fix: 홀딩 종목 volume_ratio를 price API high/low 실데이터로 계산 (#267)

candidate 없는 해외 홀딩 종목(NVDA 등)에 대해 이미 호출된
get_overseas_price 응답의 high/low를 활용하여 scanner와 동일한 방식으로
volume_ratio 계산:

  intraday_range_pct = (high - low) / price * 100
  volume_ratio = max(1.0, volatility_pct / 2.0)

high/low 미제공 시(국내 종목, API 미응답) 기존 기본값 1.0 유지.
implied_rsi는 이미 실API price_change_pct(rate 필드) 기반.

tests/test_main.py: 해외 홀딩 종목 volume_ratio 계산 검증 테스트 추가

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

src/main.py

@@ -477,6 +477,7 @@ async def trading_cycle(
     cycle_start_time = asyncio.get_event_loop().time()
 
     # 1. Fetch market data
+    price_output: dict[str, Any] = {}  # Populated for overseas markets; used for fallback metrics
     if market.is_domestic:
         current_price, price_change_pct, foreigner_net = await broker.get_current_price(
             stock_code
@@ -511,7 +512,8 @@ async def trading_cycle(
         purchase_total = safe_float(balance_info.get("frcr_buy_amt_smtl", "0") or "0")
 
         # Resolve current price first (needed for buying power API)
-        current_price = safe_float(price_data.get("output", {}).get("last", "0"))
+        price_output = price_data.get("output", {})
+        current_price = safe_float(price_output.get("last", "0"))
         if current_price <= 0:
             market_candidates_lookup = scan_candidates.get(market.code, {})
             cand_lookup = market_candidates_lookup.get(stock_code)
@@ -523,7 +525,7 @@ async def trading_cycle(
                 )
                 current_price = cand_lookup.price
         foreigner_net = 0.0  # Not available for overseas
-        price_change_pct = safe_float(price_data.get("output", {}).get("rate", "0"))
+        price_change_pct = safe_float(price_output.get("rate", "0"))
 
         # Fetch available foreign currency cash via inquire-psamount (TTTS3007R/VTTS3007R).
         # TTTS3012R output2 does not include a cash/deposit field — frcr_dncl_amt_2 does not exist.
@@ -582,10 +584,27 @@ async def trading_cycle(
         market_data["rsi"] = candidate.rsi
         market_data["volume_ratio"] = candidate.volume_ratio
     else:
-        # Holding stocks not in scanner: derive implied RSI from price change,
-        # volume_ratio defaults to 1.0 (no surge data available).
+        # Holding stocks not in scanner: derive metrics from price API data already fetched.
+        # For overseas stocks, price_output contains high/low/rate from get_overseas_price.
+        # For domestic stocks, only price_change_pct is available from get_current_price.
         market_data["rsi"] = max(0.0, min(100.0, 50.0 + price_change_pct * 2.0))
-        market_data["volume_ratio"] = 1.0
+        if price_output and current_price > 0:
+            pr_high = safe_float(
+                price_output.get("high") or price_output.get("ovrs_hgpr")
+                or price_output.get("stck_hgpr")
+            )
+            pr_low = safe_float(
+                price_output.get("low") or price_output.get("ovrs_lwpr")
+                or price_output.get("stck_lwpr")
+            )
+            if pr_high > 0 and pr_low > 0 and pr_high >= pr_low:
+                intraday_range_pct = (pr_high - pr_low) / current_price * 100.0
+                volatility_pct = max(abs(price_change_pct), intraday_range_pct)
+                market_data["volume_ratio"] = max(1.0, volatility_pct / 2.0)
+            else:
+                market_data["volume_ratio"] = 1.0
+        else:
+            market_data["volume_ratio"] = 1.0
 
     # Enrich market_data with holding info for SELL/HOLD scenario conditions
     open_pos = get_open_position(db_conn, stock_code, market.code)

tests/test_main.py

@@ -1711,6 +1711,61 @@ class TestScenarioEngineIntegration:
         assert market_data["volume_ratio"] == 1.0
         assert market_data["current_price"] == 50000.0
 
+    @pytest.mark.asyncio
+    async def test_holding_overseas_stock_derives_volume_ratio_from_price_api(
+        self, mock_broker: MagicMock, mock_telegram: MagicMock,
+    ) -> None:
+        """Test overseas holding stocks derive volume_ratio from get_overseas_price high/low."""
+        engine = MagicMock(spec=ScenarioEngine)
+        engine.evaluate = MagicMock(return_value=_make_hold_match())
+
+        os_market = MagicMock()
+        os_market.name = "NASDAQ"
+        os_market.code = "US_NASDAQ"
+        os_market.exchange_code = "NAS"
+        os_market.is_domestic = False
+        os_market.timezone = UTC
+
+        os_broker = MagicMock()
+        # price_change_pct=5.0, high=106, low=94 → intraday_range=12% → volume_ratio=max(1,6)=6
+        os_broker.get_overseas_price = AsyncMock(return_value={
+            "output": {"last": "100.0", "rate": "5.0", "high": "106.0", "low": "94.0"}
+        })
+        os_broker.get_overseas_balance = AsyncMock(return_value={
+            "output2": [{"frcr_evlu_tota": "10000", "frcr_buy_amt_smtl": "9000"}]
+        })
+        os_broker.get_overseas_buying_power = AsyncMock(return_value={
+            "output": {"ord_psbl_frcr_amt": "500"}
+        })
+
+        with patch("src.main.log_trade"):
+            await trading_cycle(
+                broker=mock_broker,
+                overseas_broker=os_broker,
+                scenario_engine=engine,
+                playbook=_make_playbook(),
+                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=mock_telegram,
+                market=os_market,
+                stock_code="NVDA",
+                scan_candidates={},  # Not in scanner — holding stock
+            )
+
+        market_data = engine.evaluate.call_args[0][2]
+        # rsi: 50.0 + 5.0 * 2.0 = 60.0
+        assert market_data["rsi"] == pytest.approx(60.0)
+        # intraday_range = (106-94)/100 * 100 = 12.0%
+        # volatility_pct = max(abs(5.0), 12.0) = 12.0
+        # volume_ratio = max(1.0, 12.0 / 2.0) = 6.0
+        assert market_data["volume_ratio"] == pytest.approx(6.0)
+
     @pytest.mark.asyncio
     async def test_scenario_matched_notification_sent(
         self, mock_broker: MagicMock, mock_market: MagicMock, mock_telegram: MagicMock,