잔액 부족(주문가능금액 부족) 에러 발생 시 해당 종목을 10분간 BUY 시도에서
제외하는 cooldown 메커니즘을 realtime/daily 루프 모두에 적용.
- _BUY_COOLDOWN_SECONDS = 600 상수 추가
- trading_cycle()에 buy_cooldown 파라미터 추가
- 잔액 부족 에러(주문가능금액) 감지 후 cooldown 설정
- BUY 실행 전 cooldown 체크 (realtime + daily session 모두)
- TestBuyCooldown 테스트 클래스 4개 추가
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Import MarketOutlook at module level in main.py
- After scenario evaluation, check market_outlook and apply BUY confidence
threshold: BEARISH→90, BULLISH→75, others→settings.CONFIDENCE_THRESHOLD
- BUY actions below the adjusted threshold are downgraded to HOLD with
a descriptive rationale including the outlook and threshold values
- Add 5 integration tests covering bearish suppression, bearish allow,
bullish allow, bullish suppression, and neutral default threshold
Closes#173
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add playbook_allocation_pct and scenario_confidence parameters to
_determine_order_quantity() with playbook-based sizing taking priority
over volatility-score fallback when provided
- Confidence scaling: confidence/80 multiplier (confidence 96 → 1.2x)
clipped to [POSITION_MIN_ALLOCATION_PCT, POSITION_MAX_ALLOCATION_PCT]
- Pass matched_scenario.allocation_pct and match.confidence from
trading_cycle so AI's allocation decisions reach order execution
- Add 4 new tests: playbook priority, confidence scaling, max clamp,
and fallback behavior
Closes#172
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add unrealized_pnl_pct_above/below and holding_days_above/below fields
to StockCondition so AI can generate rules like 'P&L > 3% → SELL'
- Evaluate new fields in ScenarioEngine.evaluate_condition() with same
AND-combining logic as existing technical indicator fields
- Include position fields in _build_match_details() for audit logging
- Parse new fields from AI JSON response in PreMarketPlanner._parse_scenario()
- Update prompt schema example to show new position-aware condition fields
- Add 13 tests covering all new condition combinations and edge cases
Closes#171
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add current_holdings parameter to generate_playbook() and _build_prompt()
- Inject '## Current Holdings' section into Gemini prompt with qty, entry
price, unrealized PnL%, and holding days for each held position
- Instruct AI to generate SELL/HOLD scenarios for held stocks even if not
in scanner candidates list
- Allow held stock codes in _parse_response() valid_codes set so AI-
generated SELL scenarios for holdings pass validation
- Add 6 tests covering prompt inclusion, omission, and response parsing
Closes#170
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
DB의 주문 수량 기록은 실제 체결 수량과 다를 수 있음(부분 체결, 외부 수동 거래).
브로커 잔고 API(output1)를 source of truth로 사용하도록 수정.
## 변경 사항
### SELL 수량 (#164)
- _extract_held_qty_from_balance() 추가
- 국내: output1의 ord_psbl_qty (→ hldg_qty fallback)
- 해외: output1의 ovrs_cblc_qty (→ hldg_qty fallback)
- _determine_order_quantity()에 broker_held_qty 파라미터 추가
- SELL 시 broker_held_qty 반환 (0이면 주문 스킵)
- trading_cycle / run_daily_session 양쪽 호출 지점 수정
- 이미 fetch된 balance_data에서 수량 추출 (추가 API 호출 없음)
### 보유 종목 루프 (#165)
- _extract_held_codes_from_balance() 추가
- ord_psbl_qty > 0인 종목 코드 목록 반환
- 실시간 루프에서 스캔 시점에 get_balance() 호출해 보유 종목 병합
- 스캐너 후보 + 실제 보유 종목 union으로 trading_cycle 순회
- 실패 시 경고 로그 후 스캐너 후보만으로 계속 진행
### 테스트
- TestExtractHeldQtyFromBalance: 7개 (국내/해외/fallback/미보유)
- TestExtractHeldCodesFromBalance: 4개 (qty>0 포함, qty=0 제외 등)
- TestDetermineOrderQuantity: 5개 (SELL qty, BUY sizing)
- test_sell_order_uses_broker_balance_qty_not_db:
DB 10주 기록 vs 브로커 5주 확인 → 브로커 값(5) 사용 검증
- 기존 SELL/stop-loss/take-profit 테스트에 output1 mock 추가
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
HOLD 판정 후 보유 포지션에 대해 stop_loss와 함께 take_profit도 체크하도록 수정.
AI가 생성한 take_profit_pct가 실제 거래 로직에 반영되지 않던 구조적 결함 수정.
- HOLD 블록에서 loss_pct >= take_profit_threshold 조건 추가
- stop_loss와 상호 배타적으로 동작 (stop_loss 우선 체크)
- take_profit 기본값 3.0% (playbook 없는 경우 적용)
- 테스트 2개 추가:
- test_hold_overridden_to_sell_when_take_profit_triggered
- test_hold_not_overridden_when_between_stop_loss_and_take_profit
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add /api/pnl/history endpoint to app.py for daily P&L history charting
- Rewrite index.html as full SPA with Chart.js bar chart, summary cards,
and decisions log table with market filter tabs and 30s auto-refresh
- Add test_pnl_history_all_markets and test_pnl_history_market_filter tests
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
**Problem 1 — Current price always 0**
get_orderbook() used inquire-asking-price-exp-ccn which has no stck_prpr
in output1 (only askp/bidp data). This caused every domestic BUY to be
skipped with "no affordable quantity (cash=..., price=0.00)".
**Problem 2 — KRX tick unit error on limit orders**
Limit order prices were passed unrounded, triggering 호가단위 오류 in VTS.
Also ORD_DVSN was wrongly set to "01" (시장가) for limit orders.
**Fix**
- Add kr_tick_unit(price) and kr_round_down(price) module-level helpers
implementing KRX 7-tier price tick rules (1/5/10/50/100/500/1000원).
- Add get_current_price(stock_code) → (price, change_pct, foreigner_net)
using FHKST01010100 / inquire-price API (works in VTS, returns correct
stck_prpr, prdy_ctrt, frgn_ntby_qty).
- Fix send_order() ORD_DVSN: "00"=지정가, "01"=시장가 (was "01"/"06").
- Apply kr_round_down() to limit order price inside send_order().
- Replace both get_orderbook() calls in main.py with get_current_price().
- Update all 4 test_main.py mock sites to use get_current_price AsyncMock.
**Tests added** (25 new tests, all 646 pass)
- TestKrTickUnit: 13 parametrized boundary cases + 7 round-down cases
- TestGetCurrentPrice: correct fields, correct API path/TR_ID, HTTP error
- TestSendOrderTickRounding: tick rounding, ORD_DVSN 00/01
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Three bugs found by comparing against KIS official GitHub examples:
1. FID_COND_SCR_DIV_CODE: "20001" → "20171" (volume-rank screen code)
2. FID_TRGT_EXLS_CLS_CODE: "000000" (6-digit) → "0000000000" (10-digit)
3. fluctuation ranking:
- TR_ID: "FHPST01710100" (invalid) → "FHPST01700000"
- path: /quotations/volume-rank → /ranking/fluctuation
- params: volume-rank params → lowercase fluctuation-specific params
(fid_rank_sort_cls_code, fid_input_cnt_1, fid_prc_cls_code,
fid_rsfl_rate1, fid_rsfl_rate2, etc.)
Note: VTS (paper trading) does not return data from ranking APIs regardless
of parameter correctness — this is a KIS policy restriction, not a code bug.
These fixes ensure correct behavior when switching to a live account.
Tests: TestFetchMarketRankings (3 tests) added to test_broker.py
Closes#155
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Three fixes for overseas stock trading failures:
1. Price API exchange code mapping:
- get_overseas_price() now applies _PRICE_EXCHANGE_MAP (NASD→NAS, NYSE→NYS, AMEX→AMS)
- Price API HHDFS00000300 requires short exchange codes same as ranking API
2. rt_cd check in send_overseas_order():
- Log WARNING (not INFO) when rt_cd != "0" (e.g., "주문가능금액이 부족합니다")
- Caller (main.py) checks rt_cd == "0" before calling log_trade()
- Prevents DB from recording failed orders as successful trades
3. Limit order price premium for BUY:
- BUY limit price = current_price * 1.005 (0.5% premium)
- SELL limit price = current_price (no premium)
- Improves fill probability: KIS VTS only accepts limit orders,
and last price is typically at or below ask
4. PAPER_OVERSEAS_CASH fallback (config + main.py):
- New setting: PAPER_OVERSEAS_CASH = 50000.0 (USD)
- When VTS overseas balance API fails/returns 0, use this as simulated cash
- Applied in both trading_cycle() and run_daily_session()
5. Candidate price fallback:
- If price API returns 0, use scanner candidate price as fallback
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
KIS VTS (paper trading) rejects overseas market orders with:
"모의투자 주문처리가 안되었습니다(지정가만 가능한 상품입니다)"
Root cause: send_overseas_order() was called with price=0.0 (market order)
in both trading_cycle() and run_daily_session(), even though current_price
was already computed correctly by Fix#147 (exchange code mapping).
Fix: pass current_price as the limit order price in both call sites.
Domestic broker send_order() keeps price=0 (market orders are fine on KRX).
Adds regression test TestOverseasBalanceParsing::test_overseas_buy_order_uses_limit_price
verifying price=182.5 is passed, not 0.0.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Apply _PRICE_EXCHANGE_MAP in get_overseas_price() to send short codes
(NASD→NAS, NYSE→NYS, AMEX→AMS) required by HHDFS00000300 price API
- Add PAPER_OVERSEAS_CASH config setting (default $50,000) for simulated
USD balance when VTS overseas balance API returns 0 in paper mode
- Fall back to scan candidate price when live price API returns 0
- Both fixes together resolve "no affordable quantity (cash=0, price=0)"
which was preventing all overseas trade execution
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
When gemini-2.5-flash quota is exhausted (20 RPD free tier), generate_playbook()
fell back to _defensive_playbook() which only had price_change_pct_below: -3.0 SELL
conditions — no BUY conditions — causing zero trades on US market despite scanner
finding strong momentum/oversold candidates.
Changes:
- Add _smart_fallback_playbook() that uses scanner signals to build BUY conditions:
- momentum signal: BUY when volume_ratio_above=VOL_MULTIPLIER
- oversold signal: BUY when rsi_below=RSI_OVERSOLD_THRESHOLD
- always: SELL stop-loss at price_change_pct_below=-3.0
- Use _smart_fallback_playbook() instead of _defensive_playbook() on Gemini failure
- Add 10 new tests for _smart_fallback_playbook() covering momentum/oversold/empty cases
- Update existing test_gemini_failure_returns_defensive to match new behavior
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
decide() ignored market_data["prompt_override"], always building a generic
trade-decision prompt. This caused pre_market_planner playbook generation
to fail with JSONDecodeError on every market, falling back to defensive
playbooks. Now prompt_override takes priority over both optimization and
standard prompt building.
Closes#143
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The overseas ranking API was returning 404 for all exchanges because the
TR_IDs, API paths, and exchange codes were all incorrect. Updated to match
KIS official API documentation:
- TR_ID: HHDFS76290000 (updown-rate), HHDFS76270000 (volume-surge)
- Path: /uapi/overseas-stock/v1/ranking/{updown-rate,volume-surge}
- Exchange codes: NASD→NAS, NYSE→NYS, AMEX→AMS via ranking-specific mapping
Fixes#141
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- MARKET_SHORTHAND + expand_market_codes()로 config "US" → schedule "US_NASDAQ/NYSE/AMEX" 자동 확장
- /report, /scenarios, /review, /dashboard 텔레그램 명령 추가
- price_change_pct를 trading_cycle과 run_daily_session에 주입
- HOLD시 get_open_position 기반 손절 모니터링 및 자동 SELL 오버라이드
- 대시보드 /api/status 동적 market 조회로 변경
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add --dashboard CLI flag and DASHBOARD_ENABLED env var to start
FastAPI dashboard in a daemon thread alongside the trading loop.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add observability dashboard: status, playbook, scorecard, performance,
context browser, decisions, and active scenarios endpoints.
SQLite read-only on separate connections from trading loop.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Wrap evolution notification in try/except so telegram failures don't
crash the evolution loop. Add integration tests for market close flow.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Run EvolutionOptimizer.evolve() at US market close, skip for other
markets, and notify via Telegram when a strategy PR is generated.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Wire up periodic context rollups (weekly/monthly/quarterly/annual/legacy)
in both daily and realtime trading loops with dedup-safe scheduling.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add build_self_market_scorecard() to read previous day's own market
performance, and include it in the Gemini planning prompt alongside
cross-market context.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
KR planner now reads US scorecard from previous day (timezone-aware),
and generate_playbook uses STRATEGIC context selection.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Extract _handle_market_close() helper that runs EOD aggregation,
generates scorecard with optional AI lessons, and sends Telegram summary.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Generate per-market daily scorecards from decision_logs and trades,
optional Gemini-powered lessons, and store results in L6 context.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add decision_id column to trades table, capture log_decision() return
value, and update original BUY decision outcome on SELL execution.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add ContextScheduler with run_if_due() for periodic rollups
- Weekly (Sunday), monthly (last day), quarterly, annual, legacy schedules
- Daily cleanup of expired contexts via ContextStore
- Dedup guard: each task runs at most once per day
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add market parameter to aggregate_daily_from_trades() for per-market L6 aggregation
- Store market-scoped keys (total_pnl_KR, win_rate_US, etc.) in L6/L5/L4 layers
- Hook aggregate_daily_from_trades() into market close detection in run()
- Update tests for market-scoped context keys
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add L7_REALTIME writes in trading_cycle() for volatility, price, rsi, volume_ratio
- Normalize key format to {metric}_{market}_{stock_code} across scanner and main
- Fix existing key mismatch between scanner writes and main reads
- Remove unused MarketScanner dead code
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
run_all_aggregations() previously used datetime.now(UTC) for weekly
through annual layers while using the trade date only for daily,
causing data misalignment on backfill. Now all layers consistently
use the latest trade timestamp. Also adds "Z" suffix handling for
fromisoformat() compatibility and strengthens test assertions to
verify L4-L2 layer values end-to-end.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Address PR #110 review findings:
1. High — Realtime mode now loads playbook from DB before calling Gemini,
preventing duplicate API calls on process restart (4/day budget).
2. Medium — Pass market-local date (via market.timezone) to
generate_playbook() and _empty_playbook() instead of date.today().
3. Medium — scan_candidates restructured from {stock_code: candidate}
to {market_code: {stock_code: candidate}} to prevent KR/US symbol
collision.
New test: test_scan_candidates_market_scoped verifies cross-market
isolation.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Remove unused imports (sys, ScenarioMatch, asyncio, StockPlaybook),
fix import ordering, and split long lines for ruff compliance.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace brain.decide() with scenario_engine.evaluate() in trading_cycle
and brain.decide_batch() with per-stock scenario evaluation in
run_daily_session. Initialize PreMarketPlanner, ScenarioEngine, and
PlaybookStore in run(). Add pre-market playbook generation on market
open (1 Gemini call per market per day), market_data enrichment from
scanner metrics (rsi, volume_ratio), portfolio_data for global rules,
scenario match notifications, and playbook lifecycle management.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Review findings addressed:
- Finding 1 (ImportError): false positive — ContextLayer is re-exported from
src.context.store, import works correctly at runtime
- Finding 2 (timezone): generate_playbook() and build_cross_market_context()
now accept optional today parameter for market-local date injection
- Finding 3 (lint): removed unused imports (UTC, datetime, PlaybookStatus),
fixed line-too-long in prompt template
- Tests simplified: replaced date patching with direct today= parameter
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add playbooks table to src/db.py with UNIQUE(date, market) constraint
- PlaybookStore: save/load/delete, status management, match_count tracking,
list_recent with market filter, stats without full deserialization
- DayPlaybook JSON serialization via Pydantic model_dump_json/model_validate_json
- 23 tests, 100% coverage on playbook_store.py
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
