improve: implied_rsi 계수 4.0→2.0으로 완화 — 포화 임계점 12.5%→25% (#181)

SmartScanner의 implied_rsi 공식에서 계수를 4.0에서 2.0으로 수정.
12.5% 이상 변동률에서 RSI=100으로 포화되던 문제를 개선.

변경 전: 50 + (change_rate * 4.0) → 12.5% 변동 시 RSI=100
변경 후: 50 + (change_rate * 2.0) → 25% 변동 시 RSI=100

이제 10% 상승 → RSI=70, 12.5% 상승 → RSI=75 (의미 있는 구분 가능)
해외 소형주(NYSE American 등)의 RSI=100 집단 현상 완화.

- smart_scanner.py 3곳 동일 공식 모두 수정
- TestImpliedRSIFormula 클래스 5개 테스트 추가

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

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/main.py

@@ -42,7 +42,7 @@ from src.logging.decision_logger import DecisionLogger
 from src.logging_config import setup_logging
 from src.markets.schedule import MarketInfo, get_next_market_open, get_open_markets
 from src.notifications.telegram_client import NotificationFilter, TelegramClient, TelegramCommandHandler
-from src.strategy.models import DayPlaybook
+from src.strategy.models import DayPlaybook, MarketOutlook
 from src.strategy.playbook_store import PlaybookStore
 from src.strategy.pre_market_planner import PreMarketPlanner
 from src.strategy.scenario_engine import ScenarioEngine
@@ -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()
@@ -457,6 +482,34 @@ async def trading_cycle(
     )
     stock_playbook = playbook.get_stock_playbook(stock_code)
 
+    # 2.1. Apply market_outlook-based BUY confidence threshold
+    if decision.action == "BUY":
+        base_threshold = (settings.CONFIDENCE_THRESHOLD if settings else 80)
+        outlook = playbook.market_outlook
+        if outlook == MarketOutlook.BEARISH:
+            min_confidence = 90
+        elif outlook == MarketOutlook.BULLISH:
+            min_confidence = 75
+        else:
+            min_confidence = base_threshold
+        if match.confidence < min_confidence:
+            logger.info(
+                "BUY suppressed for %s (%s): confidence %d < %d (market_outlook=%s)",
+                stock_code,
+                market.name,
+                match.confidence,
+                min_confidence,
+                outlook.value,
+            )
+            decision = TradeDecision(
+                action="HOLD",
+                confidence=match.confidence,
+                rationale=(
+                    f"BUY confidence {match.confidence} < {min_confidence} "
+                    f"(market_outlook={outlook.value})"
+                ),
+            )
+
     if decision.action == "HOLD":
         open_position = get_open_position(db_conn, stock_code, market.code)
         if open_position:
@@ -568,6 +621,7 @@ 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,
@@ -575,6 +629,8 @@ 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(
@@ -588,7 +644,22 @@ 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
         try:
             risk.validate_order(
                 current_pnl_pct=pnl_pct,
@@ -636,12 +707,24 @@ 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)
@@ -749,6 +832,9 @@ 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
@@ -1021,6 +1107,21 @@ 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
                 try:
                     risk.validate_order(
@@ -1077,12 +1178,23 @@ 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)
@@ -1246,10 +1358,18 @@ 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)
@@ -1260,7 +1380,7 @@ 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,
@@ -1701,6 +1821,9 @@ 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%
@@ -2043,6 +2166,7 @@ async def run(settings: Settings) -> None:
                                     stock_code,
                                     scan_candidates,
                                     settings,
+                                    buy_cooldown,
                                 )
                                 break  # Success — exit retry loop
                             except CircuitBreakerTripped as exc:

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

@@ -332,7 +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'
@@ -436,6 +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_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."""
@@ -2114,3 +2192,546 @@ def test_start_dashboard_server_enabled_starts_thread() -> None:
     assert thread == mock_thread
     mock_thread_cls.assert_called_once()
     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)
+# ---------------------------------------------------------------------------
+
+
+class TestMarketOutlookConfidenceThreshold:
+    """Tests for market_outlook-based BUY confidence suppression in trading_cycle."""
+
+    @pytest.fixture
+    def mock_broker(self) -> MagicMock:
+        broker = MagicMock()
+        broker.get_current_price = AsyncMock(return_value=(50000.0, 1.0, 0.0))
+        broker.get_balance = AsyncMock(
+            return_value={
+                "output2": [
+                    {
+                        "tot_evlu_amt": "10000000",
+                        "dnca_tot_amt": "5000000",
+                        "pchs_amt_smtl_amt": "9500000",
+                    }
+                ]
+            }
+        )
+        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_telegram(self) -> MagicMock:
+        telegram = MagicMock()
+        telegram.notify_trade_execution = AsyncMock()
+        telegram.notify_scenario_matched = AsyncMock()
+        telegram.notify_fat_finger = AsyncMock()
+        return telegram
+
+    def _make_buy_match_with_confidence(
+        self, confidence: int, stock_code: str = "005930"
+    ) -> ScenarioMatch:
+        from src.strategy.models import StockScenario
+        scenario = StockScenario(
+            condition=StockCondition(rsi_below=30),
+            action=ScenarioAction.BUY,
+            confidence=confidence,
+            allocation_pct=10.0,
+        )
+        return ScenarioMatch(
+            stock_code=stock_code,
+            matched_scenario=scenario,
+            action=ScenarioAction.BUY,
+            confidence=confidence,
+            rationale="Test buy",
+        )
+
+    def _make_playbook_with_outlook(
+        self, outlook_str: str, market: str = "KR"
+    ) -> DayPlaybook:
+        from src.strategy.models import MarketOutlook
+        outlook_map = {
+            "bearish": MarketOutlook.BEARISH,
+            "bullish": MarketOutlook.BULLISH,
+            "neutral": MarketOutlook.NEUTRAL,
+            "neutral_to_bullish": MarketOutlook.NEUTRAL_TO_BULLISH,
+            "neutral_to_bearish": MarketOutlook.NEUTRAL_TO_BEARISH,
+        }
+        return DayPlaybook(
+            date=date(2026, 2, 20),
+            market=market,
+            market_outlook=outlook_map[outlook_str],
+        )
+
+    @pytest.mark.asyncio
+    async def test_bearish_outlook_raises_buy_confidence_threshold(
+        self,
+        mock_broker: MagicMock,
+        mock_market: MagicMock,
+        mock_telegram: MagicMock,
+    ) -> None:
+        """BUY with confidence 85 should be suppressed to HOLD in bearish market."""
+        engine = MagicMock(spec=ScenarioEngine)
+        engine.evaluate = MagicMock(return_value=self._make_buy_match_with_confidence(85))
+        playbook = self._make_playbook_with_outlook("bearish")
+
+        decision_logger = MagicMock()
+        decision_logger.log_decision = MagicMock(return_value="decision-id")
+
+        with patch("src.main.log_trade"):
+            await trading_cycle(
+                broker=mock_broker,
+                overseas_broker=MagicMock(),
+                scenario_engine=engine,
+                playbook=playbook,
+                risk=MagicMock(),
+                db_conn=MagicMock(),
+                decision_logger=decision_logger,
+                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=mock_telegram,
+                market=mock_market,
+                stock_code="005930",
+                scan_candidates={},
+            )
+
+        # HOLD should be logged (not BUY) — check decision_logger was called with HOLD
+        call_args = decision_logger.log_decision.call_args
+        assert call_args is not None
+        assert call_args.kwargs["action"] == "HOLD"
+
+    @pytest.mark.asyncio
+    async def test_bearish_outlook_allows_high_confidence_buy(
+        self,
+        mock_broker: MagicMock,
+        mock_market: MagicMock,
+        mock_telegram: MagicMock,
+    ) -> None:
+        """BUY with confidence 92 should proceed in bearish market (threshold=90)."""
+        engine = MagicMock(spec=ScenarioEngine)
+        engine.evaluate = MagicMock(return_value=self._make_buy_match_with_confidence(92))
+        playbook = self._make_playbook_with_outlook("bearish")
+        risk = MagicMock()
+        risk.validate_order = MagicMock()
+
+        decision_logger = MagicMock()
+        decision_logger.log_decision = MagicMock(return_value="decision-id")
+
+        with patch("src.main.log_trade"):
+            await trading_cycle(
+                broker=mock_broker,
+                overseas_broker=MagicMock(),
+                scenario_engine=engine,
+                playbook=playbook,
+                risk=risk,
+                db_conn=MagicMock(),
+                decision_logger=decision_logger,
+                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=mock_telegram,
+                market=mock_market,
+                stock_code="005930",
+                scan_candidates={},
+            )
+
+        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_bullish_outlook_lowers_buy_confidence_threshold(
+        self,
+        mock_broker: MagicMock,
+        mock_market: MagicMock,
+        mock_telegram: MagicMock,
+    ) -> None:
+        """BUY with confidence 77 should proceed in bullish market (threshold=75)."""
+        engine = MagicMock(spec=ScenarioEngine)
+        engine.evaluate = MagicMock(return_value=self._make_buy_match_with_confidence(77))
+        playbook = self._make_playbook_with_outlook("bullish")
+        risk = MagicMock()
+        risk.validate_order = MagicMock()
+
+        decision_logger = MagicMock()
+        decision_logger.log_decision = MagicMock(return_value="decision-id")
+
+        with patch("src.main.log_trade"):
+            await trading_cycle(
+                broker=mock_broker,
+                overseas_broker=MagicMock(),
+                scenario_engine=engine,
+                playbook=playbook,
+                risk=risk,
+                db_conn=MagicMock(),
+                decision_logger=decision_logger,
+                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=mock_telegram,
+                market=mock_market,
+                stock_code="005930",
+                scan_candidates={},
+            )
+
+        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_bullish_outlook_suppresses_very_low_confidence_buy(
+        self,
+        mock_broker: MagicMock,
+        mock_market: MagicMock,
+        mock_telegram: MagicMock,
+    ) -> None:
+        """BUY with confidence 70 should be suppressed even in bullish market (threshold=75)."""
+        engine = MagicMock(spec=ScenarioEngine)
+        engine.evaluate = MagicMock(return_value=self._make_buy_match_with_confidence(70))
+        playbook = self._make_playbook_with_outlook("bullish")
+
+        decision_logger = MagicMock()
+        decision_logger.log_decision = MagicMock(return_value="decision-id")
+
+        with patch("src.main.log_trade"):
+            await trading_cycle(
+                broker=mock_broker,
+                overseas_broker=MagicMock(),
+                scenario_engine=engine,
+                playbook=playbook,
+                risk=MagicMock(),
+                db_conn=MagicMock(),
+                decision_logger=decision_logger,
+                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=mock_telegram,
+                market=mock_market,
+                stock_code="005930",
+                scan_candidates={},
+            )
+
+        call_args = decision_logger.log_decision.call_args
+        assert call_args is not None
+        assert call_args.kwargs["action"] == "HOLD"
+
+    @pytest.mark.asyncio
+    async def test_neutral_outlook_uses_default_threshold(
+        self,
+        mock_broker: MagicMock,
+        mock_market: MagicMock,
+        mock_telegram: MagicMock,
+    ) -> None:
+        """BUY with confidence 82 should proceed in neutral market (default=80)."""
+        engine = MagicMock(spec=ScenarioEngine)
+        engine.evaluate = MagicMock(return_value=self._make_buy_match_with_confidence(82))
+        playbook = self._make_playbook_with_outlook("neutral")
+        risk = MagicMock()
+        risk.validate_order = MagicMock()
+
+        decision_logger = MagicMock()
+        decision_logger.log_decision = MagicMock(return_value="decision-id")
+
+        with patch("src.main.log_trade"):
+            await trading_cycle(
+                broker=mock_broker,
+                overseas_broker=MagicMock(),
+                scenario_engine=engine,
+                playbook=playbook,
+                risk=risk,
+                db_conn=MagicMock(),
+                decision_logger=decision_logger,
+                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=mock_telegram,
+                market=mock_market,
+                stock_code="005930",
+                scan_candidates={},
+            )
+
+        call_args = decision_logger.log_decision.call_args
+        assert call_args is not None
+        assert call_args.kwargs["action"] == "BUY"

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."""