feat: 대시보드 오픈 포지션 패널 추가 (#193)

- /api/positions 엔드포인트 신설: 마지막 거래가 BUY인 종목을 오픈 포지션으로 반환
- _connect()에 WAL 모드 + busy_timeout=8000 추가 (트레이딩 루프와 동시 읽기 안전)
- init_db()에 idx_trades_stock_market_ts 인덱스 추가 (포지션 쿼리 최적화)
- index.html: 카드와 P&L 차트 사이에 포지션 패널 삽입 (종목/시장/수량/진입가/보유시간)
- 포지션 패널 테스트 3개 추가 (open BUY 반환, SELL 제외, 빈 DB 처리)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

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/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

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,
@@ -338,7 +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,

src/broker/overseas.py

@@ -230,7 +230,9 @@ class OverseasBroker:
         session = self._broker._get_session()
 
         # Virtual trading TR_IDs for overseas orders
-        tr_id = "VTTT1002U" if order_type == "BUY" else "VTTT1006U"
+        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 주문' 시트
+        # VTTT1002U: 모의투자 미국 매수, VTTT1001U: 모의투자 미국 매도
+        tr_id = "VTTT1002U" if order_type == "BUY" else "VTTT1001U"
 
         body = {
             "CANO": self._broker._account_no,

src/dashboard/app.py

@@ -4,7 +4,7 @@ from __future__ import annotations
 
 import json
 import sqlite3
-from datetime import UTC, datetime
+from datetime import UTC, datetime, timezone
 from pathlib import Path
 from typing import Any
 
@@ -341,12 +341,68 @@ 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

@@ -123,6 +123,32 @@
       .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); } }
@@ -163,6 +189,30 @@
         </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">
@@ -242,6 +292,39 @@
         </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>';
+        }
+      }
+
       async function fetchStatus() {
         try {
           const r = await fetch('/api/status');
@@ -383,6 +466,7 @@
         await Promise.all([
           fetchStatus(),
           fetchPerformance(),
+          fetchPositions(),
           fetchPnlHistory(currentDays),
           fetchDecisions(currentMarket),
         ]);

src/db.py

@@ -131,6 +131,13 @@ 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)"
+    )
+
     conn.commit()
     return conn
 

src/main.py

@@ -81,6 +81,7 @@ def safe_float(value: str | float | None, default: float = 0.0) -> float:
 TRADE_INTERVAL_SECONDS = 60
 SCAN_INTERVAL_SECONDS = 60  # Scan markets every 60 seconds
 MAX_CONNECTION_RETRIES = 3
+_BUY_COOLDOWN_SECONDS = 600  # 10-minute cooldown after insufficient-balance rejection
 
 # Daily trading mode constants (for Free tier API efficiency)
 DAILY_TRADE_SESSIONS = 4  # Number of trading sessions per day
@@ -190,8 +191,15 @@ def _determine_order_quantity(
     candidate: ScanCandidate | None,
     settings: Settings | None,
     broker_held_qty: int = 0,
+    playbook_allocation_pct: float | None = None,
+    scenario_confidence: int = 80,
 ) -> int:
-    """Determine order quantity using volatility-aware position sizing."""
+    """Determine order quantity using volatility-aware position sizing.
+
+    Priority:
+    1. playbook_allocation_pct (AI-specified) scaled by scenario_confidence
+    2. Fallback: volatility-score-based allocation from scanner candidate
+    """
     if action == "SELL":
         return broker_held_qty
     if current_price <= 0 or total_cash <= 0:
@@ -200,6 +208,22 @@ def _determine_order_quantity(
     if settings is None or not settings.POSITION_SIZING_ENABLED:
         return 1
 
+    # Use AI-specified allocation_pct if available
+    if playbook_allocation_pct is not None:
+        # Confidence scaling: confidence 80 → 1.0x, confidence 95 → 1.19x
+        confidence_scale = scenario_confidence / 80.0
+        effective_pct = min(
+            settings.POSITION_MAX_ALLOCATION_PCT,
+            max(
+                settings.POSITION_MIN_ALLOCATION_PCT,
+                playbook_allocation_pct * confidence_scale,
+            ),
+        )
+        budget = total_cash * (effective_pct / 100.0)
+        quantity = int(budget // current_price)
+        return max(0, quantity)
+
+    # Fallback: volatility-score-based allocation
     target_score = max(1.0, settings.POSITION_VOLATILITY_TARGET_SCORE)
     observed_score = candidate.score if candidate else target_score
     observed_score = max(1.0, min(100.0, observed_score))
@@ -275,6 +299,7 @@ async def trading_cycle(
     stock_code: str,
     scan_candidates: dict[str, dict[str, ScanCandidate]],
     settings: Settings | None = None,
+    buy_cooldown: dict[str, float] | None = None,
 ) -> None:
     """Execute one trading cycle for a single stock."""
     cycle_start_time = asyncio.get_event_loop().time()
@@ -485,6 +510,25 @@ async def trading_cycle(
                 ),
             )
 
+    # BUY 결정 전 기존 포지션 체크 (중복 매수 방지)
+    if decision.action == "BUY":
+        existing_position = get_open_position(db_conn, stock_code, market.code)
+        if existing_position:
+            decision = TradeDecision(
+                action="HOLD",
+                confidence=decision.confidence,
+                rationale=(
+                    f"Already holding {stock_code} "
+                    f"(entry={existing_position['price']:.4f}, "
+                    f"qty={existing_position['quantity']})"
+                ),
+            )
+            logger.info(
+                "BUY suppressed for %s (%s): already holding open position",
+                stock_code,
+                market.name,
+            )
+
     if decision.action == "HOLD":
         open_position = get_open_position(db_conn, stock_code, market.code)
         if open_position:
@@ -596,6 +640,7 @@ async def trading_cycle(
             if decision.action == "SELL"
             else 0
         )
+        matched_scenario = match.matched_scenario
         quantity = _determine_order_quantity(
             action=decision.action,
             current_price=current_price,
@@ -603,6 +648,8 @@ async def trading_cycle(
             candidate=candidate,
             settings=settings,
             broker_held_qty=broker_held_qty,
+            playbook_allocation_pct=matched_scenario.allocation_pct if matched_scenario else None,
+            scenario_confidence=match.confidence,
         )
         if quantity <= 0:
             logger.info(
@@ -616,13 +663,33 @@ async def trading_cycle(
             return
         order_amount = current_price * quantity
 
-        # 4. Risk check BEFORE order
+        # 4. Check BUY cooldown (set when a prior BUY failed due to insufficient balance)
+        if decision.action == "BUY" and buy_cooldown is not None:
+            cooldown_key = f"{market.code}:{stock_code}"
+            cooldown_until = buy_cooldown.get(cooldown_key, 0.0)
+            now = asyncio.get_event_loop().time()
+            if now < cooldown_until:
+                remaining = int(cooldown_until - now)
+                logger.info(
+                    "Skip BUY %s (%s): insufficient-balance cooldown active (%ds remaining)",
+                    stock_code,
+                    market.name,
+                    remaining,
+                )
+                return
+
+        # 5a. Risk check BEFORE order
+        # SELL orders do not consume cash (they receive it), so fat-finger check
+        # is skipped for SELLs — only circuit breaker applies.
         try:
-            risk.validate_order(
-                current_pnl_pct=pnl_pct,
-                order_amount=order_amount,
-                total_cash=total_cash,
-            )
+            if decision.action == "SELL":
+                risk.check_circuit_breaker(pnl_pct)
+            else:
+                risk.validate_order(
+                    current_pnl_pct=pnl_pct,
+                    order_amount=order_amount,
+                    total_cash=total_cash,
+                )
         except FatFingerRejected as exc:
             try:
                 await telegram.notify_fat_finger(
@@ -664,12 +731,24 @@ async def trading_cycle(
             # Check if KIS rejected the order (rt_cd != "0")
             if result.get("rt_cd", "") != "0":
                 order_succeeded = False
+                msg1 = result.get("msg1") or ""
                 logger.warning(
                     "Overseas order not accepted for %s: rt_cd=%s msg=%s",
                     stock_code,
                     result.get("rt_cd"),
-                    result.get("msg1"),
+                    msg1,
                 )
+                # Set BUY cooldown when the rejection is due to insufficient balance
+                if decision.action == "BUY" and buy_cooldown is not None and "주문가능금액" in msg1:
+                    cooldown_key = f"{market.code}:{stock_code}"
+                    buy_cooldown[cooldown_key] = (
+                        asyncio.get_event_loop().time() + _BUY_COOLDOWN_SECONDS
+                    )
+                    logger.info(
+                        "BUY cooldown set for %s: %.0fs (insufficient balance)",
+                        stock_code,
+                        _BUY_COOLDOWN_SECONDS,
+                    )
         logger.info("Order result: %s", result.get("msg1", "OK"))
 
         # 5.5. Notify trade execution (only on success)
@@ -777,6 +856,9 @@ async def run_daily_session(
 
     logger.info("Starting daily trading session for %d markets", len(open_markets))
 
+    # BUY cooldown: prevents retrying stocks rejected for insufficient balance
+    daily_buy_cooldown: dict[str, float] = {}  # "{market_code}:{stock_code}" -> expiry timestamp
+
     # Process each open market
     for market in open_markets:
         # Use market-local date for playbook keying
@@ -1049,13 +1131,33 @@ async def run_daily_session(
                     continue
                 order_amount = stock_data["current_price"] * quantity
 
+                # Check BUY cooldown (insufficient balance)
+                if decision.action == "BUY":
+                    daily_cooldown_key = f"{market.code}:{stock_code}"
+                    daily_cooldown_until = daily_buy_cooldown.get(daily_cooldown_key, 0.0)
+                    now = asyncio.get_event_loop().time()
+                    if now < daily_cooldown_until:
+                        remaining = int(daily_cooldown_until - now)
+                        logger.info(
+                            "Skip BUY %s (%s): insufficient-balance cooldown active (%ds remaining)",
+                            stock_code,
+                            market.name,
+                            remaining,
+                        )
+                        continue
+
                 # Risk check
+                # SELL orders do not consume cash (they receive it), so fat-finger
+                # check is skipped for SELLs — only circuit breaker applies.
                 try:
-                    risk.validate_order(
-                        current_pnl_pct=pnl_pct,
-                        order_amount=order_amount,
-                        total_cash=total_cash,
-                    )
+                    if decision.action == "SELL":
+                        risk.check_circuit_breaker(pnl_pct)
+                    else:
+                        risk.validate_order(
+                            current_pnl_pct=pnl_pct,
+                            order_amount=order_amount,
+                            total_cash=total_cash,
+                        )
                 except FatFingerRejected as exc:
                     try:
                         await telegram.notify_fat_finger(
@@ -1105,12 +1207,23 @@ async def run_daily_session(
                         )
                         if result.get("rt_cd", "") != "0":
                             order_succeeded = False
+                            daily_msg1 = result.get("msg1") or ""
                             logger.warning(
                                 "Overseas order not accepted for %s: rt_cd=%s msg=%s",
                                 stock_code,
                                 result.get("rt_cd"),
-                                result.get("msg1"),
+                                daily_msg1,
                             )
+                            if decision.action == "BUY" and "주문가능금액" in daily_msg1:
+                                daily_cooldown_key = f"{market.code}:{stock_code}"
+                                daily_buy_cooldown[daily_cooldown_key] = (
+                                    asyncio.get_event_loop().time() + _BUY_COOLDOWN_SECONDS
+                                )
+                                logger.info(
+                                    "BUY cooldown set for %s: %.0fs (insufficient balance)",
+                                    stock_code,
+                                    _BUY_COOLDOWN_SECONDS,
+                                )
                     logger.info("Order result: %s", result.get("msg1", "OK"))
 
                     # Notify trade execution (only on success)
@@ -1274,10 +1387,18 @@ def _start_dashboard_server(settings: Settings) -> threading.Thread | None:
     if not settings.DASHBOARD_ENABLED:
         return None
 
+    # Validate dependencies before spawning the thread so startup failures are
+    # reported synchronously (avoids the misleading "started" → "failed" log pair).
+    try:
+        import uvicorn  # noqa: F401
+        from src.dashboard import create_dashboard_app  # noqa: F401
+    except ImportError as exc:
+        logger.warning("Dashboard server unavailable (missing dependency): %s", exc)
+        return None
+
     def _serve() -> None:
         try:
             import uvicorn
-
             from src.dashboard import create_dashboard_app
 
             app = create_dashboard_app(settings.DB_PATH)
@@ -1288,7 +1409,7 @@ def _start_dashboard_server(settings: Settings) -> threading.Thread | None:
                 log_level="info",
             )
         except Exception as exc:
-            logger.warning("Dashboard server failed to start: %s", exc)
+            logger.warning("Dashboard server stopped unexpectedly: %s", exc)
 
     thread = threading.Thread(
         target=_serve,
@@ -1729,6 +1850,9 @@ async def run(settings: Settings) -> None:
     # Active stocks per market (dynamically discovered by scanner)
     active_stocks: dict[str, list[str]] = {}  # market_code -> [stock_codes]
 
+    # BUY cooldown: prevents retrying a stock rejected for insufficient balance
+    buy_cooldown: dict[str, float] = {}  # "{market_code}:{stock_code}" -> expiry timestamp
+
     # Initialize latency control system
     criticality_assessor = CriticalityAssessor(
         critical_pnl_threshold=-2.5,  # Near circuit breaker at -3.0%
@@ -2071,6 +2195,7 @@ async def run(settings: Settings) -> None:
                                     stock_code,
                                     scan_candidates,
                                     settings,
+                                    buy_cooldown,
                                 )
                                 break  # Success — exit retry loop
                             except CircuitBreakerTripped as exc:

src/notifications/telegram_client.py

@@ -604,9 +604,19 @@ class TelegramCommandHandler:
             async with session.post(url, json=payload) as resp:
                 if resp.status != 200:
                     error_text = await resp.text()
-                    logger.error(
-                        "getUpdates API error (status=%d): %s", resp.status, error_text
-                    )
+                    if resp.status == 409:
+                        # 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()

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

@@ -75,6 +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.
 
@@ -82,6 +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.
@@ -106,6 +111,7 @@ class PreMarketPlanner:
                 context_data,
                 self_market_scorecard,
                 cross_market,
+                current_holdings=current_holdings,
             )
 
             # 3. Call Gemini
@@ -118,7 +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}
@@ -230,6 +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
@@ -241,6 +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 = (
@@ -273,10 +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"
@@ -294,7 +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'
@@ -308,7 +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"
@@ -321,12 +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")
@@ -390,6 +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():

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_dashboard.py

@@ -316,3 +316,38 @@ def test_pnl_history_market_filter(tmp_path: Path) -> None:
     # 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"] == []

tests/test_main.py

@@ -205,6 +205,84 @@ class TestDetermineOrderQuantity:
         )
         assert result == 2
 
+    def test_determine_order_quantity_uses_playbook_allocation_pct(self) -> None:
+        """playbook_allocation_pct should take priority over volatility-based sizing."""
+        settings = MagicMock(spec=Settings)
+        settings.POSITION_SIZING_ENABLED = True
+        settings.POSITION_MAX_ALLOCATION_PCT = 30.0
+        settings.POSITION_MIN_ALLOCATION_PCT = 1.0
+        # playbook says 20%, confidence 80 → scale=1.0 → 20%
+        # 1,000,000 * 20% = 200,000 // 50,000 price = 4 shares
+        result = _determine_order_quantity(
+            action="BUY",
+            current_price=50000.0,
+            total_cash=1000000.0,
+            candidate=None,
+            settings=settings,
+            playbook_allocation_pct=20.0,
+            scenario_confidence=80,
+        )
+        assert result == 4
+
+    def test_determine_order_quantity_confidence_scales_allocation(self) -> None:
+        """Higher confidence should produce a larger allocation (up to max)."""
+        settings = MagicMock(spec=Settings)
+        settings.POSITION_SIZING_ENABLED = True
+        settings.POSITION_MAX_ALLOCATION_PCT = 30.0
+        settings.POSITION_MIN_ALLOCATION_PCT = 1.0
+        # confidence 96 → scale=1.2 → 10% * 1.2 = 12%
+        # 1,000,000 * 12% = 120,000 // 50,000 price = 2 shares
+        result = _determine_order_quantity(
+            action="BUY",
+            current_price=50000.0,
+            total_cash=1000000.0,
+            candidate=None,
+            settings=settings,
+            playbook_allocation_pct=10.0,
+            scenario_confidence=96,
+        )
+        # scale = 96/80 = 1.2 → effective_pct = 12.0
+        # budget = 1_000_000 * 0.12 = 120_000 → qty = 120_000 // 50_000 = 2
+        assert result == 2
+
+    def test_determine_order_quantity_confidence_clamped_to_max(self) -> None:
+        """Confidence scaling should not exceed POSITION_MAX_ALLOCATION_PCT."""
+        settings = MagicMock(spec=Settings)
+        settings.POSITION_SIZING_ENABLED = True
+        settings.POSITION_MAX_ALLOCATION_PCT = 15.0
+        settings.POSITION_MIN_ALLOCATION_PCT = 1.0
+        # playbook 20% * scale 1.5 = 30% → clamped to 15%
+        # 1,000,000 * 15% = 150,000 // 50,000 price = 3 shares
+        result = _determine_order_quantity(
+            action="BUY",
+            current_price=50000.0,
+            total_cash=1000000.0,
+            candidate=None,
+            settings=settings,
+            playbook_allocation_pct=20.0,
+            scenario_confidence=120,  # extreme → scale = 1.5
+        )
+        assert result == 3
+
+    def test_determine_order_quantity_fallback_when_no_playbook(self) -> None:
+        """Without playbook_allocation_pct, falls back to volatility-based sizing."""
+        settings = MagicMock(spec=Settings)
+        settings.POSITION_SIZING_ENABLED = True
+        settings.POSITION_VOLATILITY_TARGET_SCORE = 50.0
+        settings.POSITION_BASE_ALLOCATION_PCT = 10.0
+        settings.POSITION_MAX_ALLOCATION_PCT = 30.0
+        settings.POSITION_MIN_ALLOCATION_PCT = 1.0
+        # Same as test_buy_with_position_sizing_calculates_correctly (no playbook)
+        result = _determine_order_quantity(
+            action="BUY",
+            current_price=50000.0,
+            total_cash=1000000.0,
+            candidate=None,
+            settings=settings,
+            playbook_allocation_pct=None,  # explicit None → fallback
+        )
+        assert result == 2
+
 
 class TestSafeFloat:
     """Test safe_float() helper function."""
@@ -553,6 +631,119 @@ class TestTradingCycleTelegramIntegration:
         # Verify no trade notification sent
         mock_telegram.notify_trade_execution.assert_not_called()
 
+    @pytest.mark.asyncio
+    async def test_sell_skips_fat_finger_check(
+        self,
+        mock_broker: MagicMock,
+        mock_overseas_broker: MagicMock,
+        mock_scenario_engine: MagicMock,
+        mock_playbook: DayPlaybook,
+        mock_risk: MagicMock,
+        mock_db: MagicMock,
+        mock_decision_logger: MagicMock,
+        mock_context_store: MagicMock,
+        mock_criticality_assessor: MagicMock,
+        mock_telegram: MagicMock,
+        mock_market: MagicMock,
+    ) -> None:
+        """SELL orders must not be blocked by fat-finger check.
+
+        Even if position value > 30% of cash (e.g. stop-loss on a large holding
+        with low remaining cash), the SELL should proceed — only circuit breaker
+        applies to SELLs.
+        """
+        # SELL decision with held qty=100 shares @ 50,000 = 5,000,000
+        # cash = 5,000,000 → ratio = 100% which would normally trigger fat finger
+        mock_scenario_engine.evaluate = MagicMock(return_value=_make_sell_match())
+        mock_broker.get_balance = AsyncMock(
+            return_value={
+                "output1": [{"pdno": "005930", "ord_psbl_qty": "100"}],
+                "output2": [
+                    {
+                        "tot_evlu_amt": "10000000",
+                        "dnca_tot_amt": "5000000",
+                        "pchs_amt_smtl_amt": "5000000",
+                    }
+                ],
+            }
+        )
+
+        with patch("src.main.log_trade"):
+            await trading_cycle(
+                broker=mock_broker,
+                overseas_broker=mock_overseas_broker,
+                scenario_engine=mock_scenario_engine,
+                playbook=mock_playbook,
+                risk=mock_risk,
+                db_conn=mock_db,
+                decision_logger=mock_decision_logger,
+                context_store=mock_context_store,
+                criticality_assessor=mock_criticality_assessor,
+                telegram=mock_telegram,
+                market=mock_market,
+                stock_code="005930",
+                scan_candidates={},
+            )
+
+        # validate_order (which includes fat finger) must NOT be called for SELL
+        mock_risk.validate_order.assert_not_called()
+        # check_circuit_breaker MUST be called for SELL
+        mock_risk.check_circuit_breaker.assert_called_once()
+
+    @pytest.mark.asyncio
+    async def test_sell_circuit_breaker_still_applies(
+        self,
+        mock_broker: MagicMock,
+        mock_overseas_broker: MagicMock,
+        mock_scenario_engine: MagicMock,
+        mock_playbook: DayPlaybook,
+        mock_risk: MagicMock,
+        mock_db: MagicMock,
+        mock_decision_logger: MagicMock,
+        mock_context_store: MagicMock,
+        mock_criticality_assessor: MagicMock,
+        mock_telegram: MagicMock,
+        mock_market: MagicMock,
+    ) -> None:
+        """SELL orders must still respect the circuit breaker."""
+        mock_scenario_engine.evaluate = MagicMock(return_value=_make_sell_match())
+        mock_broker.get_balance = AsyncMock(
+            return_value={
+                "output1": [{"pdno": "005930", "ord_psbl_qty": "100"}],
+                "output2": [
+                    {
+                        "tot_evlu_amt": "10000000",
+                        "dnca_tot_amt": "5000000",
+                        "pchs_amt_smtl_amt": "5000000",
+                    }
+                ],
+            }
+        )
+        mock_risk.check_circuit_breaker.side_effect = CircuitBreakerTripped(
+            pnl_pct=-4.0, threshold=-3.0
+        )
+
+        with patch("src.main.log_trade"):
+            with pytest.raises(CircuitBreakerTripped):
+                await trading_cycle(
+                    broker=mock_broker,
+                    overseas_broker=mock_overseas_broker,
+                    scenario_engine=mock_scenario_engine,
+                    playbook=mock_playbook,
+                    risk=mock_risk,
+                    db_conn=mock_db,
+                    decision_logger=mock_decision_logger,
+                    context_store=mock_context_store,
+                    criticality_assessor=mock_criticality_assessor,
+                    telegram=mock_telegram,
+                    market=mock_market,
+                    stock_code="005930",
+                    scan_candidates={},
+                )
+
+        mock_risk.check_circuit_breaker.assert_called_once()
+        mock_risk.validate_order.assert_not_called()
+
 
 class TestRunFunctionTelegramIntegration:
     """Test telegram notifications in run function."""
@@ -2116,6 +2307,268 @@ def test_start_dashboard_server_enabled_starts_thread() -> None:
     mock_thread.start.assert_called_once()
 
 
+def test_start_dashboard_server_returns_none_when_uvicorn_missing() -> None:
+    """Returns None (no thread) and logs a warning when uvicorn is not installed."""
+    settings = Settings(
+        KIS_APP_KEY="test_key",
+        KIS_APP_SECRET="test_secret",
+        KIS_ACCOUNT_NO="12345678-01",
+        GEMINI_API_KEY="test_gemini_key",
+        DASHBOARD_ENABLED=True,
+    )
+    import builtins
+    real_import = builtins.__import__
+
+    def mock_import(name: str, *args: object, **kwargs: object) -> object:
+        if name == "uvicorn":
+            raise ImportError("No module named 'uvicorn'")
+        return real_import(name, *args, **kwargs)
+
+    with patch("builtins.__import__", side_effect=mock_import):
+        thread = _start_dashboard_server(settings)
+
+    assert thread is None
+
+
+# ---------------------------------------------------------------------------
+# BUY cooldown tests (#179)
+# ---------------------------------------------------------------------------
+
+
+class TestBuyCooldown:
+    """Tests for BUY cooldown after insufficient-balance rejection."""
+
+    @pytest.fixture
+    def mock_broker(self) -> MagicMock:
+        broker = MagicMock()
+        broker.get_current_price = AsyncMock(return_value=(100.0, 1.0, 0.0))
+        broker.get_balance = AsyncMock(
+            return_value={
+                "output2": [{"tot_evlu_amt": "1000000", "dnca_tot_amt": "500000",
+                             "pchs_amt_smtl_amt": "500000"}]
+            }
+        )
+        broker.send_order = AsyncMock(return_value={"msg1": "OK"})
+        return broker
+
+    @pytest.fixture
+    def mock_market(self) -> MagicMock:
+        market = MagicMock()
+        market.name = "Korea"
+        market.code = "KR"
+        market.exchange_code = "KRX"
+        market.is_domestic = True
+        return market
+
+    @pytest.fixture
+    def mock_overseas_market(self) -> MagicMock:
+        market = MagicMock()
+        market.name = "NASDAQ"
+        market.code = "US_NASDAQ"
+        market.exchange_code = "NAS"
+        market.is_domestic = False
+        return market
+
+    @pytest.fixture
+    def mock_overseas_broker(self) -> MagicMock:
+        broker = MagicMock()
+        broker.get_overseas_price = AsyncMock(
+            return_value={"output": {"last": "1.0", "rate": "0.0",
+                                     "high": "1.05", "low": "0.95", "tvol": "1000000"}}
+        )
+        broker.get_overseas_balance = AsyncMock(return_value={
+            "output1": [],
+            "output2": [{"frcr_dncl_amt_2": "50000", "frcr_evlu_tota": "50000",
+                         "frcr_buy_amt_smtl": "0"}],
+        })
+        broker.send_overseas_order = AsyncMock(
+            return_value={"rt_cd": "1", "msg1": "모의투자 주문가능금액이 부족합니다."}
+        )
+        return broker
+
+    def _make_buy_match_overseas(self, stock_code: str = "MLECW") -> ScenarioMatch:
+        return ScenarioMatch(
+            stock_code=stock_code,
+            matched_scenario=None,
+            action=ScenarioAction.BUY,
+            confidence=85,
+            rationale="Test buy",
+        )
+
+    @pytest.mark.asyncio
+    async def test_cooldown_set_on_insufficient_balance(
+        self, mock_broker: MagicMock, mock_overseas_broker: MagicMock,
+        mock_overseas_market: MagicMock,
+    ) -> None:
+        """BUY cooldown entry is created after 주문가능금액 rejection."""
+        engine = MagicMock(spec=ScenarioEngine)
+        engine.evaluate = MagicMock(return_value=self._make_buy_match_overseas("MLECW"))
+        buy_cooldown: dict[str, float] = {}
+
+        with patch("src.main.log_trade"):
+            await trading_cycle(
+                broker=mock_broker,
+                overseas_broker=mock_overseas_broker,
+                scenario_engine=engine,
+                playbook=_make_playbook("US_NASDAQ"),
+                risk=MagicMock(),
+                db_conn=MagicMock(),
+                decision_logger=MagicMock(),
+                context_store=MagicMock(get_latest_timeframe=MagicMock(return_value=None)),
+                criticality_assessor=MagicMock(
+                    assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
+                    get_timeout=MagicMock(return_value=5.0),
+                ),
+                telegram=MagicMock(
+                    notify_trade_execution=AsyncMock(),
+                    notify_fat_finger=AsyncMock(),
+                    notify_circuit_breaker=AsyncMock(),
+                    notify_scenario_matched=AsyncMock(),
+                ),
+                market=mock_overseas_market,
+                stock_code="MLECW",
+                scan_candidates={},
+                buy_cooldown=buy_cooldown,
+            )
+
+        assert "US_NASDAQ:MLECW" in buy_cooldown
+        assert buy_cooldown["US_NASDAQ:MLECW"] > 0
+
+    @pytest.mark.asyncio
+    async def test_cooldown_skips_buy(
+        self, mock_broker: MagicMock, mock_overseas_broker: MagicMock,
+        mock_overseas_market: MagicMock,
+    ) -> None:
+        """BUY is skipped when cooldown is active for the stock."""
+        engine = MagicMock(spec=ScenarioEngine)
+        engine.evaluate = MagicMock(return_value=self._make_buy_match_overseas("MLECW"))
+
+        import asyncio
+        # Set an active cooldown (expires far in the future)
+        buy_cooldown: dict[str, float] = {
+            "US_NASDAQ:MLECW": asyncio.get_event_loop().time() + 600
+        }
+
+        with patch("src.main.log_trade"):
+            await trading_cycle(
+                broker=mock_broker,
+                overseas_broker=mock_overseas_broker,
+                scenario_engine=engine,
+                playbook=_make_playbook("US_NASDAQ"),
+                risk=MagicMock(),
+                db_conn=MagicMock(),
+                decision_logger=MagicMock(),
+                context_store=MagicMock(get_latest_timeframe=MagicMock(return_value=None)),
+                criticality_assessor=MagicMock(
+                    assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
+                    get_timeout=MagicMock(return_value=5.0),
+                ),
+                telegram=MagicMock(
+                    notify_trade_execution=AsyncMock(),
+                    notify_fat_finger=AsyncMock(),
+                    notify_circuit_breaker=AsyncMock(),
+                    notify_scenario_matched=AsyncMock(),
+                ),
+                market=mock_overseas_market,
+                stock_code="MLECW",
+                scan_candidates={},
+                buy_cooldown=buy_cooldown,
+            )
+
+        # Order should NOT have been sent
+        mock_overseas_broker.send_overseas_order.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_cooldown_not_set_on_other_errors(
+        self, mock_broker: MagicMock, mock_overseas_market: MagicMock,
+    ) -> None:
+        """Cooldown is NOT set for non-balance-related rejections."""
+        engine = MagicMock(spec=ScenarioEngine)
+        engine.evaluate = MagicMock(return_value=self._make_buy_match_overseas("MLECW"))
+        # Different rejection reason
+        overseas_broker = MagicMock()
+        overseas_broker.get_overseas_price = AsyncMock(
+            return_value={"output": {"last": "1.0", "rate": "0.0",
+                                     "high": "1.05", "low": "0.95", "tvol": "1000000"}}
+        )
+        overseas_broker.get_overseas_balance = AsyncMock(return_value={
+            "output1": [],
+            "output2": [{"frcr_dncl_amt_2": "50000", "frcr_evlu_tota": "50000",
+                         "frcr_buy_amt_smtl": "0"}],
+        })
+        overseas_broker.send_overseas_order = AsyncMock(
+            return_value={"rt_cd": "1", "msg1": "기타 오류 메시지"}
+        )
+        buy_cooldown: dict[str, float] = {}
+
+        with patch("src.main.log_trade"):
+            await trading_cycle(
+                broker=mock_broker,
+                overseas_broker=overseas_broker,
+                scenario_engine=engine,
+                playbook=_make_playbook("US_NASDAQ"),
+                risk=MagicMock(),
+                db_conn=MagicMock(),
+                decision_logger=MagicMock(),
+                context_store=MagicMock(get_latest_timeframe=MagicMock(return_value=None)),
+                criticality_assessor=MagicMock(
+                    assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
+                    get_timeout=MagicMock(return_value=5.0),
+                ),
+                telegram=MagicMock(
+                    notify_trade_execution=AsyncMock(),
+                    notify_fat_finger=AsyncMock(),
+                    notify_circuit_breaker=AsyncMock(),
+                    notify_scenario_matched=AsyncMock(),
+                ),
+                market=mock_overseas_market,
+                stock_code="MLECW",
+                scan_candidates={},
+                buy_cooldown=buy_cooldown,
+            )
+
+        # Cooldown should NOT be set for non-balance errors
+        assert "US_NASDAQ:MLECW" not in buy_cooldown
+
+    @pytest.mark.asyncio
+    async def test_no_cooldown_param_still_works(
+        self, mock_broker: MagicMock, mock_overseas_broker: MagicMock,
+        mock_overseas_market: MagicMock,
+    ) -> None:
+        """trading_cycle works normally when buy_cooldown is None (default)."""
+        engine = MagicMock(spec=ScenarioEngine)
+        engine.evaluate = MagicMock(return_value=self._make_buy_match_overseas("MLECW"))
+
+        with patch("src.main.log_trade"):
+            await trading_cycle(
+                broker=mock_broker,
+                overseas_broker=mock_overseas_broker,
+                scenario_engine=engine,
+                playbook=_make_playbook("US_NASDAQ"),
+                risk=MagicMock(),
+                db_conn=MagicMock(),
+                decision_logger=MagicMock(),
+                context_store=MagicMock(get_latest_timeframe=MagicMock(return_value=None)),
+                criticality_assessor=MagicMock(
+                    assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
+                    get_timeout=MagicMock(return_value=5.0),
+                ),
+                telegram=MagicMock(
+                    notify_trade_execution=AsyncMock(),
+                    notify_fat_finger=AsyncMock(),
+                    notify_circuit_breaker=AsyncMock(),
+                    notify_scenario_matched=AsyncMock(),
+                ),
+                market=mock_overseas_market,
+                stock_code="MLECW",
+                scan_candidates={},
+                # buy_cooldown not passed → defaults to None
+            )
+
+        # Should attempt the order (and fail), but not crash
+        mock_overseas_broker.send_overseas_order.assert_called_once()
+
+
 # ---------------------------------------------------------------------------
 # market_outlook BUY confidence threshold tests (#173)
 # ---------------------------------------------------------------------------
@@ -2395,3 +2848,156 @@ class TestMarketOutlookConfidenceThreshold:
         call_args = decision_logger.log_decision.call_args
         assert call_args is not None
         assert call_args.kwargs["action"] == "BUY"
+
+
+@pytest.mark.asyncio
+async def test_buy_suppressed_when_open_position_exists() -> None:
+    """BUY should be suppressed when an open position already exists for the stock."""
+    db_conn = init_db(":memory:")
+    decision_logger = DecisionLogger(db_conn)
+
+    # 기존 BUY 포지션 DB에 기록 (중복 매수 상황)
+    buy_decision_id = decision_logger.log_decision(
+        stock_code="NP",
+        market="US",
+        exchange_code="AMS",
+        action="BUY",
+        confidence=90,
+        rationale="initial entry",
+        context_snapshot={},
+        input_data={},
+    )
+    log_trade(
+        conn=db_conn,
+        stock_code="NP",
+        action="BUY",
+        confidence=90,
+        rationale="initial entry",
+        quantity=10,
+        price=50.0,
+        market="US",
+        exchange_code="AMS",
+        decision_id=buy_decision_id,
+    )
+
+    broker = MagicMock()
+    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
+
+    overseas_broker = MagicMock()
+    overseas_broker.get_overseas_price = AsyncMock(
+        return_value={"output": {"last": "51.0", "rate": "2.0", "high": "52.0", "low": "50.0", "tvol": "1000000"}}
+    )
+    overseas_broker.get_overseas_balance = AsyncMock(
+        return_value={
+            "output1": [],
+            "output2": [{"frcr_dncl_amt_2": "10000", "frcr_evlu_tota": "10000", "frcr_buy_amt_smtl": "0"}],
+        }
+    )
+    overseas_broker.send_overseas_order = AsyncMock(return_value={"msg1": "OK"})
+
+    engine = MagicMock(spec=ScenarioEngine)
+    engine.evaluate = MagicMock(return_value=_make_buy_match(stock_code="NP"))
+
+    market = MagicMock()
+    market.name = "United States"
+    market.code = "US"
+    market.exchange_code = "AMS"
+    market.is_domestic = False
+
+    telegram = MagicMock()
+    telegram.notify_trade_execution = AsyncMock()
+    telegram.notify_fat_finger = AsyncMock()
+    telegram.notify_circuit_breaker = AsyncMock()
+    telegram.notify_scenario_matched = AsyncMock()
+
+    await trading_cycle(
+        broker=broker,
+        overseas_broker=overseas_broker,
+        scenario_engine=engine,
+        playbook=_make_playbook(market="US"),
+        risk=MagicMock(),
+        db_conn=db_conn,
+        decision_logger=decision_logger,
+        context_store=MagicMock(
+            get_latest_timeframe=MagicMock(return_value=None),
+            set_context=MagicMock(),
+        ),
+        criticality_assessor=MagicMock(
+            assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
+            get_timeout=MagicMock(return_value=5.0),
+        ),
+        telegram=telegram,
+        market=market,
+        stock_code="NP",
+        scan_candidates={},
+    )
+
+    # 이미 보유 중이므로 주문이 실행되지 않아야 함
+    broker.send_order.assert_not_called()
+    overseas_broker.send_overseas_order.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_buy_proceeds_when_no_open_position() -> None:
+    """BUY should proceed normally when no open position exists for the stock."""
+    db_conn = init_db(":memory:")
+    decision_logger = DecisionLogger(db_conn)
+    # DB가 비어있는 상태 — 기존 포지션 없음
+
+    broker = MagicMock()
+    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
+
+    overseas_broker = MagicMock()
+    overseas_broker.get_overseas_price = AsyncMock(
+        return_value={"output": {"last": "100.0", "rate": "1.0", "high": "101.0", "low": "99.0", "tvol": "500000"}}
+    )
+    overseas_broker.get_overseas_balance = AsyncMock(
+        return_value={
+            "output1": [],
+            "output2": [{"frcr_dncl_amt_2": "50000", "frcr_evlu_tota": "50000", "frcr_buy_amt_smtl": "0"}],
+        }
+    )
+    overseas_broker.send_overseas_order = AsyncMock(return_value={"msg1": "OK"})
+
+    engine = MagicMock(spec=ScenarioEngine)
+    engine.evaluate = MagicMock(return_value=_make_buy_match(stock_code="KNRX"))
+
+    market = MagicMock()
+    market.name = "United States"
+    market.code = "US"
+    market.exchange_code = "NAS"
+    market.is_domestic = False
+
+    risk = MagicMock()
+    risk.validate_order = MagicMock()
+
+    telegram = MagicMock()
+    telegram.notify_trade_execution = AsyncMock()
+    telegram.notify_fat_finger = AsyncMock()
+    telegram.notify_circuit_breaker = AsyncMock()
+    telegram.notify_scenario_matched = AsyncMock()
+
+    await trading_cycle(
+        broker=broker,
+        overseas_broker=overseas_broker,
+        scenario_engine=engine,
+        playbook=_make_playbook(market="US"),
+        risk=risk,
+        db_conn=db_conn,
+        decision_logger=decision_logger,
+        context_store=MagicMock(
+            get_latest_timeframe=MagicMock(return_value=None),
+            set_context=MagicMock(),
+        ),
+        criticality_assessor=MagicMock(
+            assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
+            get_timeout=MagicMock(return_value=5.0),
+        ),
+        telegram=telegram,
+        market=market,
+        stock_code="KNRX",
+        scan_candidates={},
+    )
+
+    # 포지션이 없으므로 해외 주문이 실행되어야 함
+    overseas_broker.send_overseas_order.assert_called_once()

tests/test_overseas_broker.py

@@ -414,7 +414,7 @@ class TestSendOverseasOrder:
 
     @pytest.mark.asyncio
     async def test_sell_limit_order(self, overseas_broker: OverseasBroker) -> None:
-        """Limit sell order should use VTTT1006U and ORD_DVSN=00."""
+        """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"})
@@ -428,7 +428,7 @@ class TestSendOverseasOrder:
         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("VTTT1006U")
+        overseas_broker._broker._auth_headers.assert_called_with("VTTT1001U")
 
         call_args = mock_session.post.call_args
         body = call_args[1]["json"]

tests/test_pre_market_planner.py

@@ -830,3 +830,171 @@ class TestSmartFallbackPlaybook:
         ]
         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_telegram_commands.py

@@ -876,6 +876,54 @@ class TestGetUpdates:
 
             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."""