fix(data): reject stale yfinance OHLCV instead of reporting wrong prices

yfinance intermittently returns a year-old partial frame (e.g. June 2025 rows
for a June 2026 request) that still has rows and a Close, so it passed the
empty-check and silently fed a wrong close price and indicators into the report
(#1021). Add a freshness guard that rejects a frame whose latest row is far
older than the requested date, on both the raw OHLCV path and the indicator
path. It raises the existing NoMarketDataError with a stale-specific detail, so
the vendor router's try-next-vendor and single unavailable-signal handling apply
unchanged; the sentinel now surfaces that detail so the agent reports the
specific reason rather than fabricating a value.

tests/test_yfinance_stale_ohlcv_guard.py

@@ -0,0 +1,113 @@
+"""Stale OHLCV guard (#1021): a vendor returning a year-old partial frame must
+be rejected, not fed into the report as if it were current.
+
+The guard raises NoMarketDataError with a stale-specific detail, so the router's
+existing try-next-vendor + single-sentinel handling applies and the sentinel
+surfaces the reason.
+"""
+import copy
+import unittest
+from unittest import mock
+
+import pandas as pd
+import pytest
+
+import tradingagents.dataflows.config as config_module
+import tradingagents.dataflows.y_finance as y_finance
+import tradingagents.default_config as default_config
+from tradingagents.dataflows import interface
+from tradingagents.dataflows.config import set_config
+from tradingagents.dataflows.stockstats_utils import _assert_ohlcv_not_stale
+from tradingagents.dataflows.symbol_utils import NoMarketDataError
+
+
+def _frame(date):
+    return pd.DataFrame(
+        {
+            "Date": [pd.Timestamp(date)],
+            "Open": [330.0],
+            "High": [332.0],
+            "Low": [328.0],
+            "Close": [330.58],
+            "Volume": [1_000_000],
+        }
+    )
+
+
+@pytest.mark.unit
+class StaleGuardUnitTests(unittest.TestCase):
+    def test_recent_prior_trading_day_is_accepted(self):
+        # 1 day before curr_date — well within the freshness window.
+        _assert_ohlcv_not_stale(_frame("2026-06-10"), "2026-06-11", "CB")
+
+    def test_year_old_row_is_rejected_with_detail(self):
+        with self.assertRaises(NoMarketDataError) as ctx:
+            _assert_ohlcv_not_stale(_frame("2025-06-11"), "2026-06-11", "CB", "CB")
+        msg = str(ctx.exception)
+        self.assertIn("2025-06-11", msg)
+        self.assertIn("2026-06-11", msg)
+        self.assertIn("stale", msg)
+
+    def test_empty_frame_is_left_to_caller(self):
+        # Empty is a no-data condition handled elsewhere, not a staleness one.
+        _assert_ohlcv_not_stale(
+            pd.DataFrame(columns=["Date", "Close"]), "2026-06-11", "X"
+        )
+
+    def test_long_holiday_gap_within_threshold_is_accepted(self):
+        _assert_ohlcv_not_stale(_frame("2026-06-02"), "2026-06-11", "X")  # 9 days
+
+
+@pytest.mark.unit
+class StaleGuardPropagationTests(unittest.TestCase):
+    def test_get_yfin_data_online_raises_on_stale_frame(self):
+        stale = pd.DataFrame(
+            {
+                "Open": [280.0], "High": [286.0], "Low": [278.0],
+                "Close": [284.45], "Volume": [1_000_000],
+            },
+            index=pd.DatetimeIndex([pd.Timestamp("2025-06-11")], name="Date"),
+        )
+
+        class DummyTicker:
+            def __init__(self, symbol):
+                pass
+
+            def history(self, start, end):
+                return stale
+
+        with mock.patch.object(y_finance.yf, "Ticker", DummyTicker), \
+                self.assertRaises(NoMarketDataError):
+            y_finance.get_YFin_data_online("CB", "2026-06-01", "2026-06-11")
+
+
+@pytest.mark.unit
+class StaleGuardRoutingTests(unittest.TestCase):
+    def setUp(self):
+        config_module._config = copy.deepcopy(default_config.DEFAULT_CONFIG)
+
+    def tearDown(self):
+        config_module._config = copy.deepcopy(default_config.DEFAULT_CONFIG)
+
+    def test_router_sentinel_surfaces_stale_reason(self):
+        set_config({"data_vendors": {"core_stock_apis": "yfinance"}})
+
+        def _stale(symbol, *a, **k):
+            raise NoMarketDataError(
+                symbol, symbol, "latest row is 2025-06-11, 365 days before ... (stale)"
+            )
+
+        with mock.patch.dict(
+            interface.VENDOR_METHODS,
+            {"get_stock_data": {"yfinance": _stale}},
+            clear=False,
+        ):
+            out = interface.route_to_vendor(
+                "get_stock_data", "CB", "2026-06-01", "2026-06-11"
+            )
+        self.assertIn("NO_DATA_AVAILABLE", out)
+        self.assertIn("stale", out)  # the typed detail is surfaced to the agent
+
+
+if __name__ == "__main__":
+    unittest.main()

tradingagents/dataflows/stockstats_utils.py

@@ -1,18 +1,24 @@
-import time
 import logging
+import os
+import time
+from typing import Annotated
 
 import pandas as pd
 import yfinance as yf
-from yfinance.exceptions import YFRateLimitError
 from stockstats import wrap
-from typing import Annotated
-import os
+from yfinance.exceptions import YFRateLimitError
+
 from .config import get_config
+from .symbol_utils import NoMarketDataError, normalize_symbol
 from .utils import safe_ticker_component
-from .symbol_utils import normalize_symbol, NoMarketDataError
 
 logger = logging.getLogger(__name__)
 
+# A vendor's latest OHLCV row this many calendar days before the requested date
+# is treated as stale. Generous enough to span long holiday weekends, tight
+# enough to catch the year-old frames yfinance occasionally returns (#1021).
+MAX_OHLCV_STALE_DAYS = 10
+
 
 def yf_retry(func, max_retries=3, base_delay=2.0):
     """Execute a yfinance call with exponential backoff on rate limits.
@@ -62,6 +68,60 @@ def _clean_dataframe(data: pd.DataFrame) -> pd.DataFrame:
     return data
 
 
+def _coerce_ohlcv_dates(data: pd.DataFrame) -> pd.Series:
+    """Return parsed dates from an OHLCV frame, whether Date is a column or the index."""
+    if "Date" in data.columns:
+        return pd.to_datetime(data["Date"], errors="coerce").dropna()
+    # yfinance keeps the dates in the index (a DatetimeIndex, sometimes unnamed).
+    if isinstance(data.index, pd.DatetimeIndex):
+        return pd.Series(pd.to_datetime(data.index, errors="coerce")).dropna()
+    # Fallback: expose the index and look for any date-like column.
+    df = data.reset_index()
+    for col in ("Date", "Datetime", "date", "index"):
+        if col in df.columns:
+            parsed = pd.to_datetime(df[col], errors="coerce").dropna()
+            if not parsed.empty:
+                return parsed
+    return pd.Series(dtype="datetime64[ns]")
+
+
+def _assert_ohlcv_not_stale(
+    data: pd.DataFrame,
+    curr_date: str,
+    symbol: str,
+    canonical: str | None = None,
+    *,
+    max_stale_days: int = MAX_OHLCV_STALE_DAYS,
+) -> None:
+    """Reject OHLCV whose latest row is far older than curr_date.
+
+    Raises NoMarketDataError (with a stale-specific detail) so the router treats
+    it like any other "no usable data from this vendor" — try the next vendor,
+    then emit one clear unavailable signal. Empty frames are left to the
+    caller's existing no-data handling; this guards only the dangerous case of
+    present-but-stale rows (a vendor returning a year-old frame that would
+    otherwise feed wrong prices to the agent, #1021).
+    """
+    if data is None or data.empty:
+        return
+    requested = pd.to_datetime(curr_date, errors="coerce")
+    if pd.isna(requested):
+        return
+    requested = requested.normalize()
+    dates = _coerce_ohlcv_dates(data)
+    if dates.empty:
+        return
+    latest = dates.max().normalize()
+    stale_days = (requested - latest).days
+    if stale_days > max_stale_days:
+        raise NoMarketDataError(
+            symbol,
+            canonical,
+            f"latest row is {latest.date()}, {stale_days} days before the "
+            f"requested {requested.date()} (stale) — refusing to use it",
+        )
+
+
 def load_ohlcv(symbol: str, curr_date: str) -> pd.DataFrame:
     """Fetch OHLCV data with caching, filtered to prevent look-ahead bias.
 
@@ -125,6 +185,10 @@ def load_ohlcv(symbol: str, curr_date: str) -> pd.DataFrame:
     # Filter to curr_date to prevent look-ahead bias in backtesting
     data = data[data["Date"] <= curr_date_dt]
 
+    # Reject a stale frame (latest row far older than curr_date) rather than
+    # feeding year-old prices into indicators (#1021).
+    _assert_ohlcv_not_stale(data, curr_date, symbol, canonical)
+
     return data
 
 

tradingagents/dataflows/y_finance.py

@@ -1,11 +1,19 @@
-from typing import Annotated
 from datetime import datetime
-from dateutil.relativedelta import relativedelta
+from typing import Annotated
+
 import pandas as pd
 import yfinance as yf
-import os
-from .stockstats_utils import StockstatsUtils, _clean_dataframe, yf_retry, load_ohlcv, filter_financials_by_date
-from .symbol_utils import normalize_symbol, NoMarketDataError
+from dateutil.relativedelta import relativedelta
+
+from .stockstats_utils import (
+    StockstatsUtils,
+    _assert_ohlcv_not_stale,
+    filter_financials_by_date,
+    load_ohlcv,
+    yf_retry,
+)
+from .symbol_utils import NoMarketDataError, normalize_symbol
+
 
 def get_YFin_data_online(
     symbol: Annotated[str, "ticker symbol of the company"],
@@ -38,6 +46,11 @@ def get_YFin_data_online(
     if data.index.tz is not None:
         data.index = data.index.tz_localize(None)
 
+    # Reject a stale frame (e.g. a year-old partial response) before it is
+    # formatted into the report. Raises NoMarketDataError, which the router
+    # turns into one clear unavailable signal (#1021).
+    _assert_ohlcv_not_stale(data, end_date, symbol, canonical)
+
     # Round numerical values to 2 decimal places for cleaner display
     numeric_columns = ["Open", "High", "Low", "Close", "Adj Close"]
     for col in numeric_columns:
@@ -150,23 +163,23 @@ def get_stock_stats_indicators_window(
     # Optimized: Get stock data once and calculate indicators for all dates
     try:
         indicator_data = _get_stock_stats_bulk(symbol, indicator, curr_date)
-        
+
         # Generate the date range we need
         current_dt = curr_date_dt
         date_values = []
-        
+
         while current_dt >= before:
             date_str = current_dt.strftime('%Y-%m-%d')
-            
+
             # Look up the indicator value for this date
             if date_str in indicator_data:
                 indicator_value = indicator_data[date_str]
             else:
                 indicator_value = "N/A: Not a trading day (weekend or holiday)"
-            
+
             date_values.append((date_str, indicator_value))
             current_dt = current_dt - relativedelta(days=1)
-        
+
         # Build the result string
         ind_string = ""
         for date_str, value in date_values:
@@ -211,22 +224,22 @@ def _get_stock_stats_bulk(
     data = load_ohlcv(symbol, curr_date)
     df = wrap(data)
     df["Date"] = df["Date"].dt.strftime("%Y-%m-%d")
-    
+
     # Calculate the indicator for all rows at once
     df[indicator]  # This triggers stockstats to calculate the indicator
-    
+
     # Create a dictionary mapping date strings to indicator values
     result_dict = {}
     for _, row in df.iterrows():
         date_str = row["Date"]
         indicator_value = row[indicator]
-        
+
         # Handle NaN/None values
         if pd.isna(indicator_value):
             result_dict[date_str] = "N/A"
         else:
             result_dict[date_str] = str(indicator_value)
-    
+
     return result_dict
 
 
@@ -450,8 +463,8 @@ def get_insider_transactions(
         # Add header information
         header = f"# Insider Transactions data for {canonical}\n"
         header += f"# Data retrieved on: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n"
-        
+
         return header + csv_string
-        
+
     except Exception as e:
-        return f"Error retrieving insider transactions for {ticker}: {str(e)}"
+        return f"Error retrieving insider transactions for {ticker}: {str(e)}"