feat: use playbook allocation_pct in position sizing (#172)

- Add playbook_allocation_pct and scenario_confidence parameters to
  _determine_order_quantity() with playbook-based sizing taking priority
  over volatility-score fallback when provided
- Confidence scaling: confidence/80 multiplier (confidence 96 → 1.2x)
  clipped to [POSITION_MIN_ALLOCATION_PCT, POSITION_MAX_ALLOCATION_PCT]
- Pass matched_scenario.allocation_pct and match.confidence from
  trading_cycle so AI's allocation decisions reach order execution
- Add 4 new tests: playbook priority, confidence scaling, max clamp,
  and fallback behavior

Closes #172

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

src/db.py

@@ -237,28 +237,6 @@ def get_open_position(
     return {"decision_id": row[1], "price": row[2], "quantity": row[3]}
 
 
-def get_open_positions_by_market(
-    conn: sqlite3.Connection, market: str
-) -> list[str]:
-    """Return stock codes with a net positive position in the given market.
-
-    Uses net BUY - SELL quantity aggregation to avoid false positives from
-    the simpler "latest record is BUY" heuristic.  A stock is considered
-    open only when the bot's own recorded trades leave a positive net quantity.
-    """
-    cursor = conn.execute(
-        """
-        SELECT stock_code
-        FROM trades
-        WHERE market = ?
-        GROUP BY stock_code
-        HAVING SUM(CASE WHEN action = 'BUY' THEN quantity ELSE -quantity END) > 0
-        """,
-        (market,),
-    )
-    return [row[0] for row in cursor.fetchall()]
-
-
 def get_recent_symbols(
     conn: sqlite3.Connection, market: str, limit: int = 30
 ) -> list[str]:

src/main.py

@@ -32,7 +32,6 @@ from src.core.risk_manager import CircuitBreakerTripped, FatFingerRejected, Risk
 from src.db import (
     get_latest_buy_trade,
     get_open_position,
-    get_open_positions_by_market,
     get_recent_symbols,
     init_db,
     log_trade,
@@ -107,6 +106,82 @@ def _extract_symbol_from_holding(item: dict[str, Any]) -> str:
     return ""
 
 
+def _extract_held_codes_from_balance(
+    balance_data: dict[str, Any],
+    *,
+    is_domestic: bool,
+) -> list[str]:
+    """Return stock codes with a positive orderable quantity from a balance response.
+
+    Uses the broker's live output1 as the source of truth so that partial fills
+    and manual external trades are always reflected correctly.
+    """
+    output1 = balance_data.get("output1", [])
+    if isinstance(output1, dict):
+        output1 = [output1]
+    if not isinstance(output1, list):
+        return []
+
+    codes: list[str] = []
+    for holding in output1:
+        if not isinstance(holding, dict):
+            continue
+        code_key = "pdno" if is_domestic else "ovrs_pdno"
+        code = str(holding.get(code_key, "")).strip().upper()
+        if not code:
+            continue
+        if is_domestic:
+            qty = int(holding.get("ord_psbl_qty") or holding.get("hldg_qty") or 0)
+        else:
+            qty = int(holding.get("ovrs_cblc_qty") or holding.get("hldg_qty") or 0)
+        if qty > 0:
+            codes.append(code)
+    return codes
+
+
+def _extract_held_qty_from_balance(
+    balance_data: dict[str, Any],
+    stock_code: str,
+    *,
+    is_domestic: bool,
+) -> int:
+    """Extract the broker-confirmed orderable quantity for a stock.
+
+    Uses the broker's live balance response (output1) as the source of truth
+    rather than the local DB, because DB records reflect order quantity which
+    may differ from actual fill quantity due to partial fills.
+
+    Domestic fields (VTTC8434R output1):
+        pdno          — 종목코드
+        ord_psbl_qty  — 주문가능수량 (preferred: excludes unsettled)
+        hldg_qty      — 보유수량 (fallback)
+
+    Overseas fields (output1):
+        ovrs_pdno     — 종목코드
+        ovrs_cblc_qty — 해외잔고수량 (preferred)
+        hldg_qty      — 보유수량 (fallback)
+    """
+    output1 = balance_data.get("output1", [])
+    if isinstance(output1, dict):
+        output1 = [output1]
+    if not isinstance(output1, list):
+        return 0
+
+    for holding in output1:
+        if not isinstance(holding, dict):
+            continue
+        code_key = "pdno" if is_domestic else "ovrs_pdno"
+        held_code = str(holding.get(code_key, "")).strip().upper()
+        if held_code != stock_code.strip().upper():
+            continue
+        if is_domestic:
+            qty = int(holding.get("ord_psbl_qty") or holding.get("hldg_qty") or 0)
+        else:
+            qty = int(holding.get("ovrs_cblc_qty") or holding.get("hldg_qty") or 0)
+        return qty
+    return 0
+
+
 def _determine_order_quantity(
     *,
     action: str,
@@ -114,16 +189,40 @@ def _determine_order_quantity(
     total_cash: float,
     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."""
-    if action != "BUY":
-        return 1
+    """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:
         return 0
 
     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))
@@ -388,8 +487,10 @@ async def trading_cycle(
             if entry_price > 0:
                 loss_pct = (current_price - entry_price) / entry_price * 100
                 stop_loss_threshold = -2.0
+                take_profit_threshold = 3.0
                 if stock_playbook and stock_playbook.scenarios:
                     stop_loss_threshold = stock_playbook.scenarios[0].stop_loss_pct
+                    take_profit_threshold = stock_playbook.scenarios[0].take_profit_pct
 
                 if loss_pct <= stop_loss_threshold:
                     decision = TradeDecision(
@@ -407,6 +508,22 @@ async def trading_cycle(
                         loss_pct,
                         stop_loss_threshold,
                     )
+                elif loss_pct >= take_profit_threshold:
+                    decision = TradeDecision(
+                        action="SELL",
+                        confidence=90,
+                        rationale=(
+                            f"Take-profit triggered ({loss_pct:.2f}% >= "
+                            f"{take_profit_threshold:.2f}%)"
+                        ),
+                    )
+                    logger.info(
+                        "Take-profit override for %s (%s): %.2f%% >= %.2f%%",
+                        stock_code,
+                        market.name,
+                        loss_pct,
+                        take_profit_threshold,
+                    )
     logger.info(
         "Decision for %s (%s): %s (confidence=%d)",
         stock_code,
@@ -467,12 +584,23 @@ async def trading_cycle(
     trade_price = current_price
     trade_pnl = 0.0
     if decision.action in ("BUY", "SELL"):
+        broker_held_qty = (
+            _extract_held_qty_from_balance(
+                balance_data, stock_code, is_domestic=market.is_domestic
+            )
+            if decision.action == "SELL"
+            else 0
+        )
+        matched_scenario = match.matched_scenario
         quantity = _determine_order_quantity(
             action=decision.action,
             current_price=current_price,
             total_cash=total_cash,
             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(
@@ -892,12 +1020,20 @@ async def run_daily_session(
             trade_pnl = 0.0
             order_succeeded = True
             if decision.action in ("BUY", "SELL"):
+                daily_broker_held_qty = (
+                    _extract_held_qty_from_balance(
+                        balance_data, stock_code, is_domestic=market.is_domestic
+                    )
+                    if decision.action == "SELL"
+                    else 0
+                )
                 quantity = _determine_order_quantity(
                     action=decision.action,
                     current_price=stock_data["current_price"],
                     total_cash=total_cash,
                     candidate=candidate_map.get(stock_code),
                     settings=settings,
+                    broker_held_qty=daily_broker_held_qty,
                 )
                 if quantity <= 0:
                     logger.info(
@@ -1864,22 +2000,38 @@ async def run(settings: Settings) -> None:
                         except Exception as exc:
                             logger.error("Smart Scanner failed for %s: %s", market.name, exc)
 
-                    # Get active stocks from scanner (dynamic, no static fallback)
-                    # Also include current holdings so stop-loss / take-profit
-                    # can trigger even when a position drops off the scanner.
+                    # Get active stocks from scanner (dynamic, no static fallback).
+                    # Also include currently-held positions so stop-loss /
+                    # take-profit can fire even when a holding drops off the
+                    # scanner.  Broker balance is the source of truth here —
+                    # unlike the local DB it reflects actual fills and any
+                    # manual trades done outside the bot.
                     scanner_codes = active_stocks.get(market.code, [])
-                    held_codes = get_open_positions_by_market(db_conn, market.code)
-                    # Union: scanner candidates first, then holdings not already present.
-                    # dict.fromkeys preserves insertion order and removes duplicates.
-                    stock_codes = list(dict.fromkeys(scanner_codes + held_codes))
-                    if held_codes:
-                        new_held = [c for c in held_codes if c not in set(scanner_codes)]
-                        if new_held:
-                            logger.info(
-                                "Holdings added to loop for %s (not in scanner): %s",
-                                market.name,
-                                new_held,
+                    try:
+                        if market.is_domestic:
+                            held_balance = await broker.get_balance()
+                        else:
+                            held_balance = await overseas_broker.get_overseas_balance(
+                                market.exchange_code
                             )
+                        held_codes = _extract_held_codes_from_balance(
+                            held_balance, is_domestic=market.is_domestic
+                        )
+                    except Exception as exc:
+                        logger.warning(
+                            "Failed to fetch holdings for %s: %s — skipping holdings merge",
+                            market.name, exc,
+                        )
+                        held_codes = []
+
+                    stock_codes = list(dict.fromkeys(scanner_codes + held_codes))
+                    extra_held = [c for c in held_codes if c not in set(scanner_codes)]
+                    if extra_held:
+                        logger.info(
+                            "Holdings added to loop for %s (not in scanner): %s",
+                            market.name, extra_held,
+                        )
+
                     if not stock_codes:
                         logger.debug("No active stocks for market %s", market.code)
                         continue

tests/test_db.py

@@ -1,6 +1,6 @@
 """Tests for database helper functions."""
 
-from src.db import get_open_position, get_open_positions_by_market, init_db, log_trade
+from src.db import get_open_position, init_db, log_trade
 
 
 def test_get_open_position_returns_latest_buy() -> None:
@@ -58,87 +58,3 @@ def test_get_open_position_returns_none_when_latest_is_sell() -> None:
 def test_get_open_position_returns_none_when_no_trades() -> None:
     conn = init_db(":memory:")
     assert get_open_position(conn, "AAPL", "US_NASDAQ") is None
-
-
-# --- get_open_positions_by_market tests ---
-
-
-def test_get_open_positions_by_market_returns_net_positive_stocks() -> None:
-    """Stocks with net BUY quantity > 0 are included."""
-    conn = init_db(":memory:")
-    log_trade(
-        conn=conn, stock_code="005930", action="BUY", confidence=90,
-        rationale="entry", quantity=5, price=70000.0, market="KR",
-        exchange_code="KRX", decision_id="d1",
-    )
-    log_trade(
-        conn=conn, stock_code="000660", action="BUY", confidence=85,
-        rationale="entry", quantity=3, price=100000.0, market="KR",
-        exchange_code="KRX", decision_id="d2",
-    )
-
-    result = get_open_positions_by_market(conn, "KR")
-    assert set(result) == {"005930", "000660"}
-
-
-def test_get_open_positions_by_market_excludes_fully_sold_stocks() -> None:
-    """Stocks where BUY qty == SELL qty are excluded (net qty = 0)."""
-    conn = init_db(":memory:")
-    log_trade(
-        conn=conn, stock_code="005930", action="BUY", confidence=90,
-        rationale="entry", quantity=3, price=70000.0, market="KR",
-        exchange_code="KRX", decision_id="d1",
-    )
-    log_trade(
-        conn=conn, stock_code="005930", action="SELL", confidence=95,
-        rationale="exit", quantity=3, price=71000.0, market="KR",
-        exchange_code="KRX", decision_id="d2",
-    )
-
-    result = get_open_positions_by_market(conn, "KR")
-    assert "005930" not in result
-
-
-def test_get_open_positions_by_market_includes_partially_sold_stocks() -> None:
-    """Stocks with partial SELL (net qty > 0) are still included."""
-    conn = init_db(":memory:")
-    log_trade(
-        conn=conn, stock_code="005930", action="BUY", confidence=90,
-        rationale="entry", quantity=5, price=70000.0, market="KR",
-        exchange_code="KRX", decision_id="d1",
-    )
-    log_trade(
-        conn=conn, stock_code="005930", action="SELL", confidence=95,
-        rationale="partial exit", quantity=2, price=71000.0, market="KR",
-        exchange_code="KRX", decision_id="d2",
-    )
-
-    result = get_open_positions_by_market(conn, "KR")
-    assert "005930" in result
-
-
-def test_get_open_positions_by_market_is_market_scoped() -> None:
-    """Only stocks from the specified market are returned."""
-    conn = init_db(":memory:")
-    log_trade(
-        conn=conn, stock_code="005930", action="BUY", confidence=90,
-        rationale="entry", quantity=3, price=70000.0, market="KR",
-        exchange_code="KRX", decision_id="d1",
-    )
-    log_trade(
-        conn=conn, stock_code="AAPL", action="BUY", confidence=85,
-        rationale="entry", quantity=2, price=200.0, market="NASD",
-        exchange_code="NAS", decision_id="d2",
-    )
-
-    kr_result = get_open_positions_by_market(conn, "KR")
-    nasd_result = get_open_positions_by_market(conn, "NASD")
-
-    assert kr_result == ["005930"]
-    assert nasd_result == ["AAPL"]
-
-
-def test_get_open_positions_by_market_returns_empty_when_no_trades() -> None:
-    """Empty list returned when no trades exist for the market."""
-    conn = init_db(":memory:")
-    assert get_open_positions_by_market(conn, "KR") == []

tests/test_main.py

@@ -14,6 +14,9 @@ from src.evolution.scorecard import DailyScorecard
 from src.logging.decision_logger import DecisionLogger
 from src.main import (
     _apply_dashboard_flag,
+    _determine_order_quantity,
+    _extract_held_codes_from_balance,
+    _extract_held_qty_from_balance,
     _handle_market_close,
     _run_context_scheduler,
     _run_evolution_loop,
@@ -68,6 +71,219 @@ def _make_sell_match(stock_code: str = "005930") -> ScenarioMatch:
     )
 
 
+class TestExtractHeldQtyFromBalance:
+    """Tests for _extract_held_qty_from_balance()."""
+
+    def _domestic_balance(self, stock_code: str, ord_psbl_qty: int) -> dict:
+        return {
+            "output1": [{"pdno": stock_code, "ord_psbl_qty": str(ord_psbl_qty)}],
+            "output2": [{"dnca_tot_amt": "1000000"}],
+        }
+
+    def test_domestic_returns_ord_psbl_qty(self) -> None:
+        balance = self._domestic_balance("005930", 7)
+        assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 7
+
+    def test_domestic_fallback_to_hldg_qty(self) -> None:
+        balance = {"output1": [{"pdno": "005930", "hldg_qty": "3"}]}
+        assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 3
+
+    def test_domestic_returns_zero_when_not_found(self) -> None:
+        balance = self._domestic_balance("005930", 5)
+        assert _extract_held_qty_from_balance(balance, "000660", is_domestic=True) == 0
+
+    def test_domestic_returns_zero_when_output1_empty(self) -> None:
+        balance = {"output1": [], "output2": [{}]}
+        assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 0
+
+    def test_overseas_returns_ovrs_cblc_qty(self) -> None:
+        balance = {"output1": [{"ovrs_pdno": "AAPL", "ovrs_cblc_qty": "10"}]}
+        assert _extract_held_qty_from_balance(balance, "AAPL", is_domestic=False) == 10
+
+    def test_overseas_fallback_to_hldg_qty(self) -> None:
+        balance = {"output1": [{"ovrs_pdno": "AAPL", "hldg_qty": "4"}]}
+        assert _extract_held_qty_from_balance(balance, "AAPL", is_domestic=False) == 4
+
+    def test_case_insensitive_match(self) -> None:
+        balance = {"output1": [{"pdno": "005930", "ord_psbl_qty": "2"}]}
+        assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 2
+
+
+class TestExtractHeldCodesFromBalance:
+    """Tests for _extract_held_codes_from_balance()."""
+
+    def test_returns_codes_with_positive_qty(self) -> None:
+        balance = {
+            "output1": [
+                {"pdno": "005930", "ord_psbl_qty": "5"},
+                {"pdno": "000660", "ord_psbl_qty": "3"},
+            ]
+        }
+        result = _extract_held_codes_from_balance(balance, is_domestic=True)
+        assert set(result) == {"005930", "000660"}
+
+    def test_excludes_zero_qty_holdings(self) -> None:
+        balance = {
+            "output1": [
+                {"pdno": "005930", "ord_psbl_qty": "0"},
+                {"pdno": "000660", "ord_psbl_qty": "2"},
+            ]
+        }
+        result = _extract_held_codes_from_balance(balance, is_domestic=True)
+        assert "005930" not in result
+        assert "000660" in result
+
+    def test_returns_empty_when_output1_missing(self) -> None:
+        balance: dict = {}
+        assert _extract_held_codes_from_balance(balance, is_domestic=True) == []
+
+    def test_overseas_uses_ovrs_pdno(self) -> None:
+        balance = {"output1": [{"ovrs_pdno": "AAPL", "ovrs_cblc_qty": "3"}]}
+        result = _extract_held_codes_from_balance(balance, is_domestic=False)
+        assert result == ["AAPL"]
+
+
+class TestDetermineOrderQuantity:
+    """Test _determine_order_quantity() — SELL uses broker_held_qty."""
+
+    def test_sell_returns_broker_held_qty(self) -> None:
+        result = _determine_order_quantity(
+            action="SELL",
+            current_price=105.0,
+            total_cash=50000.0,
+            candidate=None,
+            settings=None,
+            broker_held_qty=7,
+        )
+        assert result == 7
+
+    def test_sell_returns_zero_when_broker_qty_zero(self) -> None:
+        result = _determine_order_quantity(
+            action="SELL",
+            current_price=105.0,
+            total_cash=50000.0,
+            candidate=None,
+            settings=None,
+            broker_held_qty=0,
+        )
+        assert result == 0
+
+    def test_buy_without_position_sizing_returns_one(self) -> None:
+        result = _determine_order_quantity(
+            action="BUY",
+            current_price=50000.0,
+            total_cash=1000000.0,
+            candidate=None,
+            settings=None,
+        )
+        assert result == 1
+
+    def test_buy_with_zero_cash_returns_zero(self) -> None:
+        result = _determine_order_quantity(
+            action="BUY",
+            current_price=50000.0,
+            total_cash=0.0,
+            candidate=None,
+            settings=None,
+        )
+        assert result == 0
+
+    def test_buy_with_position_sizing_calculates_correctly(self) -> None:
+        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
+        # 1,000,000 * 10% = 100,000 budget // 50,000 price = 2 shares
+        result = _determine_order_quantity(
+            action="BUY",
+            current_price=50000.0,
+            total_cash=1000000.0,
+            candidate=None,
+            settings=settings,
+        )
+        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."""
 
@@ -1240,13 +1456,14 @@ async def test_sell_updates_original_buy_decision_outcome() -> None:
     broker.get_current_price = AsyncMock(return_value=(120.0, 0.0, 0.0))
     broker.get_balance = AsyncMock(
         return_value={
+            "output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
             "output2": [
                 {
                     "tot_evlu_amt": "100000",
                     "dnca_tot_amt": "10000",
                     "pchs_amt_smtl_amt": "90000",
                 }
-            ]
+            ],
         }
     )
     broker.send_order = AsyncMock(return_value={"msg1": "OK"})
@@ -1330,13 +1547,14 @@ async def test_hold_overridden_to_sell_when_stop_loss_triggered() -> None:
     broker.get_current_price = AsyncMock(return_value=(95.0, -5.0, 0.0))
     broker.get_balance = AsyncMock(
         return_value={
+            "output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
             "output2": [
                 {
                     "tot_evlu_amt": "100000",
                     "dnca_tot_amt": "10000",
                     "pchs_amt_smtl_amt": "90000",
                 }
-            ]
+            ],
         }
     )
     broker.send_order = AsyncMock(return_value={"msg1": "OK"})
@@ -1396,6 +1614,318 @@ async def test_hold_overridden_to_sell_when_stop_loss_triggered() -> None:
     assert broker.send_order.call_args.kwargs["order_type"] == "SELL"
 
 
+@pytest.mark.asyncio
+async def test_hold_overridden_to_sell_when_take_profit_triggered() -> None:
+    """HOLD decision should be overridden to SELL when take-profit threshold is reached."""
+    db_conn = init_db(":memory:")
+    decision_logger = DecisionLogger(db_conn)
+
+    buy_decision_id = decision_logger.log_decision(
+        stock_code="005930",
+        market="KR",
+        exchange_code="KRX",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        context_snapshot={},
+        input_data={},
+    )
+    log_trade(
+        conn=db_conn,
+        stock_code="005930",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        quantity=1,
+        price=100.0,
+        market="KR",
+        exchange_code="KRX",
+        decision_id=buy_decision_id,
+    )
+
+    broker = MagicMock()
+    # Current price 106.0 → +6% gain, above take_profit_pct=3.0
+    broker.get_current_price = AsyncMock(return_value=(106.0, 6.0, 0.0))
+    broker.get_balance = AsyncMock(
+        return_value={
+            "output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
+            "output2": [
+                {
+                    "tot_evlu_amt": "100000",
+                    "dnca_tot_amt": "10000",
+                    "pchs_amt_smtl_amt": "90000",
+                }
+            ],
+        }
+    )
+    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
+
+    scenario = StockScenario(
+        condition=StockCondition(rsi_below=30),
+        action=ScenarioAction.BUY,
+        confidence=88,
+        stop_loss_pct=-2.0,
+        take_profit_pct=3.0,
+        rationale="take profit policy",
+    )
+    playbook = DayPlaybook(
+        date=date(2026, 2, 8),
+        market="KR",
+        stock_playbooks=[
+            {"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
+        ],
+    )
+    engine = MagicMock(spec=ScenarioEngine)
+    engine.evaluate = MagicMock(return_value=_make_hold_match())
+
+    market = MagicMock()
+    market.name = "Korea"
+    market.code = "KR"
+    market.exchange_code = "KRX"
+    market.is_domestic = True
+
+    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=MagicMock(),
+        scenario_engine=engine,
+        playbook=playbook,
+        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="005930",
+        scan_candidates={},
+    )
+
+    broker.send_order.assert_called_once()
+    assert broker.send_order.call_args.kwargs["order_type"] == "SELL"
+
+
+@pytest.mark.asyncio
+async def test_hold_not_overridden_when_between_stop_loss_and_take_profit() -> None:
+    """HOLD should remain HOLD when P&L is within stop-loss and take-profit bounds."""
+    db_conn = init_db(":memory:")
+    decision_logger = DecisionLogger(db_conn)
+
+    buy_decision_id = decision_logger.log_decision(
+        stock_code="005930",
+        market="KR",
+        exchange_code="KRX",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        context_snapshot={},
+        input_data={},
+    )
+    log_trade(
+        conn=db_conn,
+        stock_code="005930",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        quantity=1,
+        price=100.0,
+        market="KR",
+        exchange_code="KRX",
+        decision_id=buy_decision_id,
+    )
+
+    broker = MagicMock()
+    # Current price 101.0 → +1% gain, within [-2%, +3%] range
+    broker.get_current_price = AsyncMock(return_value=(101.0, 1.0, 0.0))
+    broker.get_balance = AsyncMock(
+        return_value={
+            "output2": [
+                {
+                    "tot_evlu_amt": "100000",
+                    "dnca_tot_amt": "10000",
+                    "pchs_amt_smtl_amt": "90000",
+                }
+            ]
+        }
+    )
+    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
+
+    scenario = StockScenario(
+        condition=StockCondition(rsi_below=30),
+        action=ScenarioAction.BUY,
+        confidence=88,
+        stop_loss_pct=-2.0,
+        take_profit_pct=3.0,
+        rationale="within range policy",
+    )
+    playbook = DayPlaybook(
+        date=date(2026, 2, 8),
+        market="KR",
+        stock_playbooks=[
+            {"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
+        ],
+    )
+    engine = MagicMock(spec=ScenarioEngine)
+    engine.evaluate = MagicMock(return_value=_make_hold_match())
+
+    market = MagicMock()
+    market.name = "Korea"
+    market.code = "KR"
+    market.exchange_code = "KRX"
+    market.is_domestic = True
+
+    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=MagicMock(),
+        scenario_engine=engine,
+        playbook=playbook,
+        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="005930",
+        scan_candidates={},
+    )
+
+    broker.send_order.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_sell_order_uses_broker_balance_qty_not_db() -> None:
+    """SELL quantity must come from broker balance output1, not DB.
+
+    The DB records order quantity which may differ from actual fill quantity.
+    This test verifies that we use the broker-confirmed orderable quantity.
+    """
+    db_conn = init_db(":memory:")
+    decision_logger = DecisionLogger(db_conn)
+
+    buy_decision_id = decision_logger.log_decision(
+        stock_code="005930",
+        market="KR",
+        exchange_code="KRX",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        context_snapshot={},
+        input_data={},
+    )
+    # DB records 10 shares ordered — but only 5 actually filled (partial fill scenario)
+    log_trade(
+        conn=db_conn,
+        stock_code="005930",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        quantity=10,  # ordered quantity (may differ from fill)
+        price=100.0,
+        market="KR",
+        exchange_code="KRX",
+        decision_id=buy_decision_id,
+    )
+
+    broker = MagicMock()
+    # Stop-loss triggers (price dropped below -2%)
+    broker.get_current_price = AsyncMock(return_value=(95.0, -5.0, 0.0))
+    broker.get_balance = AsyncMock(
+        return_value={
+            # Broker confirms only 5 shares are actually orderable (partial fill)
+            "output1": [{"pdno": "005930", "ord_psbl_qty": "5"}],
+            "output2": [
+                {
+                    "tot_evlu_amt": "100000",
+                    "dnca_tot_amt": "10000",
+                    "pchs_amt_smtl_amt": "90000",
+                }
+            ],
+        }
+    )
+    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
+
+    scenario = StockScenario(
+        condition=StockCondition(rsi_below=30),
+        action=ScenarioAction.BUY,
+        confidence=88,
+        stop_loss_pct=-2.0,
+        rationale="stop loss policy",
+    )
+    playbook = DayPlaybook(
+        date=date(2026, 2, 8),
+        market="KR",
+        stock_playbooks=[
+            {"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
+        ],
+    )
+    engine = MagicMock(spec=ScenarioEngine)
+    engine.evaluate = MagicMock(return_value=_make_hold_match())
+
+    market = MagicMock()
+    market.name = "Korea"
+    market.code = "KR"
+    market.exchange_code = "KRX"
+    market.is_domestic = True
+
+    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=MagicMock(),
+        scenario_engine=engine,
+        playbook=playbook,
+        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="005930",
+        scan_candidates={},
+    )
+
+    broker.send_order.assert_called_once()
+    call_kwargs = broker.send_order.call_args.kwargs
+    assert call_kwargs["order_type"] == "SELL"
+    # Must use broker-confirmed qty (5), NOT DB-recorded ordered qty (10)
+    assert call_kwargs["quantity"] == 5
+
+
 @pytest.mark.asyncio
 async def test_handle_market_close_runs_daily_review_flow() -> None:
     """Market close should aggregate, create scorecard, lessons, and notify."""