(settings, "paper")
+        mock_hash = AsyncMock()
+        mock_hash.status = 200
+        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
+        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
+        mock_hash.__aexit__ = AsyncMock(return_value=False)
+
+        mock_order = AsyncMock()
+        mock_order.status = 200
+        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
+        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
+        mock_order.__aexit__ = AsyncMock(return_value=False)
+
+        with patch(
+            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
+        ) as mock_post:
+            await broker.send_order("005930", "BUY", 1)
+
+        order_headers = mock_post.call_args_list[1][1].get("headers", {})
+        assert order_headers["tr_id"] == "VTTC0012U"
+
+    @pytest.mark.asyncio
+    async def test_send_order_buy_live_uses_tttc0012u(self, settings) -> None:
+        broker = self._make_broker(settings, "live")
+        mock_hash = AsyncMock()
+        mock_hash.status = 200
+        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
+        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
+        mock_hash.__aexit__ = AsyncMock(return_value=False)
+
+        mock_order = AsyncMock()
+        mock_order.status = 200
+        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
+        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
+        mock_order.__aexit__ = AsyncMock(return_value=False)
+
+        with patch(
+            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
+        ) as mock_post:
+            await broker.send_order("005930", "BUY", 1)
+
+        order_headers = mock_post.call_args_list[1][1].get("headers", {})
+        assert order_headers["tr_id"] == "TTTC0012U"
+
+    @pytest.mark.asyncio
+    async def test_send_order_sell_paper_uses_vttc0011u(self, settings) -> None:
+        broker = self._make_broker(settings, "paper")
+        mock_hash = AsyncMock()
+        mock_hash.status = 200
+        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
+        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
+        mock_hash.__aexit__ = AsyncMock(return_value=False)
+
+        mock_order = AsyncMock()
+        mock_order.status = 200
+        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
+        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
+        mock_order.__aexit__ = AsyncMock(return_value=False)
+
+        with patch(
+            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
+        ) as mock_post:
+            await broker.send_order("005930", "SELL", 1)
+
+        order_headers = mock_post.call_args_list[1][1].get("headers", {})
+        assert order_headers["tr_id"] == "VTTC0011U"
+
+    @pytest.mark.asyncio
+    async def test_send_order_sell_live_uses_tttc0011u(self, settings) -> None:
+        broker = self._make_broker(settings, "live")
+        mock_hash = AsyncMock()
+        mock_hash.status = 200
+        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
+        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
+        mock_hash.__aexit__ = AsyncMock(return_value=False)
+
+        mock_order = AsyncMock()
+        mock_order.status = 200
+        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
+        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
+        mock_order.__aexit__ = AsyncMock(return_value=False)
+
+        with patch(
+            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
+        ) as mock_post:
+            await broker.send_order("005930", "SELL", 1)
+
+        order_headers = mock_post.call_args_list[1][1].get("headers", {})
+        assert order_headers["tr_id"] == "TTTC0011U"

tests/test_context.py

@@ -10,6 +10,7 @@ import pytest
 from src.context.aggregator import ContextAggregator
 from src.context.layer import LAYER_CONFIG, ContextLayer
 from src.context.store import ContextStore
+from src.context.summarizer import ContextSummarizer
 from src.db import init_db, log_trade
 
 
@@ -370,3 +371,259 @@ class TestLayerMetadata:
 
         # L1 aggregates from L2
         assert LAYER_CONFIG[ContextLayer.L1_LEGACY].aggregation_source == ContextLayer.L2_ANNUAL
+
+
+# ---------------------------------------------------------------------------
+# ContextSummarizer tests
+# ---------------------------------------------------------------------------
+
+
+@pytest.fixture
+def summarizer(db_conn: sqlite3.Connection) -> ContextSummarizer:
+    """Provide a ContextSummarizer backed by an in-memory store."""
+    return ContextSummarizer(ContextStore(db_conn))
+
+
+class TestContextSummarizer:
+    """Test suite for ContextSummarizer."""
+
+    # ------------------------------------------------------------------
+    # summarize_numeric_values
+    # ------------------------------------------------------------------
+
+    def test_summarize_empty_values(self, summarizer: ContextSummarizer) -> None:
+        """Empty list must return SummaryStats with count=0 and no other fields."""
+        stats = summarizer.summarize_numeric_values([])
+        assert stats.count == 0
+        assert stats.mean is None
+        assert stats.min is None
+        assert stats.max is None
+
+    def test_summarize_single_value(self, summarizer: ContextSummarizer) -> None:
+        """Single-element list must return correct stats with std=0 and trend=flat."""
+        stats = summarizer.summarize_numeric_values([42.0])
+        assert stats.count == 1
+        assert stats.mean == 42.0
+        assert stats.std == 0.0
+        assert stats.trend == "flat"
+
+    def test_summarize_upward_trend(self, summarizer: ContextSummarizer) -> None:
+        """Increasing values must produce trend='up'."""
+        values = [1.0, 2.0, 3.0, 10.0, 20.0, 30.0]
+        stats = summarizer.summarize_numeric_values(values)
+        assert stats.trend == "up"
+
+    def test_summarize_downward_trend(self, summarizer: ContextSummarizer) -> None:
+        """Decreasing values must produce trend='down'."""
+        values = [30.0, 20.0, 10.0, 3.0, 2.0, 1.0]
+        stats = summarizer.summarize_numeric_values(values)
+        assert stats.trend == "down"
+
+    def test_summarize_flat_trend(self, summarizer: ContextSummarizer) -> None:
+        """Stable values must produce trend='flat'."""
+        values = [100.0, 100.1, 99.9, 100.0, 100.2, 99.8]
+        stats = summarizer.summarize_numeric_values(values)
+        assert stats.trend == "flat"
+
+    # ------------------------------------------------------------------
+    # summarize_layer
+    # ------------------------------------------------------------------
+
+    def test_summarize_layer_no_data(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """summarize_layer with no data must return the 'No data' sentinel."""
+        result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
+        assert result["count"] == 0
+        assert "No data" in result["summary"]
+
+    def test_summarize_layer_numeric(
+        self, summarizer: ContextSummarizer, db_conn: sqlite3.Connection
+    ) -> None:
+        """summarize_layer must collect numeric values and produce stats."""
+        store = summarizer.store
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "total_pnl", 100.0)
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-02", "total_pnl", 200.0)
+
+        result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
+        assert "total_entries" in result
+
+    def test_summarize_layer_with_dict_values(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """summarize_layer must handle dict values by extracting numeric subkeys."""
+        store = summarizer.store
+        # set_context serialises the value as JSON, so passing a dict works
+        store.set_context(
+            ContextLayer.L6_DAILY, "2026-02-01", "metrics",
+            {"win_rate": 65.0, "label": "good"}
+        )
+
+        result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
+        assert "total_entries" in result
+        # numeric subkey "win_rate" should appear as "metrics.win_rate"
+        assert "metrics.win_rate" in result
+
+    def test_summarize_layer_with_string_values(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """summarize_layer must count string values separately."""
+        store = summarizer.store
+        # set_context stores string values as JSON-encoded strings
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "outlook", "BULLISH")
+
+        result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
+        # String fields contribute a `<key>_count` entry
+        assert "outlook_count" in result
+
+    # ------------------------------------------------------------------
+    # rolling_window_summary
+    # ------------------------------------------------------------------
+
+    def test_rolling_window_summary_basic(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """rolling_window_summary must return the expected structure."""
+        store = summarizer.store
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "pnl", 500.0)
+
+        result = summarizer.rolling_window_summary(ContextLayer.L6_DAILY)
+        assert "window_days" in result
+        assert "recent_data" in result
+        assert "historical_summary" in result
+
+    def test_rolling_window_summary_no_older_data(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """rolling_window_summary with summarize_older=False skips history."""
+        result = summarizer.rolling_window_summary(
+            ContextLayer.L6_DAILY, summarize_older=False
+        )
+        assert result["historical_summary"] == {}
+
+    # ------------------------------------------------------------------
+    # aggregate_to_higher_layer
+    # ------------------------------------------------------------------
+
+    def test_aggregate_to_higher_layer_mean(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """aggregate_to_higher_layer with 'mean' via dict subkeys returns average."""
+        store = summarizer.store
+        # Use different outer keys but same inner metric key so get_all_contexts
+        # returns multiple rows with the target subkey.
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
+
+        result = summarizer.aggregate_to_higher_layer(
+            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "mean"
+        )
+        assert result == pytest.approx(150.0)
+
+    def test_aggregate_to_higher_layer_sum(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """aggregate_to_higher_layer with 'sum' must return the total."""
+        store = summarizer.store
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
+
+        result = summarizer.aggregate_to_higher_layer(
+            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "sum"
+        )
+        assert result == pytest.approx(300.0)
+
+    def test_aggregate_to_higher_layer_max(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """aggregate_to_higher_layer with 'max' must return the maximum."""
+        store = summarizer.store
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
+
+        result = summarizer.aggregate_to_higher_layer(
+            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "max"
+        )
+        assert result == pytest.approx(200.0)
+
+    def test_aggregate_to_higher_layer_min(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """aggregate_to_higher_layer with 'min' must return the minimum."""
+        store = summarizer.store
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
+
+        result = summarizer.aggregate_to_higher_layer(
+            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "min"
+        )
+        assert result == pytest.approx(100.0)
+
+    def test_aggregate_to_higher_layer_no_data(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """aggregate_to_higher_layer with no matching key must return None."""
+        result = summarizer.aggregate_to_higher_layer(
+            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "nonexistent", "mean"
+        )
+        assert result is None
+
+    def test_aggregate_to_higher_layer_unknown_func_defaults_to_mean(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """Unknown aggregation function must fall back to mean."""
+        store = summarizer.store
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
+
+        result = summarizer.aggregate_to_higher_layer(
+            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "unknown_func"
+        )
+        assert result == pytest.approx(150.0)
+
+    # ------------------------------------------------------------------
+    # create_compact_summary + format_summary_for_prompt
+    # ------------------------------------------------------------------
+
+    def test_create_compact_summary(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """create_compact_summary must produce a dict keyed by layer value."""
+        store = summarizer.store
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "pnl", 100.0)
+
+        result = summarizer.create_compact_summary([ContextLayer.L6_DAILY])
+        assert ContextLayer.L6_DAILY.value in result
+
+    def test_format_summary_for_prompt_with_numeric_metrics(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """format_summary_for_prompt must render avg/trend fields."""
+        store = summarizer.store
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "pnl", 100.0)
+        store.set_context(ContextLayer.L6_DAILY, "2026-02-02", "pnl", 200.0)
+
+        compact = summarizer.create_compact_summary([ContextLayer.L6_DAILY])
+        text = summarizer.format_summary_for_prompt(compact)
+        assert isinstance(text, str)
+
+    def test_format_summary_for_prompt_skips_empty_layers(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """format_summary_for_prompt must skip layers with no metrics."""
+        summary = {ContextLayer.L6_DAILY.value: {}}
+        text = summarizer.format_summary_for_prompt(summary)
+        assert text == ""
+
+    def test_format_summary_non_dict_value(
+        self, summarizer: ContextSummarizer
+    ) -> None:
+        """format_summary_for_prompt must render non-dict values as plain text."""
+        summary = {
+            "daily": {
+                "plain_count": 42,
+            }
+        }
+        text = summarizer.format_summary_for_prompt(summary)
+        assert "plain_count" in text
+        assert "42" in text

tests/test_dashboard.py

@@ -296,3 +296,120 @@ def test_scenarios_active_empty_when_no_matches(tmp_path: Path) -> None:
     get_active_scenarios = _endpoint(app, "/api/scenarios/active")
     body = get_active_scenarios(market="US", date_str="2026-02-14", limit=50)
     assert body["count"] == 0
+
+
+def test_pnl_history_all_markets(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_pnl_history = _endpoint(app, "/api/pnl/history")
+    body = get_pnl_history(days=30, market="all")
+    assert body["market"] == "all"
+    assert isinstance(body["labels"], list)
+    assert isinstance(body["pnl"], list)
+    assert len(body["labels"]) == len(body["pnl"])
+
+
+def test_pnl_history_market_filter(tmp_path: Path) -> None:
+    app = _app(tmp_path)
+    get_pnl_history = _endpoint(app, "/api/pnl/history")
+    body = get_pnl_history(days=30, market="KR")
+    assert body["market"] == "KR"
+    # KR has 1 trade with pnl=2.0
+    assert len(body["labels"]) >= 1
+    assert body["pnl"][0] == 2.0
+
+
+def test_positions_returns_open_buy(tmp_path: Path) -> None:
+    """BUY가 마지막 거래인 종목은 포지션으로 반환되어야 한다."""
+    app = _app(tmp_path)
+    get_positions = _endpoint(app, "/api/positions")
+    body = get_positions()
+    # seed_db: 005930은 BUY (오픈), AAPL은 SELL (마지막)
+    assert body["count"] == 1
+    pos = body["positions"][0]
+    assert pos["stock_code"] == "005930"
+    assert pos["market"] == "KR"
+    assert pos["quantity"] == 1
+    assert pos["entry_price"] == 70000
+
+
+def test_positions_excludes_closed_sell(tmp_path: Path) -> None:
+    """마지막 거래가 SELL인 종목은 포지션에 나타나지 않아야 한다."""
+    app = _app(tmp_path)
+    get_positions = _endpoint(app, "/api/positions")
+    body = get_positions()
+    codes = [p["stock_code"] for p in body["positions"]]
+    assert "AAPL" not in codes
+
+
+def test_positions_empty_when_no_trades(tmp_path: Path) -> None:
+    """거래 내역이 없으면 빈 포지션 목록을 반환해야 한다."""
+    db_path = tmp_path / "empty.db"
+    conn = init_db(str(db_path))
+    conn.close()
+    app = create_dashboard_app(str(db_path))
+    get_positions = _endpoint(app, "/api/positions")
+    body = get_positions()
+    assert body["count"] == 0
+    assert body["positions"] == []
+
+
+def _seed_cb_context(conn: sqlite3.Connection, pnl_pct: float, market: str = "KR") -> None:
+    import json as _json
+    conn.execute(
+        "INSERT OR REPLACE INTO system_metrics (key, value, updated_at) VALUES (?, ?, ?)",
+        (
+            f"portfolio_pnl_pct_{market}",
+            _json.dumps({"pnl_pct": pnl_pct}),
+            "2026-02-22T10:00:00+00:00",
+        ),
+    )
+    conn.commit()
+
+
+def test_status_circuit_breaker_ok(tmp_path: Path) -> None:
+    """pnl_pct가 -2.0%보다 높으면 status=ok를 반환해야 한다."""
+    db_path = tmp_path / "cb_ok.db"
+    conn = init_db(str(db_path))
+    _seed_cb_context(conn, -1.0)
+    conn.close()
+    app = create_dashboard_app(str(db_path))
+    get_status = _endpoint(app, "/api/status")
+    body = get_status()
+    cb = body["circuit_breaker"]
+    assert cb["status"] == "ok"
+    assert cb["current_pnl_pct"] == -1.0
+    assert cb["threshold_pct"] == -3.0
+
+
+def test_status_circuit_breaker_warning(tmp_path: Path) -> None:
+    """pnl_pct가 -2.0% 이하이면 status=warning을 반환해야 한다."""
+    db_path = tmp_path / "cb_warn.db"
+    conn = init_db(str(db_path))
+    _seed_cb_context(conn, -2.5)
+    conn.close()
+    app = create_dashboard_app(str(db_path))
+    get_status = _endpoint(app, "/api/status")
+    body = get_status()
+    assert body["circuit_breaker"]["status"] == "warning"
+
+
+def test_status_circuit_breaker_tripped(tmp_path: Path) -> None:
+    """pnl_pct가 임계값(-3.0%) 이하이면 status=tripped를 반환해야 한다."""
+    db_path = tmp_path / "cb_tripped.db"
+    conn = init_db(str(db_path))
+    _seed_cb_context(conn, -3.5)
+    conn.close()
+    app = create_dashboard_app(str(db_path))
+    get_status = _endpoint(app, "/api/status")
+    body = get_status()
+    assert body["circuit_breaker"]["status"] == "tripped"
+
+
+def test_status_circuit_breaker_unknown_when_no_data(tmp_path: Path) -> None:
+    """L7 context에 pnl_pct 데이터가 없으면 status=unknown을 반환해야 한다."""
+    app = _app(tmp_path)  # seed_db에는 portfolio_pnl_pct 없음
+    get_status = _endpoint(app, "/api/status")
+    body = get_status()
+    cb = body["circuit_breaker"]
+    assert cb["status"] == "unknown"
+    assert cb["current_pnl_pct"] is None

tests/test_db.py

@@ -1,5 +1,8 @@
 """Tests for database helper functions."""
 
+import tempfile
+import os
+
 from src.db import get_open_position, init_db, log_trade
 
 
@@ -58,3 +61,135 @@ def test_get_open_position_returns_none_when_latest_is_sell() -> None:
 def test_get_open_position_returns_none_when_no_trades() -> None:
     conn = init_db(":memory:")
     assert get_open_position(conn, "AAPL", "US_NASDAQ") is None
+
+
+# ---------------------------------------------------------------------------
+# WAL mode tests (issue #210)
+# ---------------------------------------------------------------------------
+
+
+def test_wal_mode_applied_to_file_db() -> None:
+    """File-based DB must use WAL journal mode for dashboard concurrent reads."""
+    with tempfile.NamedTemporaryFile(suffix=".db", delete=False) as f:
+        db_path = f.name
+    try:
+        conn = init_db(db_path)
+        cursor = conn.execute("PRAGMA journal_mode")
+        mode = cursor.fetchone()[0]
+        assert mode == "wal", f"Expected WAL mode, got {mode}"
+        conn.close()
+    finally:
+        os.unlink(db_path)
+        # Clean up WAL auxiliary files if they exist
+        for ext in ("-wal", "-shm"):
+            path = db_path + ext
+            if os.path.exists(path):
+                os.unlink(path)
+
+
+def test_wal_mode_not_applied_to_memory_db() -> None:
+    """:memory: DB must not apply WAL (SQLite does not support WAL for in-memory)."""
+    conn = init_db(":memory:")
+    cursor = conn.execute("PRAGMA journal_mode")
+    mode = cursor.fetchone()[0]
+    # In-memory DBs default to 'memory' journal mode
+    assert mode != "wal", "WAL should not be set on in-memory database"
+    conn.close()
+
+
+# ---------------------------------------------------------------------------
+# mode column tests (issue #212)
+# ---------------------------------------------------------------------------
+
+
+def test_log_trade_stores_mode_paper() -> None:
+    """log_trade must persist mode='paper' in the trades table."""
+    conn = init_db(":memory:")
+    log_trade(
+        conn=conn,
+        stock_code="005930",
+        action="BUY",
+        confidence=85,
+        rationale="test",
+        mode="paper",
+    )
+    row = conn.execute("SELECT mode FROM trades ORDER BY id DESC LIMIT 1").fetchone()
+    assert row is not None
+    assert row[0] == "paper"
+
+
+def test_log_trade_stores_mode_live() -> None:
+    """log_trade must persist mode='live' in the trades table."""
+    conn = init_db(":memory:")
+    log_trade(
+        conn=conn,
+        stock_code="005930",
+        action="BUY",
+        confidence=85,
+        rationale="test",
+        mode="live",
+    )
+    row = conn.execute("SELECT mode FROM trades ORDER BY id DESC LIMIT 1").fetchone()
+    assert row is not None
+    assert row[0] == "live"
+
+
+def test_log_trade_default_mode_is_paper() -> None:
+    """log_trade without explicit mode must default to 'paper'."""
+    conn = init_db(":memory:")
+    log_trade(
+        conn=conn,
+        stock_code="005930",
+        action="HOLD",
+        confidence=50,
+        rationale="test",
+    )
+    row = conn.execute("SELECT mode FROM trades ORDER BY id DESC LIMIT 1").fetchone()
+    assert row is not None
+    assert row[0] == "paper"
+
+
+def test_mode_column_exists_in_schema() -> None:
+    """trades table must have a mode column after init_db."""
+    conn = init_db(":memory:")
+    cursor = conn.execute("PRAGMA table_info(trades)")
+    columns = {row[1] for row in cursor.fetchall()}
+    assert "mode" in columns
+
+
+def test_mode_migration_adds_column_to_existing_db() -> None:
+    """init_db must add mode column to existing DBs that lack it (migration)."""
+    import sqlite3
+
+    with tempfile.NamedTemporaryFile(suffix=".db", delete=False) as f:
+        db_path = f.name
+    try:
+        # Create DB without mode column (simulate old schema)
+        old_conn = sqlite3.connect(db_path)
+        old_conn.execute(
+            """CREATE TABLE trades (
+                id INTEGER PRIMARY KEY AUTOINCREMENT,
+                timestamp TEXT NOT NULL,
+                stock_code TEXT NOT NULL,
+                action TEXT NOT NULL,
+                confidence INTEGER NOT NULL,
+                rationale TEXT,
+                quantity INTEGER,
+                price REAL,
+                pnl REAL DEFAULT 0.0,
+                market TEXT DEFAULT 'KR',
+                exchange_code TEXT DEFAULT 'KRX',
+                decision_id TEXT
+            )"""
+        )
+        old_conn.commit()
+        old_conn.close()
+
+        # Run init_db — should add mode column via migration
+        conn = init_db(db_path)
+        cursor = conn.execute("PRAGMA table_info(trades)")
+        columns = {row[1] for row in cursor.fetchall()}
+        assert "mode" in columns
+        conn.close()
+    finally:
+        os.unlink(db_path)

tests/test_logging_config.py

@@ -0,0 +1,117 @@
+"""Tests for JSON structured logging configuration."""
+
+from __future__ import annotations
+
+import json
+import logging
+import sys
+
+from src.logging_config import JSONFormatter, setup_logging
+
+
+class TestJSONFormatter:
+    """Test JSONFormatter output."""
+
+    def test_basic_log_record(self) -> None:
+        """JSONFormatter must emit valid JSON with required fields."""
+        formatter = JSONFormatter()
+        record = logging.LogRecord(
+            name="test.logger",
+            level=logging.INFO,
+            pathname="",
+            lineno=0,
+            msg="Hello %s",
+            args=("world",),
+            exc_info=None,
+        )
+        output = formatter.format(record)
+        data = json.loads(output)
+        assert data["level"] == "INFO"
+        assert data["logger"] == "test.logger"
+        assert data["message"] == "Hello world"
+        assert "timestamp" in data
+
+    def test_includes_exception_info(self) -> None:
+        """JSONFormatter must include exception info when present."""
+        formatter = JSONFormatter()
+        try:
+            raise ValueError("test error")
+        except ValueError:
+            exc_info = sys.exc_info()
+        record = logging.LogRecord(
+            name="test",
+            level=logging.ERROR,
+            pathname="",
+            lineno=0,
+            msg="oops",
+            args=(),
+            exc_info=exc_info,
+        )
+        output = formatter.format(record)
+        data = json.loads(output)
+        assert "exception" in data
+        assert "ValueError" in data["exception"]
+
+    def test_extra_trading_fields_included(self) -> None:
+        """Extra trading fields attached to the record must appear in JSON."""
+        formatter = JSONFormatter()
+        record = logging.LogRecord(
+            name="test",
+            level=logging.INFO,
+            pathname="",
+            lineno=0,
+            msg="trade",
+            args=(),
+            exc_info=None,
+        )
+        record.stock_code = "005930"  # type: ignore[attr-defined]
+        record.action = "BUY"  # type: ignore[attr-defined]
+        record.confidence = 85  # type: ignore[attr-defined]
+        record.pnl_pct = -1.5  # type: ignore[attr-defined]
+        record.order_amount = 1_000_000  # type: ignore[attr-defined]
+        output = formatter.format(record)
+        data = json.loads(output)
+        assert data["stock_code"] == "005930"
+        assert data["action"] == "BUY"
+        assert data["confidence"] == 85
+        assert data["pnl_pct"] == -1.5
+        assert data["order_amount"] == 1_000_000
+
+    def test_none_extra_fields_excluded(self) -> None:
+        """Extra fields that are None must not appear in JSON output."""
+        formatter = JSONFormatter()
+        record = logging.LogRecord(
+            name="test",
+            level=logging.INFO,
+            pathname="",
+            lineno=0,
+            msg="no extras",
+            args=(),
+            exc_info=None,
+        )
+        output = formatter.format(record)
+        data = json.loads(output)
+        assert "stock_code" not in data
+        assert "action" not in data
+        assert "confidence" not in data
+
+
+class TestSetupLogging:
+    """Test setup_logging function."""
+
+    def test_configures_root_logger(self) -> None:
+        """setup_logging must attach a JSON handler to the root logger."""
+        setup_logging(level=logging.DEBUG)
+        root = logging.getLogger()
+        json_handlers = [
+            h for h in root.handlers if isinstance(h.formatter, JSONFormatter)
+        ]
+        assert len(json_handlers) == 1
+        assert root.level == logging.DEBUG
+
+    def test_avoids_duplicate_handlers(self) -> None:
+        """Calling setup_logging twice must not add duplicate handlers."""
+        setup_logging()
+        setup_logging()
+        root = logging.getLogger()
+        assert len(root.handlers) == 1

tests/test_overseas_broker.py

@@ -0,0 +1,815 @@
+"""Tests for OverseasBroker — rankings, price, balance, order, and helpers."""
+
+from __future__ import annotations
+
+from unittest.mock import AsyncMock, MagicMock
+
+import aiohttp
+import pytest
+
+from src.broker.kis_api import KISBroker
+from src.broker.overseas import OverseasBroker, _PRICE_EXCHANGE_MAP, _RANKING_EXCHANGE_MAP
+from src.config import Settings
+
+
+def _make_async_cm(mock_resp: AsyncMock) -> MagicMock:
+    """Create an async context manager that returns mock_resp on __aenter__."""
+    cm = MagicMock()
+    cm.__aenter__ = AsyncMock(return_value=mock_resp)
+    cm.__aexit__ = AsyncMock(return_value=False)
+    return cm
+
+
+@pytest.fixture
+def mock_settings() -> Settings:
+    """Provide mock settings with correct default TR_IDs/paths."""
+    return Settings(
+        KIS_APP_KEY="test_key",
+        KIS_APP_SECRET="test_secret",
+        KIS_ACCOUNT_NO="12345678-01",
+        GEMINI_API_KEY="test_gemini_key",
+    )
+
+
+@pytest.fixture
+def mock_broker(mock_settings: Settings) -> KISBroker:
+    """Provide a mock KIS broker."""
+    broker = KISBroker(mock_settings)
+    broker.get_orderbook = AsyncMock()  # type: ignore[method-assign]
+    return broker
+
+
+@pytest.fixture
+def overseas_broker(mock_broker: KISBroker) -> OverseasBroker:
+    """Provide an OverseasBroker wrapping a mock KISBroker."""
+    return OverseasBroker(mock_broker)
+
+
+def _setup_broker_mocks(overseas_broker: OverseasBroker, mock_session: MagicMock) -> None:
+    """Wire up common broker mocks."""
+    overseas_broker._broker._rate_limiter.acquire = AsyncMock()
+    overseas_broker._broker._get_session = MagicMock(return_value=mock_session)
+    overseas_broker._broker._auth_headers = AsyncMock(return_value={})
+
+
+class TestRankingExchangeMap:
+    """Test exchange code mapping for ranking API."""
+
+    def test_nasd_maps_to_nas(self) -> None:
+        assert _RANKING_EXCHANGE_MAP["NASD"] == "NAS"
+
+    def test_nyse_maps_to_nys(self) -> None:
+        assert _RANKING_EXCHANGE_MAP["NYSE"] == "NYS"
+
+    def test_amex_maps_to_ams(self) -> None:
+        assert _RANKING_EXCHANGE_MAP["AMEX"] == "AMS"
+
+    def test_sehk_maps_to_hks(self) -> None:
+        assert _RANKING_EXCHANGE_MAP["SEHK"] == "HKS"
+
+    def test_unmapped_exchange_passes_through(self) -> None:
+        assert _RANKING_EXCHANGE_MAP.get("UNKNOWN", "UNKNOWN") == "UNKNOWN"
+
+    def test_tse_unchanged(self) -> None:
+        assert _RANKING_EXCHANGE_MAP["TSE"] == "TSE"
+
+
+class TestConfigDefaults:
+    """Test that config defaults match KIS official API specs."""
+
+    def test_fluct_tr_id(self, mock_settings: Settings) -> None:
+        assert mock_settings.OVERSEAS_RANKING_FLUCT_TR_ID == "HHDFS76290000"
+
+    def test_volume_tr_id(self, mock_settings: Settings) -> None:
+        assert mock_settings.OVERSEAS_RANKING_VOLUME_TR_ID == "HHDFS76270000"
+
+    def test_fluct_path(self, mock_settings: Settings) -> None:
+        assert mock_settings.OVERSEAS_RANKING_FLUCT_PATH == "/uapi/overseas-stock/v1/ranking/updown-rate"
+
+    def test_volume_path(self, mock_settings: Settings) -> None:
+        assert mock_settings.OVERSEAS_RANKING_VOLUME_PATH == "/uapi/overseas-stock/v1/ranking/volume-surge"
+
+
+class TestFetchOverseasRankings:
+    """Test fetch_overseas_rankings method."""
+
+    @pytest.mark.asyncio
+    async def test_fluctuation_uses_correct_params(
+        self, overseas_broker: OverseasBroker
+    ) -> None:
+        """Fluctuation ranking should use HHDFS76290000, updown-rate path, and correct params."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(
+            return_value={"output": [{"symb": "AAPL", "name": "Apple"}]}
+        )
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+        overseas_broker._broker._auth_headers = AsyncMock(
+            return_value={"authorization": "Bearer test"}
+        )
+
+        result = await overseas_broker.fetch_overseas_rankings("NASD", "fluctuation")
+
+        assert len(result) == 1
+        assert result[0]["symb"] == "AAPL"
+
+        call_args = mock_session.get.call_args
+        url = call_args[0][0]
+        params = call_args[1]["params"]
+
+        assert "/uapi/overseas-stock/v1/ranking/updown-rate" in url
+        assert params["EXCD"] == "NAS"
+        assert params["NDAY"] == "0"
+        assert params["GUBN"] == "1"
+        assert params["VOL_RANG"] == "0"
+
+        overseas_broker._broker._auth_headers.assert_called_with("HHDFS76290000")
+
+    @pytest.mark.asyncio
+    async def test_volume_uses_correct_params(
+        self, overseas_broker: OverseasBroker
+    ) -> None:
+        """Volume ranking should use HHDFS76270000, volume-surge path, and correct params."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(
+            return_value={"output": [{"symb": "TSLA", "name": "Tesla"}]}
+        )
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+        overseas_broker._broker._auth_headers = AsyncMock(
+            return_value={"authorization": "Bearer test"}
+        )
+
+        result = await overseas_broker.fetch_overseas_rankings("NYSE", "volume")
+
+        assert len(result) == 1
+
+        call_args = mock_session.get.call_args
+        url = call_args[0][0]
+        params = call_args[1]["params"]
+
+        assert "/uapi/overseas-stock/v1/ranking/volume-surge" in url
+        assert params["EXCD"] == "NYS"
+        assert params["MIXN"] == "0"
+        assert params["VOL_RANG"] == "0"
+        assert "NDAY" not in params
+        assert "GUBN" not in params
+
+        overseas_broker._broker._auth_headers.assert_called_with("HHDFS76270000")
+
+    @pytest.mark.asyncio
+    async def test_404_returns_empty_list(
+        self, overseas_broker: OverseasBroker
+    ) -> None:
+        """HTTP 404 should return empty list (fallback) instead of raising."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 404
+        mock_resp.text = AsyncMock(return_value="Not Found")
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+
+        result = await overseas_broker.fetch_overseas_rankings("AMEX", "fluctuation")
+        assert result == []
+
+    @pytest.mark.asyncio
+    async def test_non_404_error_raises(
+        self, overseas_broker: OverseasBroker
+    ) -> None:
+        """Non-404 HTTP errors should raise ConnectionError."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 500
+        mock_resp.text = AsyncMock(return_value="Internal Server Error")
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+
+        with pytest.raises(ConnectionError, match="500"):
+            await overseas_broker.fetch_overseas_rankings("NASD")
+
+    @pytest.mark.asyncio
+    async def test_empty_response_returns_empty(
+        self, overseas_broker: OverseasBroker
+    ) -> None:
+        """Empty output in response should return empty list."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"output": []})
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+
+        result = await overseas_broker.fetch_overseas_rankings("NASD")
+        assert result == []
+
+    @pytest.mark.asyncio
+    async def test_ranking_disabled_returns_empty(
+        self, overseas_broker: OverseasBroker
+    ) -> None:
+        """When OVERSEAS_RANKING_ENABLED=False, should return empty immediately."""
+        overseas_broker._broker._settings.OVERSEAS_RANKING_ENABLED = False
+        result = await overseas_broker.fetch_overseas_rankings("NASD")
+        assert result == []
+
+    @pytest.mark.asyncio
+    async def test_limit_truncates_results(
+        self, overseas_broker: OverseasBroker
+    ) -> None:
+        """Results should be truncated to the specified limit."""
+        rows = [{"symb": f"SYM{i}"} for i in range(20)]
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"output": rows})
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+
+        result = await overseas_broker.fetch_overseas_rankings("NASD", limit=5)
+        assert len(result) == 5
+
+    @pytest.mark.asyncio
+    async def test_network_error_raises(
+        self, overseas_broker: OverseasBroker
+    ) -> None:
+        """Network errors should raise ConnectionError."""
+        cm = MagicMock()
+        cm.__aenter__ = AsyncMock(side_effect=aiohttp.ClientError("timeout"))
+        cm.__aexit__ = AsyncMock(return_value=False)
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=cm)
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+
+        with pytest.raises(ConnectionError, match="Network error"):
+            await overseas_broker.fetch_overseas_rankings("NASD")
+
+    @pytest.mark.asyncio
+    async def test_exchange_code_mapping_applied(
+        self, overseas_broker: OverseasBroker
+    ) -> None:
+        """All major exchanges should use mapped codes in API params."""
+        for original, mapped in [("NASD", "NAS"), ("NYSE", "NYS"), ("AMEX", "AMS")]:
+            mock_resp = AsyncMock()
+            mock_resp.status = 200
+            mock_resp.json = AsyncMock(return_value={"output": [{"symb": "X"}]})
+
+            mock_session = MagicMock()
+            mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
+
+            _setup_broker_mocks(overseas_broker, mock_session)
+
+            await overseas_broker.fetch_overseas_rankings(original)
+
+            call_params = mock_session.get.call_args[1]["params"]
+            assert call_params["EXCD"] == mapped, f"{original} should map to {mapped}"
+
+
+class TestGetOverseasPrice:
+    """Test get_overseas_price method."""
+
+    @pytest.mark.asyncio
+    async def test_success(self, overseas_broker: OverseasBroker) -> None:
+        """Successful price fetch returns JSON data."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"output": {"last": "150.00"}})
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+        overseas_broker._broker._auth_headers = AsyncMock(return_value={"authorization": "Bearer t"})
+
+        result = await overseas_broker.get_overseas_price("NASD", "AAPL")
+        assert result["output"]["last"] == "150.00"
+
+        call_args = mock_session.get.call_args
+        params = call_args[1]["params"]
+        assert params["EXCD"] == "NAS"  # NASD → NAS via _PRICE_EXCHANGE_MAP
+        assert params["SYMB"] == "AAPL"
+
+    @pytest.mark.asyncio
+    async def test_http_error_raises(self, overseas_broker: OverseasBroker) -> None:
+        """Non-200 response should raise ConnectionError."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 400
+        mock_resp.text = AsyncMock(return_value="Bad Request")
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+
+        with pytest.raises(ConnectionError, match="get_overseas_price failed"):
+            await overseas_broker.get_overseas_price("NASD", "AAPL")
+
+    @pytest.mark.asyncio
+    async def test_network_error_raises(self, overseas_broker: OverseasBroker) -> None:
+        """Network error should raise ConnectionError."""
+        cm = MagicMock()
+        cm.__aenter__ = AsyncMock(side_effect=aiohttp.ClientError("conn refused"))
+        cm.__aexit__ = AsyncMock(return_value=False)
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=cm)
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+
+        with pytest.raises(ConnectionError, match="Network error"):
+            await overseas_broker.get_overseas_price("NASD", "AAPL")
+
+
+class TestGetOverseasBalance:
+    """Test get_overseas_balance method."""
+
+    @pytest.mark.asyncio
+    async def test_success(self, overseas_broker: OverseasBroker) -> None:
+        """Successful balance fetch returns JSON data."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"output1": [{"pdno": "AAPL"}]})
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+
+        result = await overseas_broker.get_overseas_balance("NASD")
+        assert result["output1"][0]["pdno"] == "AAPL"
+
+    @pytest.mark.asyncio
+    async def test_http_error_raises(self, overseas_broker: OverseasBroker) -> None:
+        """Non-200 should raise ConnectionError."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 500
+        mock_resp.text = AsyncMock(return_value="Server Error")
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+
+        with pytest.raises(ConnectionError, match="get_overseas_balance failed"):
+            await overseas_broker.get_overseas_balance("NASD")
+
+    @pytest.mark.asyncio
+    async def test_network_error_raises(self, overseas_broker: OverseasBroker) -> None:
+        """Network error should raise ConnectionError."""
+        cm = MagicMock()
+        cm.__aenter__ = AsyncMock(side_effect=TimeoutError("timeout"))
+        cm.__aexit__ = AsyncMock(return_value=False)
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=cm)
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+
+        with pytest.raises(ConnectionError, match="Network error"):
+            await overseas_broker.get_overseas_balance("NYSE")
+
+
+class TestSendOverseasOrder:
+    """Test send_overseas_order method."""
+
+    @pytest.mark.asyncio
+    async def test_buy_market_order(self, overseas_broker: OverseasBroker) -> None:
+        """Market buy order should use VTTT1002U and ORD_DVSN=01."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"rt_cd": "0"})
+
+        mock_session = MagicMock()
+        mock_session.post = MagicMock(return_value=_make_async_cm(mock_resp))
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+        overseas_broker._broker._get_hash_key = AsyncMock(return_value="hashval")
+
+        result = await overseas_broker.send_overseas_order("NASD", "AAPL", "BUY", 10)
+        assert result["rt_cd"] == "0"
+
+        # Verify BUY TR_ID
+        overseas_broker._broker._auth_headers.assert_called_with("VTTT1002U")
+
+        call_args = mock_session.post.call_args
+        body = call_args[1]["json"]
+        assert body["ORD_DVSN"] == "01"  # market order
+        assert body["OVRS_ORD_UNPR"] == "0"
+
+    @pytest.mark.asyncio
+    async def test_sell_limit_order(self, overseas_broker: OverseasBroker) -> None:
+        """Limit sell order should use VTTT1001U and ORD_DVSN=00."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"rt_cd": "0"})
+
+        mock_session = MagicMock()
+        mock_session.post = MagicMock(return_value=_make_async_cm(mock_resp))
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+        overseas_broker._broker._get_hash_key = AsyncMock(return_value="hashval")
+
+        result = await overseas_broker.send_overseas_order("NYSE", "MSFT", "SELL", 5, price=350.0)
+        assert result["rt_cd"] == "0"
+
+        overseas_broker._broker._auth_headers.assert_called_with("VTTT1001U")
+
+        call_args = mock_session.post.call_args
+        body = call_args[1]["json"]
+        assert body["ORD_DVSN"] == "00"  # limit order
+        assert body["OVRS_ORD_UNPR"] == "350.0"
+
+    @pytest.mark.asyncio
+    async def test_order_http_error_raises(self, overseas_broker: OverseasBroker) -> None:
+        """Non-200 should raise ConnectionError."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 400
+        mock_resp.text = AsyncMock(return_value="Bad Request")
+
+        mock_session = MagicMock()
+        mock_session.post = MagicMock(return_value=_make_async_cm(mock_resp))
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+        overseas_broker._broker._get_hash_key = AsyncMock(return_value="hashval")
+
+        with pytest.raises(ConnectionError, match="send_overseas_order failed"):
+            await overseas_broker.send_overseas_order("NASD", "AAPL", "BUY", 1)
+
+    @pytest.mark.asyncio
+    async def test_order_network_error_raises(self, overseas_broker: OverseasBroker) -> None:
+        """Network error should raise ConnectionError."""
+        cm = MagicMock()
+        cm.__aenter__ = AsyncMock(side_effect=aiohttp.ClientError("conn reset"))
+        cm.__aexit__ = AsyncMock(return_value=False)
+
+        mock_session = MagicMock()
+        mock_session.post = MagicMock(return_value=cm)
+
+        _setup_broker_mocks(overseas_broker, mock_session)
+        overseas_broker._broker._get_hash_key = AsyncMock(return_value="hashval")
+
+        with pytest.raises(ConnectionError, match="Network error"):
+            await overseas_broker.send_overseas_order("NASD", "TSLA", "SELL", 2)
+
+
+class TestGetCurrencyCode:
+    """Test _get_currency_code mapping."""
+
+    def test_us_exchanges(self, overseas_broker: OverseasBroker) -> None:
+        assert overseas_broker._get_currency_code("NASD") == "USD"
+        assert overseas_broker._get_currency_code("NYSE") == "USD"
+        assert overseas_broker._get_currency_code("AMEX") == "USD"
+
+    def test_japan(self, overseas_broker: OverseasBroker) -> None:
+        assert overseas_broker._get_currency_code("TSE") == "JPY"
+
+    def test_hong_kong(self, overseas_broker: OverseasBroker) -> None:
+        assert overseas_broker._get_currency_code("SEHK") == "HKD"
+
+    def test_china(self, overseas_broker: OverseasBroker) -> None:
+        assert overseas_broker._get_currency_code("SHAA") == "CNY"
+        assert overseas_broker._get_currency_code("SZAA") == "CNY"
+
+    def test_vietnam(self, overseas_broker: OverseasBroker) -> None:
+        assert overseas_broker._get_currency_code("HNX") == "VND"
+        assert overseas_broker._get_currency_code("HSX") == "VND"
+
+    def test_unknown_defaults_usd(self, overseas_broker: OverseasBroker) -> None:
+        assert overseas_broker._get_currency_code("UNKNOWN") == "USD"
+
+
+class TestExtractRankingRows:
+    """Test _extract_ranking_rows helper."""
+
+    def test_output_key(self, overseas_broker: OverseasBroker) -> None:
+        data = {"output": [{"a": 1}, {"b": 2}]}
+        assert overseas_broker._extract_ranking_rows(data) == [{"a": 1}, {"b": 2}]
+
+    def test_output1_key(self, overseas_broker: OverseasBroker) -> None:
+        data = {"output1": [{"c": 3}]}
+        assert overseas_broker._extract_ranking_rows(data) == [{"c": 3}]
+
+    def test_output2_key(self, overseas_broker: OverseasBroker) -> None:
+        data = {"output2": [{"d": 4}]}
+        assert overseas_broker._extract_ranking_rows(data) == [{"d": 4}]
+
+    def test_no_list_returns_empty(self, overseas_broker: OverseasBroker) -> None:
+        data = {"output": "not a list"}
+        assert overseas_broker._extract_ranking_rows(data) == []
+
+    def test_empty_data(self, overseas_broker: OverseasBroker) -> None:
+        assert overseas_broker._extract_ranking_rows({}) == []
+
+    def test_filters_non_dict_rows(self, overseas_broker: OverseasBroker) -> None:
+        data = {"output": [{"a": 1}, "invalid", {"b": 2}]}
+        assert overseas_broker._extract_ranking_rows(data) == [{"a": 1}, {"b": 2}]
+
+
+class TestPriceExchangeMap:
+    """Test _PRICE_EXCHANGE_MAP is applied in get_overseas_price (issue #151)."""
+
+    def test_price_map_equals_ranking_map(self) -> None:
+        assert _PRICE_EXCHANGE_MAP is _RANKING_EXCHANGE_MAP
+
+    @pytest.mark.parametrize("original,expected", [
+        ("NASD", "NAS"),
+        ("NYSE", "NYS"),
+        ("AMEX", "AMS"),
+    ])
+    def test_us_exchange_code_mapping(self, original: str, expected: str) -> None:
+        assert _PRICE_EXCHANGE_MAP[original] == expected
+
+    @pytest.mark.asyncio
+    async def test_get_overseas_price_sends_mapped_code(
+        self, overseas_broker: OverseasBroker
+    ) -> None:
+        """NASD → NAS must be sent to HHDFS00000300."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"output": {"last": "200.00"}})
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
+        _setup_broker_mocks(overseas_broker, mock_session)
+
+        await overseas_broker.get_overseas_price("NASD", "AAPL")
+
+        params = mock_session.get.call_args[1]["params"]
+        assert params["EXCD"] == "NAS"
+
+
+class TestOrderRtCdCheck:
+    """Test that send_overseas_order checks rt_cd and logs accordingly (issue #151)."""
+
+    @pytest.fixture
+    def overseas_broker(self, mock_settings: Settings) -> OverseasBroker:
+        broker = MagicMock(spec=KISBroker)
+        broker._settings = mock_settings
+        broker._account_no = "12345678"
+        broker._product_cd = "01"
+        broker._base_url = "https://openapivts.koreainvestment.com:9443"
+        broker._rate_limiter = AsyncMock()
+        broker._rate_limiter.acquire = AsyncMock()
+        broker._auth_headers = AsyncMock(return_value={"authorization": "Bearer t"})
+        broker._get_hash_key = AsyncMock(return_value="hashval")
+        return OverseasBroker(broker)
+
+    @pytest.mark.asyncio
+    async def test_success_rt_cd_returns_data(
+        self, overseas_broker: OverseasBroker
+    ) -> None:
+        """rt_cd='0' → order accepted, data returned."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"rt_cd": "0", "msg1": "완료"})
+
+        mock_session = MagicMock()
+        mock_session.post = MagicMock(return_value=_make_async_cm(mock_resp))
+        overseas_broker._broker._get_session = MagicMock(return_value=mock_session)
+
+        result = await overseas_broker.send_overseas_order("NASD", "AAPL", "BUY", 10, price=150.0)
+        assert result["rt_cd"] == "0"
+
+    @pytest.mark.asyncio
+    async def test_error_rt_cd_returns_data_with_msg(
+        self, overseas_broker: OverseasBroker
+    ) -> None:
+        """rt_cd != '0' → order rejected, data still returned (caller checks rt_cd)."""
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(
+            return_value={"rt_cd": "1", "msg1": "주문가능금액이 부족합니다."}
+        )
+
+        mock_session = MagicMock()
+        mock_session.post = MagicMock(return_value=_make_async_cm(mock_resp))
+        overseas_broker._broker._get_session = MagicMock(return_value=mock_session)
+
+        result = await overseas_broker.send_overseas_order("NASD", "AAPL", "BUY", 10, price=150.0)
+        assert result["rt_cd"] == "1"
+        assert "부족" in result["msg1"]
+
+
+class TestPaperOverseasCash:
+    """Test PAPER_OVERSEAS_CASH config setting (issue #151)."""
+
+    def test_default_value(self) -> None:
+        settings = Settings(
+            KIS_APP_KEY="k",
+            KIS_APP_SECRET="s",
+            KIS_ACCOUNT_NO="12345678-01",
+            GEMINI_API_KEY="g",
+        )
+        assert settings.PAPER_OVERSEAS_CASH == 50000.0
+
+    def test_env_override(self) -> None:
+        import os
+        os.environ["PAPER_OVERSEAS_CASH"] = "25000"
+        settings = Settings(
+            KIS_APP_KEY="k",
+            KIS_APP_SECRET="s",
+            KIS_ACCOUNT_NO="12345678-01",
+            GEMINI_API_KEY="g",
+        )
+        assert settings.PAPER_OVERSEAS_CASH == 25000.0
+        del os.environ["PAPER_OVERSEAS_CASH"]
+
+    def test_zero_disables_fallback(self) -> None:
+        import os
+        os.environ["PAPER_OVERSEAS_CASH"] = "0"
+        settings = Settings(
+            KIS_APP_KEY="k",
+            KIS_APP_SECRET="s",
+            KIS_ACCOUNT_NO="12345678-01",
+            GEMINI_API_KEY="g",
+        )
+        assert settings.PAPER_OVERSEAS_CASH == 0.0
+
+
+# ---------------------------------------------------------------------------
+# TR_ID live/paper branching — overseas (issues #201, #203)
+# ---------------------------------------------------------------------------
+
+
+def _make_overseas_broker_with_mode(mode: str) -> OverseasBroker:
+    s = Settings(
+        KIS_APP_KEY="k",
+        KIS_APP_SECRET="s",
+        KIS_ACCOUNT_NO="12345678-01",
+        GEMINI_API_KEY="g",
+        DB_PATH=":memory:",
+        MODE=mode,
+    )
+    kis = KISBroker(s)
+    kis._access_token = "tok"
+    kis._token_expires_at = float("inf")
+    kis._rate_limiter.acquire = AsyncMock()
+    return OverseasBroker(kis)
+
+
+class TestOverseasTRIDBranching:
+    """get_overseas_balance and send_overseas_order must use correct TR_ID."""
+
+    @pytest.mark.asyncio
+    async def test_get_overseas_balance_paper_uses_vtts3012r(self) -> None:
+        broker = _make_overseas_broker_with_mode("paper")
+        captured: list[str] = []
+
+        async def mock_auth_headers(tr_id: str) -> dict:
+            captured.append(tr_id)
+            return {"tr_id": tr_id, "authorization": "Bearer tok"}
+
+        broker._broker._auth_headers = mock_auth_headers  # type: ignore[method-assign]
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"output1": [], "output2": []})
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=mock_resp)
+        broker._broker._get_session = MagicMock(return_value=mock_session)
+
+        await broker.get_overseas_balance("NASD")
+        assert "VTTS3012R" in captured
+
+    @pytest.mark.asyncio
+    async def test_get_overseas_balance_live_uses_ttts3012r(self) -> None:
+        broker = _make_overseas_broker_with_mode("live")
+        captured: list[str] = []
+
+        async def mock_auth_headers(tr_id: str) -> dict:
+            captured.append(tr_id)
+            return {"tr_id": tr_id, "authorization": "Bearer tok"}
+
+        broker._broker._auth_headers = mock_auth_headers  # type: ignore[method-assign]
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"output1": [], "output2": []})
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        mock_session = MagicMock()
+        mock_session.get = MagicMock(return_value=mock_resp)
+        broker._broker._get_session = MagicMock(return_value=mock_session)
+
+        await broker.get_overseas_balance("NASD")
+        assert "TTTS3012R" in captured
+
+    @pytest.mark.asyncio
+    async def test_send_overseas_order_buy_paper_uses_vttt1002u(self) -> None:
+        broker = _make_overseas_broker_with_mode("paper")
+        captured: list[str] = []
+
+        async def mock_auth_headers(tr_id: str) -> dict:
+            captured.append(tr_id)
+            return {"tr_id": tr_id, "authorization": "Bearer tok"}
+
+        broker._broker._auth_headers = mock_auth_headers  # type: ignore[method-assign]
+        broker._broker._get_hash_key = AsyncMock(return_value="h")  # type: ignore[method-assign]
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"rt_cd": "0", "msg1": "OK"})
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        mock_session = MagicMock()
+        mock_session.post = MagicMock(return_value=mock_resp)
+        broker._broker._get_session = MagicMock(return_value=mock_session)
+
+        await broker.send_overseas_order("NASD", "AAPL", "BUY", 1)
+        assert "VTTT1002U" in captured
+
+    @pytest.mark.asyncio
+    async def test_send_overseas_order_buy_live_uses_tttt1002u(self) -> None:
+        broker = _make_overseas_broker_with_mode("live")
+        captured: list[str] = []
+
+        async def mock_auth_headers(tr_id: str) -> dict:
+            captured.append(tr_id)
+            return {"tr_id": tr_id, "authorization": "Bearer tok"}
+
+        broker._broker._auth_headers = mock_auth_headers  # type: ignore[method-assign]
+        broker._broker._get_hash_key = AsyncMock(return_value="h")  # type: ignore[method-assign]
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"rt_cd": "0", "msg1": "OK"})
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        mock_session = MagicMock()
+        mock_session.post = MagicMock(return_value=mock_resp)
+        broker._broker._get_session = MagicMock(return_value=mock_session)
+
+        await broker.send_overseas_order("NASD", "AAPL", "BUY", 1)
+        assert "TTTT1002U" in captured
+
+    @pytest.mark.asyncio
+    async def test_send_overseas_order_sell_paper_uses_vttt1001u(self) -> None:
+        broker = _make_overseas_broker_with_mode("paper")
+        captured: list[str] = []
+
+        async def mock_auth_headers(tr_id: str) -> dict:
+            captured.append(tr_id)
+            return {"tr_id": tr_id, "authorization": "Bearer tok"}
+
+        broker._broker._auth_headers = mock_auth_headers  # type: ignore[method-assign]
+        broker._broker._get_hash_key = AsyncMock(return_value="h")  # type: ignore[method-assign]
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"rt_cd": "0", "msg1": "OK"})
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        mock_session = MagicMock()
+        mock_session.post = MagicMock(return_value=mock_resp)
+        broker._broker._get_session = MagicMock(return_value=mock_session)
+
+        await broker.send_overseas_order("NASD", "AAPL", "SELL", 1)
+        assert "VTTT1001U" in captured
+
+    @pytest.mark.asyncio
+    async def test_send_overseas_order_sell_live_uses_tttt1006u(self) -> None:
+        broker = _make_overseas_broker_with_mode("live")
+        captured: list[str] = []
+
+        async def mock_auth_headers(tr_id: str) -> dict:
+            captured.append(tr_id)
+            return {"tr_id": tr_id, "authorization": "Bearer tok"}
+
+        broker._broker._auth_headers = mock_auth_headers  # type: ignore[method-assign]
+        broker._broker._get_hash_key = AsyncMock(return_value="h")  # type: ignore[method-assign]
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.json = AsyncMock(return_value={"rt_cd": "0", "msg1": "OK"})
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        mock_session = MagicMock()
+        mock_session.post = MagicMock(return_value=mock_resp)
+        broker._broker._get_session = MagicMock(return_value=mock_session)
+
+        await broker.send_overseas_order("NASD", "AAPL", "SELL", 1)
+        assert "TTTT1006U" in captured

tests/test_pre_market_planner.py

@@ -164,18 +164,23 @@ class TestGeneratePlaybook:
         assert pb.market_outlook == MarketOutlook.NEUTRAL
 
     @pytest.mark.asyncio
-    async def test_gemini_failure_returns_defensive(self) -> None:
+    async def test_gemini_failure_returns_smart_fallback(self) -> None:
         planner = _make_planner()
         planner._gemini.decide = AsyncMock(side_effect=RuntimeError("API timeout"))
+        # oversold candidate (signal="oversold", rsi=28.5)
         candidates = [_candidate()]
 
         pb = await planner.generate_playbook("KR", candidates, today=date(2026, 2, 8))
 
         assert pb.default_action == ScenarioAction.HOLD
-        assert pb.market_outlook == MarketOutlook.NEUTRAL_TO_BEARISH
+        # Smart fallback uses NEUTRAL outlook (not NEUTRAL_TO_BEARISH)
+        assert pb.market_outlook == MarketOutlook.NEUTRAL
         assert pb.stock_count == 1
-        # Defensive playbook has stop-loss scenarios
+        # Oversold candidate → first scenario is BUY, second is SELL stop-loss
-        assert pb.stock_playbooks[0].scenarios[0].action == ScenarioAction.SELL
+        scenarios = pb.stock_playbooks[0].scenarios
+        assert scenarios[0].action == ScenarioAction.BUY
+        assert scenarios[0].condition.rsi_below == 30
+        assert scenarios[1].action == ScenarioAction.SELL
 
     @pytest.mark.asyncio
     async def test_gemini_failure_empty_when_defensive_disabled(self) -> None:
@@ -657,3 +662,339 @@ class TestDefensivePlaybook:
         assert pb.stock_count == 0
         assert pb.market == "US"
         assert pb.market_outlook == MarketOutlook.NEUTRAL
+
+
+# ---------------------------------------------------------------------------
+# Smart fallback playbook
+# ---------------------------------------------------------------------------
+
+
+class TestSmartFallbackPlaybook:
+    """Tests for _smart_fallback_playbook — rule-based BUY/SELL on Gemini failure."""
+
+    def _make_settings(self) -> Settings:
+        return Settings(
+            KIS_APP_KEY="test",
+            KIS_APP_SECRET="test",
+            KIS_ACCOUNT_NO="12345678-01",
+            GEMINI_API_KEY="test",
+            RSI_OVERSOLD_THRESHOLD=30,
+            VOL_MULTIPLIER=2.0,
+        )
+
+    def test_momentum_candidate_gets_buy_on_volume(self) -> None:
+        candidates = [
+            _candidate(code="CHOW", signal="momentum", volume_ratio=13.64, rsi=100.0)
+        ]
+        settings = self._make_settings()
+
+        pb = PreMarketPlanner._smart_fallback_playbook(
+            date(2026, 2, 17), "US_AMEX", candidates, settings
+        )
+
+        assert pb.stock_count == 1
+        sp = pb.stock_playbooks[0]
+        assert sp.stock_code == "CHOW"
+        # First scenario: BUY with volume_ratio_above
+        buy_sc = sp.scenarios[0]
+        assert buy_sc.action == ScenarioAction.BUY
+        assert buy_sc.condition.volume_ratio_above == 2.0
+        assert buy_sc.condition.rsi_below is None
+        assert buy_sc.confidence == 80
+        # Second scenario: stop-loss SELL
+        sell_sc = sp.scenarios[1]
+        assert sell_sc.action == ScenarioAction.SELL
+        assert sell_sc.condition.price_change_pct_below == -3.0
+
+    def test_oversold_candidate_gets_buy_on_rsi(self) -> None:
+        candidates = [
+            _candidate(code="005930", signal="oversold", rsi=22.0, volume_ratio=3.5)
+        ]
+        settings = self._make_settings()
+
+        pb = PreMarketPlanner._smart_fallback_playbook(
+            date(2026, 2, 17), "KR", candidates, settings
+        )
+
+        sp = pb.stock_playbooks[0]
+        buy_sc = sp.scenarios[0]
+        assert buy_sc.action == ScenarioAction.BUY
+        assert buy_sc.condition.rsi_below == 30
+        assert buy_sc.condition.volume_ratio_above is None
+
+    def test_all_candidates_have_stop_loss_sell(self) -> None:
+        candidates = [
+            _candidate(code="AAA", signal="momentum", volume_ratio=5.0),
+            _candidate(code="BBB", signal="oversold", rsi=25.0),
+        ]
+        settings = self._make_settings()
+
+        pb = PreMarketPlanner._smart_fallback_playbook(
+            date(2026, 2, 17), "US_NASDAQ", candidates, settings
+        )
+
+        assert pb.stock_count == 2
+        for sp in pb.stock_playbooks:
+            sell_scenarios = [s for s in sp.scenarios if s.action == ScenarioAction.SELL]
+            assert len(sell_scenarios) == 1
+            assert sell_scenarios[0].condition.price_change_pct_below == -3.0
+            assert sell_scenarios[0].condition.price_change_pct_below == -3.0
+
+    def test_market_outlook_is_neutral(self) -> None:
+        candidates = [_candidate(signal="momentum", volume_ratio=5.0)]
+        settings = self._make_settings()
+
+        pb = PreMarketPlanner._smart_fallback_playbook(
+            date(2026, 2, 17), "US_AMEX", candidates, settings
+        )
+
+        assert pb.market_outlook == MarketOutlook.NEUTRAL
+
+    def test_default_action_is_hold(self) -> None:
+        candidates = [_candidate(signal="momentum", volume_ratio=5.0)]
+        settings = self._make_settings()
+
+        pb = PreMarketPlanner._smart_fallback_playbook(
+            date(2026, 2, 17), "US_AMEX", candidates, settings
+        )
+
+        assert pb.default_action == ScenarioAction.HOLD
+
+    def test_has_global_reduce_all_rule(self) -> None:
+        candidates = [_candidate(signal="momentum", volume_ratio=5.0)]
+        settings = self._make_settings()
+
+        pb = PreMarketPlanner._smart_fallback_playbook(
+            date(2026, 2, 17), "US_AMEX", candidates, settings
+        )
+
+        assert len(pb.global_rules) == 1
+        rule = pb.global_rules[0]
+        assert rule.action == ScenarioAction.REDUCE_ALL
+        assert "portfolio_pnl_pct" in rule.condition
+
+    def test_empty_candidates_returns_empty_playbook(self) -> None:
+        settings = self._make_settings()
+
+        pb = PreMarketPlanner._smart_fallback_playbook(
+            date(2026, 2, 17), "US_AMEX", [], settings
+        )
+
+        assert pb.stock_count == 0
+
+    def test_vol_multiplier_applied_from_settings(self) -> None:
+        """VOL_MULTIPLIER=3.0 should set volume_ratio_above=3.0 for momentum."""
+        candidates = [_candidate(signal="momentum", volume_ratio=5.0)]
+        settings = self._make_settings()
+        settings = settings.model_copy(update={"VOL_MULTIPLIER": 3.0})
+
+        pb = PreMarketPlanner._smart_fallback_playbook(
+            date(2026, 2, 17), "US_AMEX", candidates, settings
+        )
+
+        buy_sc = pb.stock_playbooks[0].scenarios[0]
+        assert buy_sc.condition.volume_ratio_above == 3.0
+
+    def test_rsi_oversold_threshold_applied_from_settings(self) -> None:
+        """RSI_OVERSOLD_THRESHOLD=25 should set rsi_below=25 for oversold."""
+        candidates = [_candidate(signal="oversold", rsi=22.0)]
+        settings = self._make_settings()
+        settings = settings.model_copy(update={"RSI_OVERSOLD_THRESHOLD": 25})
+
+        pb = PreMarketPlanner._smart_fallback_playbook(
+            date(2026, 2, 17), "KR", candidates, settings
+        )
+
+        buy_sc = pb.stock_playbooks[0].scenarios[0]
+        assert buy_sc.condition.rsi_below == 25
+
+    @pytest.mark.asyncio
+    async def test_generate_playbook_uses_smart_fallback_on_gemini_error(self) -> None:
+        """generate_playbook() should use smart fallback (not defensive) on API failure."""
+        planner = _make_planner()
+        planner._gemini.decide = AsyncMock(side_effect=ConnectionError("429 quota exceeded"))
+        # momentum candidate
+        candidates = [
+            _candidate(code="CHOW", signal="momentum", volume_ratio=13.64, rsi=100.0)
+        ]
+
+        pb = await planner.generate_playbook(
+            "US_AMEX", candidates, today=date(2026, 2, 18)
+        )
+
+        # Should NOT be all-SELL defensive; should have BUY for momentum
+        assert pb.stock_count == 1
+        buy_scenarios = [
+            s for s in pb.stock_playbooks[0].scenarios
+            if s.action == ScenarioAction.BUY
+        ]
+        assert len(buy_scenarios) == 1
+        assert buy_scenarios[0].condition.volume_ratio_above == 2.0  # VOL_MULTIPLIER default
+
+
+# ---------------------------------------------------------------------------
+# Holdings in prompt (#170)
+# ---------------------------------------------------------------------------
+
+
+class TestHoldingsInPrompt:
+    """Tests for current_holdings parameter in generate_playbook / _build_prompt."""
+
+    def _make_holdings(self) -> list[dict]:
+        return [
+            {
+                "stock_code": "005930",
+                "name": "Samsung",
+                "qty": 10,
+                "entry_price": 71000.0,
+                "unrealized_pnl_pct": 2.3,
+                "holding_days": 3,
+            }
+        ]
+
+    def test_build_prompt_includes_holdings_section(self) -> None:
+        """Prompt should contain a Current Holdings section when holdings are given."""
+        planner = _make_planner()
+        candidates = [_candidate()]
+        holdings = self._make_holdings()
+
+        prompt = planner._build_prompt(
+            "KR",
+            candidates,
+            context_data={},
+            self_market_scorecard=None,
+            cross_market=None,
+            current_holdings=holdings,
+        )
+
+        assert "## Current Holdings" in prompt
+        assert "005930" in prompt
+        assert "+2.30%" in prompt
+        assert "보유 3일" in prompt
+
+    def test_build_prompt_no_holdings_omits_section(self) -> None:
+        """Prompt should NOT contain a Current Holdings section when holdings=None."""
+        planner = _make_planner()
+        candidates = [_candidate()]
+
+        prompt = planner._build_prompt(
+            "KR",
+            candidates,
+            context_data={},
+            self_market_scorecard=None,
+            cross_market=None,
+            current_holdings=None,
+        )
+
+        assert "## Current Holdings" not in prompt
+
+    def test_build_prompt_empty_holdings_omits_section(self) -> None:
+        """Empty list should also omit the holdings section."""
+        planner = _make_planner()
+        candidates = [_candidate()]
+
+        prompt = planner._build_prompt(
+            "KR",
+            candidates,
+            context_data={},
+            self_market_scorecard=None,
+            cross_market=None,
+            current_holdings=[],
+        )
+
+        assert "## Current Holdings" not in prompt
+
+    def test_build_prompt_holdings_instruction_included(self) -> None:
+        """Prompt should include instruction to generate scenarios for held stocks."""
+        planner = _make_planner()
+        candidates = [_candidate()]
+        holdings = self._make_holdings()
+
+        prompt = planner._build_prompt(
+            "KR",
+            candidates,
+            context_data={},
+            self_market_scorecard=None,
+            cross_market=None,
+            current_holdings=holdings,
+        )
+
+        assert "005930" in prompt
+        assert "SELL/HOLD" in prompt
+
+    @pytest.mark.asyncio
+    async def test_generate_playbook_passes_holdings_to_prompt(self) -> None:
+        """generate_playbook should pass current_holdings through to the prompt."""
+        planner = _make_planner()
+        candidates = [_candidate()]
+        holdings = self._make_holdings()
+
+        # Capture the actual prompt sent to Gemini
+        captured_prompts: list[str] = []
+        original_decide = planner._gemini.decide
+
+        async def capture_and_call(data: dict) -> TradeDecision:
+            captured_prompts.append(data.get("prompt_override", ""))
+            return await original_decide(data)
+
+        planner._gemini.decide = capture_and_call  # type: ignore[method-assign]
+
+        await planner.generate_playbook(
+            "KR", candidates, today=date(2026, 2, 8), current_holdings=holdings
+        )
+
+        assert len(captured_prompts) == 1
+        assert "## Current Holdings" in captured_prompts[0]
+        assert "005930" in captured_prompts[0]
+
+    @pytest.mark.asyncio
+    async def test_holdings_stock_allowed_in_parse_response(self) -> None:
+        """Holdings stocks not in candidates list should be accepted in the response."""
+        holding_code = "000660"  # Not in candidates
+        stocks = [
+            {
+                "stock_code": "005930",  # candidate
+                "scenarios": [
+                    {
+                        "condition": {"rsi_below": 30},
+                        "action": "BUY",
+                        "confidence": 85,
+                        "rationale": "oversold",
+                    }
+                ],
+            },
+            {
+                "stock_code": holding_code,  # holding only
+                "scenarios": [
+                    {
+                        "condition": {"price_change_pct_below": -2.0},
+                        "action": "SELL",
+                        "confidence": 90,
+                        "rationale": "stop-loss",
+                    }
+                ],
+            },
+        ]
+        planner = _make_planner(gemini_response=_gemini_response_json(stocks=stocks))
+        candidates = [_candidate()]  # only 005930
+        holdings = [
+            {
+                "stock_code": holding_code,
+                "name": "SK Hynix",
+                "qty": 5,
+                "entry_price": 180000.0,
+                "unrealized_pnl_pct": -1.5,
+                "holding_days": 7,
+            }
+        ]
+
+        pb = await planner.generate_playbook(
+            "KR",
+            candidates,
+            today=date(2026, 2, 8),
+            current_holdings=holdings,
+        )
+
+        codes = [sp.stock_code for sp in pb.stock_playbooks]
+        assert "005930" in codes
+        assert holding_code in codes

tests/test_scenario_engine.py

@@ -440,3 +440,135 @@ class TestEvaluate:
         assert result.action == ScenarioAction.BUY
         assert result.match_details["rsi"] == 25.0
         assert isinstance(result.match_details["rsi"], float)
+
+
+# ---------------------------------------------------------------------------
+# Position-aware condition tests (#171)
+# ---------------------------------------------------------------------------
+
+
+class TestPositionAwareConditions:
+    """Tests for unrealized_pnl_pct and holding_days condition fields."""
+
+    def test_evaluate_condition_unrealized_pnl_above_matches(
+        self, engine: ScenarioEngine
+    ) -> None:
+        """unrealized_pnl_pct_above should match when P&L exceeds threshold."""
+        condition = StockCondition(unrealized_pnl_pct_above=3.0)
+        assert engine.evaluate_condition(condition, {"unrealized_pnl_pct": 5.0}) is True
+
+    def test_evaluate_condition_unrealized_pnl_above_no_match(
+        self, engine: ScenarioEngine
+    ) -> None:
+        """unrealized_pnl_pct_above should NOT match when P&L is below threshold."""
+        condition = StockCondition(unrealized_pnl_pct_above=3.0)
+        assert engine.evaluate_condition(condition, {"unrealized_pnl_pct": 2.0}) is False
+
+    def test_evaluate_condition_unrealized_pnl_below_matches(
+        self, engine: ScenarioEngine
+    ) -> None:
+        """unrealized_pnl_pct_below should match when P&L is under threshold."""
+        condition = StockCondition(unrealized_pnl_pct_below=-2.0)
+        assert engine.evaluate_condition(condition, {"unrealized_pnl_pct": -3.5}) is True
+
+    def test_evaluate_condition_unrealized_pnl_below_no_match(
+        self, engine: ScenarioEngine
+    ) -> None:
+        """unrealized_pnl_pct_below should NOT match when P&L is above threshold."""
+        condition = StockCondition(unrealized_pnl_pct_below=-2.0)
+        assert engine.evaluate_condition(condition, {"unrealized_pnl_pct": -1.0}) is False
+
+    def test_evaluate_condition_holding_days_above_matches(
+        self, engine: ScenarioEngine
+    ) -> None:
+        """holding_days_above should match when position held longer than threshold."""
+        condition = StockCondition(holding_days_above=5)
+        assert engine.evaluate_condition(condition, {"holding_days": 7}) is True
+
+    def test_evaluate_condition_holding_days_above_no_match(
+        self, engine: ScenarioEngine
+    ) -> None:
+        """holding_days_above should NOT match when position held shorter."""
+        condition = StockCondition(holding_days_above=5)
+        assert engine.evaluate_condition(condition, {"holding_days": 3}) is False
+
+    def test_evaluate_condition_holding_days_below_matches(
+        self, engine: ScenarioEngine
+    ) -> None:
+        """holding_days_below should match when position held fewer days."""
+        condition = StockCondition(holding_days_below=3)
+        assert engine.evaluate_condition(condition, {"holding_days": 1}) is True
+
+    def test_evaluate_condition_holding_days_below_no_match(
+        self, engine: ScenarioEngine
+    ) -> None:
+        """holding_days_below should NOT match when held more days."""
+        condition = StockCondition(holding_days_below=3)
+        assert engine.evaluate_condition(condition, {"holding_days": 5}) is False
+
+    def test_combined_pnl_and_holding_days(self, engine: ScenarioEngine) -> None:
+        """Combined position-aware conditions should AND-evaluate correctly."""
+        condition = StockCondition(
+            unrealized_pnl_pct_above=3.0,
+            holding_days_above=5,
+        )
+        # Both met → match
+        assert engine.evaluate_condition(
+            condition,
+            {"unrealized_pnl_pct": 4.5, "holding_days": 7},
+        ) is True
+        # Only pnl met → no match
+        assert engine.evaluate_condition(
+            condition,
+            {"unrealized_pnl_pct": 4.5, "holding_days": 3},
+        ) is False
+
+    def test_missing_unrealized_pnl_does_not_match(
+        self, engine: ScenarioEngine
+    ) -> None:
+        """Missing unrealized_pnl_pct key should not match the condition."""
+        condition = StockCondition(unrealized_pnl_pct_above=3.0)
+        assert engine.evaluate_condition(condition, {}) is False
+
+    def test_missing_holding_days_does_not_match(
+        self, engine: ScenarioEngine
+    ) -> None:
+        """Missing holding_days key should not match the condition."""
+        condition = StockCondition(holding_days_above=5)
+        assert engine.evaluate_condition(condition, {}) is False
+
+    def test_match_details_includes_position_fields(
+        self, engine: ScenarioEngine
+    ) -> None:
+        """match_details should include position fields when condition specifies them."""
+        pb = _playbook(
+            scenarios=[
+                StockScenario(
+                    condition=StockCondition(unrealized_pnl_pct_above=3.0),
+                    action=ScenarioAction.SELL,
+                    confidence=90,
+                    rationale="Take profit",
+                )
+            ]
+        )
+        result = engine.evaluate(
+            pb,
+            "005930",
+            {"unrealized_pnl_pct": 5.0},
+            {},
+        )
+        assert result.action == ScenarioAction.SELL
+        assert "unrealized_pnl_pct" in result.match_details
+        assert result.match_details["unrealized_pnl_pct"] == 5.0
+
+    def test_position_conditions_parse_from_planner(self) -> None:
+        """StockCondition should accept and store new fields from JSON parsing."""
+        condition = StockCondition(
+            unrealized_pnl_pct_above=3.0,
+            unrealized_pnl_pct_below=None,
+            holding_days_above=5,
+            holding_days_below=None,
+        )
+        assert condition.unrealized_pnl_pct_above == 3.0
+        assert condition.holding_days_above == 5
+        assert condition.has_any_condition() is True

tests/test_smart_scanner.py

@@ -350,6 +350,42 @@ class TestSmartVolatilityScanner:
         assert [c.stock_code for c in candidates] == ["ABCD"]
 
 
+class TestImpliedRSIFormula:
+    """Test the implied_rsi formula in SmartVolatilityScanner (issue #181)."""
+
+    def test_neutral_change_gives_neutral_rsi(self) -> None:
+        """0% change → implied_rsi = 50 (neutral)."""
+        # formula: 50 + (change_rate * 2.0)
+        rsi = max(0.0, min(100.0, 50.0 + (0.0 * 2.0)))
+        assert rsi == 50.0
+
+    def test_10pct_change_gives_rsi_70(self) -> None:
+        """10% upward change → implied_rsi = 70 (momentum signal)."""
+        rsi = max(0.0, min(100.0, 50.0 + (10.0 * 2.0)))
+        assert rsi == 70.0
+
+    def test_minus_10pct_gives_rsi_30(self) -> None:
+        """-10% change → implied_rsi = 30 (oversold signal)."""
+        rsi = max(0.0, min(100.0, 50.0 + (-10.0 * 2.0)))
+        assert rsi == 30.0
+
+    def test_saturation_at_25pct(self) -> None:
+        """Saturation occurs at >=25% change (not 12.5% as with old coefficient 4.0)."""
+        rsi_12pct = max(0.0, min(100.0, 50.0 + (12.5 * 2.0)))
+        rsi_25pct = max(0.0, min(100.0, 50.0 + (25.0 * 2.0)))
+        rsi_30pct = max(0.0, min(100.0, 50.0 + (30.0 * 2.0)))
+        # At 12.5% change: RSI = 75 (not 100, unlike old formula)
+        assert rsi_12pct == 75.0
+        # At 25%+ saturation
+        assert rsi_25pct == 100.0
+        assert rsi_30pct == 100.0  # Capped
+
+    def test_negative_saturation(self) -> None:
+        """Saturation at -25% gives RSI = 0."""
+        rsi = max(0.0, min(100.0, 50.0 + (-25.0 * 2.0)))
+        assert rsi == 0.0
+
+
 class TestRSICalculation:
     """Test RSI calculation in VolatilityAnalyzer."""
 

tests/test_strategies_base.py

@@ -0,0 +1,32 @@
+"""Tests for BaseStrategy abstract class."""
+
+from __future__ import annotations
+
+from typing import Any
+
+import pytest
+
+from src.strategies.base import BaseStrategy
+
+
+class ConcreteStrategy(BaseStrategy):
+    """Minimal concrete strategy for testing."""
+
+    def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
+        return {"action": "HOLD", "confidence": 50, "rationale": "test"}
+
+
+def test_base_strategy_cannot_be_instantiated() -> None:
+    """BaseStrategy cannot be instantiated directly (it's abstract)."""
+    with pytest.raises(TypeError):
+        BaseStrategy()  # type: ignore[abstract]
+
+
+def test_concrete_strategy_evaluate_returns_decision() -> None:
+    """Concrete subclass must implement evaluate and return a dict."""
+    strategy = ConcreteStrategy()
+    result = strategy.evaluate({"close": [100.0, 101.0]})
+    assert isinstance(result, dict)
+    assert result["action"] == "HOLD"
+    assert result["confidence"] == 50
+    assert "rationale" in result

tests/test_telegram.py

@@ -5,7 +5,7 @@ from unittest.mock import AsyncMock, patch
 import aiohttp
 import pytest
 
-from src.notifications.telegram_client import NotificationPriority, TelegramClient
+from src.notifications.telegram_client import NotificationFilter, NotificationPriority, TelegramClient
 
 
 class TestTelegramClientInit:
@@ -481,3 +481,187 @@ class TestClientCleanup:
 
         # Should not raise exception
         await client.close()
+
+
+class TestNotificationFilter:
+    """Test granular notification filter behavior."""
+
+    def test_default_filter_allows_all(self) -> None:
+        """Default NotificationFilter has all flags enabled."""
+        f = NotificationFilter()
+        assert f.trades is True
+        assert f.market_open_close is True
+        assert f.fat_finger is True
+        assert f.system_events is True
+        assert f.playbook is True
+        assert f.scenario_match is True
+        assert f.errors is True
+
+    def test_client_uses_default_filter_when_none_given(self) -> None:
+        """TelegramClient creates a default NotificationFilter when none provided."""
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        assert isinstance(client._filter, NotificationFilter)
+        assert client._filter.scenario_match is True
+
+    def test_client_stores_provided_filter(self) -> None:
+        """TelegramClient stores a custom NotificationFilter."""
+        nf = NotificationFilter(scenario_match=False, trades=False)
+        client = TelegramClient(
+            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
+        )
+        assert client._filter.scenario_match is False
+        assert client._filter.trades is False
+        assert client._filter.market_open_close is True  # default still True
+
+    @pytest.mark.asyncio
+    async def test_scenario_match_filtered_does_not_send(self) -> None:
+        """notify_scenario_matched skips send when scenario_match=False."""
+        nf = NotificationFilter(scenario_match=False)
+        client = TelegramClient(
+            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
+        )
+        with patch("aiohttp.ClientSession.post") as mock_post:
+            await client.notify_scenario_matched(
+                stock_code="005930", action="BUY", condition_summary="rsi<30", confidence=85.0
+            )
+            mock_post.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_trades_filtered_does_not_send(self) -> None:
+        """notify_trade_execution skips send when trades=False."""
+        nf = NotificationFilter(trades=False)
+        client = TelegramClient(
+            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
+        )
+        with patch("aiohttp.ClientSession.post") as mock_post:
+            await client.notify_trade_execution(
+                stock_code="005930", market="KR", action="BUY",
+                quantity=10, price=70000.0, confidence=85.0
+            )
+            mock_post.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_market_open_close_filtered_does_not_send(self) -> None:
+        """notify_market_open/close skip send when market_open_close=False."""
+        nf = NotificationFilter(market_open_close=False)
+        client = TelegramClient(
+            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
+        )
+        with patch("aiohttp.ClientSession.post") as mock_post:
+            await client.notify_market_open("Korea")
+            await client.notify_market_close("Korea", pnl_pct=1.5)
+            mock_post.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_circuit_breaker_always_sends_regardless_of_filter(self) -> None:
+        """notify_circuit_breaker always sends (no filter flag)."""
+        nf = NotificationFilter(
+            trades=False, market_open_close=False, fat_finger=False,
+            system_events=False, playbook=False, scenario_match=False, errors=False,
+        )
+        client = TelegramClient(
+            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
+        )
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
+            await client.notify_circuit_breaker(pnl_pct=-3.5, threshold=-3.0)
+            assert mock_post.call_count == 1
+
+    @pytest.mark.asyncio
+    async def test_errors_filtered_does_not_send(self) -> None:
+        """notify_error skips send when errors=False."""
+        nf = NotificationFilter(errors=False)
+        client = TelegramClient(
+            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
+        )
+        with patch("aiohttp.ClientSession.post") as mock_post:
+            await client.notify_error("TestError", "something went wrong", "KR")
+            mock_post.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_playbook_filtered_does_not_send(self) -> None:
+        """notify_playbook_generated/failed skip send when playbook=False."""
+        nf = NotificationFilter(playbook=False)
+        client = TelegramClient(
+            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
+        )
+        with patch("aiohttp.ClientSession.post") as mock_post:
+            await client.notify_playbook_generated("KR", 3, 10, 1200)
+            await client.notify_playbook_failed("KR", "timeout")
+            mock_post.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_system_events_filtered_does_not_send(self) -> None:
+        """notify_system_start/shutdown skip send when system_events=False."""
+        nf = NotificationFilter(system_events=False)
+        client = TelegramClient(
+            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
+        )
+        with patch("aiohttp.ClientSession.post") as mock_post:
+            await client.notify_system_start("paper", ["KR"])
+            await client.notify_system_shutdown("Normal shutdown")
+            mock_post.assert_not_called()
+
+    def test_set_flag_valid_key(self) -> None:
+        """set_flag returns True and updates field for a known key."""
+        nf = NotificationFilter()
+        assert nf.set_flag("scenario", False) is True
+        assert nf.scenario_match is False
+
+    def test_set_flag_invalid_key(self) -> None:
+        """set_flag returns False for an unknown key."""
+        nf = NotificationFilter()
+        assert nf.set_flag("unknown_key", False) is False
+
+    def test_as_dict_keys_match_KEYS(self) -> None:
+        """as_dict() returns every key defined in KEYS."""
+        nf = NotificationFilter()
+        d = nf.as_dict()
+        assert set(d.keys()) == set(NotificationFilter.KEYS.keys())
+
+    def test_set_notification_valid_key(self) -> None:
+        """TelegramClient.set_notification toggles filter at runtime."""
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        assert client._filter.scenario_match is True
+        assert client.set_notification("scenario", False) is True
+        assert client._filter.scenario_match is False
+
+    def test_set_notification_all_off(self) -> None:
+        """set_notification('all', False) disables every filter flag."""
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        assert client.set_notification("all", False) is True
+        for v in client.filter_status().values():
+            assert v is False
+
+    def test_set_notification_all_on(self) -> None:
+        """set_notification('all', True) enables every filter flag."""
+        client = TelegramClient(
+            bot_token="123:abc", chat_id="456", enabled=True,
+            notification_filter=NotificationFilter(
+                trades=False, market_open_close=False, scenario_match=False,
+                fat_finger=False, system_events=False, playbook=False, errors=False,
+            ),
+        )
+        assert client.set_notification("all", True) is True
+        for v in client.filter_status().values():
+            assert v is True
+
+    def test_set_notification_unknown_key(self) -> None:
+        """set_notification returns False for an unknown key."""
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        assert client.set_notification("unknown", False) is False
+
+    def test_filter_status_reflects_current_state(self) -> None:
+        """filter_status() matches the current NotificationFilter state."""
+        nf = NotificationFilter(trades=False, scenario_match=False)
+        client = TelegramClient(
+            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
+        )
+        status = client.filter_status()
+        assert status["trades"] is False
+        assert status["scenario"] is False
+        assert status["market"] is True

tests/test_telegram_commands.py

@@ -875,3 +875,139 @@ class TestGetUpdates:
             updates = await handler._get_updates()
 
             assert updates == []
+
+    @pytest.mark.asyncio
+    async def test_get_updates_409_stops_polling(self) -> None:
+        """409 Conflict response stops the poller (_running = False) and returns empty list."""
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+        handler._running = True  # simulate active poller
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 409
+        mock_resp.text = AsyncMock(
+            return_value='{"ok":false,"error_code":409,"description":"Conflict"}'
+        )
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        with patch("aiohttp.ClientSession.post", return_value=mock_resp):
+            updates = await handler._get_updates()
+
+        assert updates == []
+        assert handler._running is False  # poller stopped
+
+    @pytest.mark.asyncio
+    async def test_poll_loop_exits_after_409(self) -> None:
+        """_poll_loop exits naturally after _running is set to False by a 409 response."""
+        import asyncio as _asyncio
+
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+
+        call_count = 0
+
+        async def mock_get_updates_409() -> list[dict]:
+            nonlocal call_count
+            call_count += 1
+            # Simulate 409 stopping the poller
+            handler._running = False
+            return []
+
+        handler._get_updates = mock_get_updates_409  # type: ignore[method-assign]
+
+        handler._running = True
+        task = _asyncio.create_task(handler._poll_loop())
+        await _asyncio.wait_for(task, timeout=2.0)
+
+        # _get_updates called exactly once, then loop exited
+        assert call_count == 1
+        assert handler._running is False
+
+
+class TestCommandWithArgs:
+    """Test register_command_with_args and argument dispatch."""
+
+    def test_register_command_with_args_stored(self) -> None:
+        """register_command_with_args stores handler in _commands_with_args."""
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+
+        async def my_handler(args: list[str]) -> None:
+            pass
+
+        handler.register_command_with_args("notify", my_handler)
+        assert "notify" in handler._commands_with_args
+        assert handler._commands_with_args["notify"] is my_handler
+
+    @pytest.mark.asyncio
+    async def test_args_handler_receives_arguments(self) -> None:
+        """Args handler is called with the trailing tokens."""
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+
+        received: list[list[str]] = []
+
+        async def capture(args: list[str]) -> None:
+            received.append(args)
+
+        handler.register_command_with_args("notify", capture)
+
+        update = {
+            "message": {
+                "chat": {"id": "456"},
+                "text": "/notify scenario off",
+            }
+        }
+        await handler._handle_update(update)
+        assert received == [["scenario", "off"]]
+
+    @pytest.mark.asyncio
+    async def test_args_handler_takes_priority_over_no_args_handler(self) -> None:
+        """When both handlers exist for same command, args handler wins."""
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+
+        no_args_called = []
+        args_called = []
+
+        async def no_args_handler() -> None:
+            no_args_called.append(True)
+
+        async def args_handler(args: list[str]) -> None:
+            args_called.append(args)
+
+        handler.register_command("notify", no_args_handler)
+        handler.register_command_with_args("notify", args_handler)
+
+        update = {
+            "message": {
+                "chat": {"id": "456"},
+                "text": "/notify all off",
+            }
+        }
+        await handler._handle_update(update)
+        assert args_called == [["all", "off"]]
+        assert no_args_called == []
+
+    @pytest.mark.asyncio
+    async def test_args_handler_with_no_trailing_args(self) -> None:
+        """/notify with no args still dispatches to args handler with empty list."""
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+
+        received: list[list[str]] = []
+
+        async def capture(args: list[str]) -> None:
+            received.append(args)
+
+        handler.register_command_with_args("notify", capture)
+
+        update = {
+            "message": {
+                "chat": {"id": "456"},
+                "text": "/notify",
+            }
+        }
+        await handler._handle_update(update)
+        assert received == [[]]