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

Reviewed-on: #227

src/main.py

@@ -908,18 +908,30 @@ async def run_daily_session(
     telegram: TelegramClient,
     settings: Settings,
     smart_scanner: SmartVolatilityScanner | None = None,
-) -> None:
+    daily_start_eval: float = 0.0,
+) -> float:
     """Execute one daily trading session.
 
     V2 proactive strategy: 1 Gemini call for playbook generation,
     then local scenario evaluation per stock (0 API calls).
+
+    Args:
+        daily_start_eval: Portfolio evaluation at the start of the trading day.
+            Used to compute intra-day P&L for the Circuit Breaker.
+            Pass 0.0 on the first session of each day; the function will set
+            it from the first balance query and return it for subsequent
+            sessions.
+
+    Returns:
+        The daily_start_eval value that should be forwarded to the next
+        session of the same trading day.
     """
     # Get currently open markets
     open_markets = get_open_markets(settings.enabled_market_list)
 
     if not open_markets:
         logger.info("No markets open for this session")
-        return
+        return daily_start_eval
 
     logger.info("Starting daily trading session for %d markets", len(open_markets))
 
@@ -1121,12 +1133,27 @@ async def run_daily_session(
             ):
                 total_cash = settings.PAPER_OVERSEAS_CASH
 
-        # Calculate daily P&L %
-        pnl_pct = (
-            ((total_eval - purchase_total) / purchase_total * 100)
-            if purchase_total > 0
-            else 0.0
-        )
+        # Capture the day's opening portfolio value on the first market processed
+        # in this session.  Used to compute intra-day P&L for the CB instead of
+        # the cumulative purchase_total which spans the entire account history.
+        if daily_start_eval <= 0 and total_eval > 0:
+            daily_start_eval = total_eval
+            logger.info(
+                "Daily CB baseline set: total_eval=%.2f (first balance of the day)",
+                daily_start_eval,
+            )
+
+        # Daily P&L: compare current eval vs start-of-day eval.
+        # Falls back to purchase_total if daily_start_eval is unavailable (e.g. paper
+        # mode where balance API returns 0 for all values).
+        if daily_start_eval > 0:
+            pnl_pct = (total_eval - daily_start_eval) / daily_start_eval * 100
+        else:
+            pnl_pct = (
+                ((total_eval - purchase_total) / purchase_total * 100)
+                if purchase_total > 0
+                else 0.0
+            )
         portfolio_data = {
             "portfolio_pnl_pct": pnl_pct,
             "total_cash": total_cash,
@@ -1395,6 +1422,7 @@ async def run_daily_session(
             )
 
     logger.info("Daily trading session completed")
+    return daily_start_eval
 
 
 async def _handle_market_close(
@@ -2030,13 +2058,26 @@ async def run(settings: Settings) -> None:
 
             session_interval = settings.SESSION_INTERVAL_HOURS * 3600  # Convert to seconds
 
+            # daily_start_eval: portfolio eval captured at the first session of each
+            # trading day.  Reset on calendar-date change so the CB measures only
+            # today's drawdown, not cumulative account history.
+            _cb_daily_start_eval: float = 0.0
+            _cb_last_date: str = ""
+
             while not shutdown.is_set():
                 # Wait for trading to be unpaused
                 await pause_trading.wait()
                 _run_context_scheduler(context_scheduler, now=datetime.now(UTC))
 
+                # Reset intra-day CB baseline on a new calendar date
+                today_str = datetime.now(UTC).date().isoformat()
+                if today_str != _cb_last_date:
+                    _cb_last_date = today_str
+                    _cb_daily_start_eval = 0.0
+                    logger.info("New trading day %s — daily CB baseline reset", today_str)
+
                 try:
-                    await run_daily_session(
+                    _cb_daily_start_eval = await run_daily_session(
                         broker,
                         overseas_broker,
                         scenario_engine,
@@ -2050,6 +2091,7 @@ async def run(settings: Settings) -> None:
                         telegram,
                         settings,
                         smart_scanner=smart_scanner,
+                        daily_start_eval=_cb_daily_start_eval,
                     )
                 except CircuitBreakerTripped:
                     logger.critical("Circuit breaker tripped — shutting down")

tests/test_main.py

@@ -22,6 +22,7 @@ from src.main import (
     _run_context_scheduler,
     _run_evolution_loop,
     _start_dashboard_server,
+    run_daily_session,
     safe_float,
     trading_cycle,
 )
@@ -3271,3 +3272,243 @@ class TestRetryConnection:
             await _retry_connection(bad_input, label="bad")
 
         assert call_count == 1  # No retry for non-ConnectionError
+
+
+# ---------------------------------------------------------------------------
+# run_daily_session — daily CB baseline (daily_start_eval) tests (issue #207)
+# ---------------------------------------------------------------------------
+
+
+class TestDailyCBBaseline:
+    """Tests for run_daily_session's daily_start_eval (CB baseline) behaviour.
+
+    Issue #207: CB P&L should be computed relative to the portfolio value at
+    the start of each trading day, not the cumulative purchase_total.
+    """
+
+    def _make_settings(self) -> Settings:
+        return Settings(
+            KIS_APP_KEY="test-key",
+            KIS_APP_SECRET="test-secret",
+            KIS_ACCOUNT_NO="12345678-01",
+            GEMINI_API_KEY="test-gemini",
+            MODE="paper",
+            PAPER_OVERSEAS_CASH=0,
+        )
+
+    def _make_domestic_balance(
+        self, tot_evlu_amt: float = 0.0, dnca_tot_amt: float = 50000.0
+    ) -> dict:
+        return {
+            "output1": [],
+            "output2": [
+                {
+                    "tot_evlu_amt": str(tot_evlu_amt),
+                    "dnca_tot_amt": str(dnca_tot_amt),
+                    "pchs_amt_smtl_amt": "40000.0",
+                }
+            ],
+        }
+
+    @pytest.mark.asyncio
+    async def test_returns_daily_start_eval_when_no_markets_open(self) -> None:
+        """run_daily_session returns the unchanged daily_start_eval when no markets are open."""
+        with patch("src.main.get_open_markets", return_value=[]):
+            result = await run_daily_session(
+                broker=MagicMock(),
+                overseas_broker=MagicMock(),
+                scenario_engine=MagicMock(),
+                playbook_store=MagicMock(),
+                pre_market_planner=MagicMock(),
+                risk=MagicMock(),
+                db_conn=init_db(":memory:"),
+                decision_logger=MagicMock(),
+                context_store=MagicMock(),
+                criticality_assessor=MagicMock(),
+                telegram=MagicMock(),
+                settings=self._make_settings(),
+                smart_scanner=None,
+                daily_start_eval=12345.0,
+            )
+        assert result == 12345.0
+
+    @pytest.mark.asyncio
+    async def test_returns_zero_when_no_markets_and_no_baseline(self) -> None:
+        """run_daily_session returns 0.0 when no markets are open and daily_start_eval=0."""
+        with patch("src.main.get_open_markets", return_value=[]):
+            result = await run_daily_session(
+                broker=MagicMock(),
+                overseas_broker=MagicMock(),
+                scenario_engine=MagicMock(),
+                playbook_store=MagicMock(),
+                pre_market_planner=MagicMock(),
+                risk=MagicMock(),
+                db_conn=init_db(":memory:"),
+                decision_logger=MagicMock(),
+                context_store=MagicMock(),
+                criticality_assessor=MagicMock(),
+                telegram=MagicMock(),
+                settings=self._make_settings(),
+                smart_scanner=None,
+                daily_start_eval=0.0,
+            )
+        assert result == 0.0
+
+    @pytest.mark.asyncio
+    async def test_captures_total_eval_as_baseline_on_first_session(self) -> None:
+        """When daily_start_eval=0 and balance returns a positive total_eval, the returned
+        value equals total_eval (the captured baseline for the day)."""
+        from src.analysis.smart_scanner import ScanCandidate
+
+        settings = self._make_settings()
+        broker = MagicMock()
+        # Domestic balance: tot_evlu_amt=55000
+        broker.get_balance = AsyncMock(
+            return_value=self._make_domestic_balance(tot_evlu_amt=55000.0)
+        )
+        # Price data for the stock
+        broker.get_current_price = AsyncMock(
+            return_value=(100.0, 1.5, 100.0)
+        )
+
+        market = MagicMock()
+        market.name = "KR"
+        market.code = "KR"
+        market.exchange_code = "KRX"
+        market.is_domestic = True
+        market.timezone = __import__("zoneinfo").ZoneInfo("Asia/Seoul")
+
+        smart_scanner = MagicMock()
+        smart_scanner.scan = AsyncMock(
+            return_value=[
+                ScanCandidate(
+                    stock_code="005930",
+                    name="Samsung",
+                    price=100.0,
+                    volume=1_000_000.0,
+                    volume_ratio=2.5,
+                    rsi=45.0,
+                    signal="momentum",
+                    score=80.0,
+                )
+            ]
+        )
+
+        playbook_store = MagicMock()
+        playbook_store.load = MagicMock(return_value=_make_playbook("KR"))
+
+        scenario_engine = MagicMock(spec=ScenarioEngine)
+        scenario_engine.evaluate = MagicMock(return_value=_make_hold_match("005930"))
+
+        risk = MagicMock()
+        risk.check_circuit_breaker = MagicMock()
+        risk.check_fat_finger = MagicMock()
+
+        telegram = MagicMock()
+        telegram.notify_trade_execution = AsyncMock()
+        telegram.notify_scenario_matched = AsyncMock()
+
+        decision_logger = MagicMock()
+        decision_logger.log_decision = MagicMock(return_value="d1")
+
+        async def _passthrough(fn, *a, label: str = "", **kw):  # type: ignore[override]
+            return await fn(*a, **kw)
+
+        with patch("src.main.get_open_markets", return_value=[market]), \
+             patch("src.main._retry_connection", new=_passthrough):
+            result = await run_daily_session(
+                broker=broker,
+                overseas_broker=MagicMock(),
+                scenario_engine=scenario_engine,
+                playbook_store=playbook_store,
+                pre_market_planner=MagicMock(),
+                risk=risk,
+                db_conn=init_db(":memory:"),
+                decision_logger=decision_logger,
+                context_store=MagicMock(),
+                criticality_assessor=MagicMock(),
+                telegram=telegram,
+                settings=settings,
+                smart_scanner=smart_scanner,
+                daily_start_eval=0.0,
+            )
+
+        assert result == 55000.0  # captured from tot_evlu_amt
+
+    @pytest.mark.asyncio
+    async def test_does_not_overwrite_existing_baseline(self) -> None:
+        """When daily_start_eval > 0, it must not be overwritten even if balance returns
+        a different value (baseline is fixed at the start of each trading day)."""
+        from src.analysis.smart_scanner import ScanCandidate
+
+        settings = self._make_settings()
+        broker = MagicMock()
+        # Balance reports a different eval value (market moved during the day)
+        broker.get_balance = AsyncMock(
+            return_value=self._make_domestic_balance(tot_evlu_amt=58000.0)
+        )
+        broker.get_current_price = AsyncMock(return_value=(100.0, 1.5, 100.0))
+
+        market = MagicMock()
+        market.name = "KR"
+        market.code = "KR"
+        market.exchange_code = "KRX"
+        market.is_domestic = True
+        market.timezone = __import__("zoneinfo").ZoneInfo("Asia/Seoul")
+
+        smart_scanner = MagicMock()
+        smart_scanner.scan = AsyncMock(
+            return_value=[
+                ScanCandidate(
+                    stock_code="005930",
+                    name="Samsung",
+                    price=100.0,
+                    volume=1_000_000.0,
+                    volume_ratio=2.5,
+                    rsi=45.0,
+                    signal="momentum",
+                    score=80.0,
+                )
+            ]
+        )
+
+        playbook_store = MagicMock()
+        playbook_store.load = MagicMock(return_value=_make_playbook("KR"))
+
+        scenario_engine = MagicMock(spec=ScenarioEngine)
+        scenario_engine.evaluate = MagicMock(return_value=_make_hold_match("005930"))
+
+        risk = MagicMock()
+        risk.check_circuit_breaker = MagicMock()
+
+        telegram = MagicMock()
+        telegram.notify_trade_execution = AsyncMock()
+        telegram.notify_scenario_matched = AsyncMock()
+
+        decision_logger = MagicMock()
+        decision_logger.log_decision = MagicMock(return_value="d1")
+
+        async def _passthrough(fn, *a, label: str = "", **kw):  # type: ignore[override]
+            return await fn(*a, **kw)
+
+        with patch("src.main.get_open_markets", return_value=[market]), \
+             patch("src.main._retry_connection", new=_passthrough):
+            result = await run_daily_session(
+                broker=broker,
+                overseas_broker=MagicMock(),
+                scenario_engine=scenario_engine,
+                playbook_store=playbook_store,
+                pre_market_planner=MagicMock(),
+                risk=risk,
+                db_conn=init_db(":memory:"),
+                decision_logger=decision_logger,
+                context_store=MagicMock(),
+                criticality_assessor=MagicMock(),
+                telegram=telegram,
+                settings=settings,
+                smart_scanner=smart_scanner,
+                daily_start_eval=55000.0,  # existing baseline
+            )
+
+        # Must return the original baseline, NOT the new total_eval (58000)
+        assert result == 55000.0