Lumiwealth · someposer · May 8, 2026 · May 8, 2026
@@ -1742,15 +1742,17 @@ def _write_tearsheet_metrics_json(reason: str, scalar_metrics: dict | None = Non
         logger.error("Not enough data to create a tearsheet, at least 2 days of data are required. Skipping")
         return
     '''
-    # Set the name of the benchmark column so that quantstats can use it in the report
-    df_final["benchmark"].name = str(benchmark_asset)
+    # Set the name of the benchmark column so that quantstats can use it in the report.
+    # df_final["benchmark"] returns a new Series each time, so we must capture it;
+    # assigning to .name on a throwaway accessor is a no-op.
+    _benchmark_series = df_final["benchmark"].rename(str(benchmark_asset))
 
     # Run quantstats reports surpressing any logs because it can be noisy for no reason
     try:
         with open(os.devnull, "w") as f, contextlib.redirect_stdout(f), contextlib.redirect_stderr(f):
             result = qs.reports.html(
                 df_final["strategy"],
-                df_final["benchmark"],
+                _benchmark_series,
                 title=title,
                 output=tearsheet_file,
                 download_filename=tearsheet_file,  # Consider if you need a different name for clarity
@@ -1836,7 +1838,7 @@ def _histogram_no_kde(
                 with open(os.devnull, "w") as f, contextlib.redirect_stdout(f), contextlib.redirect_stderr(f):
                     result = qs.reports.html(
                         df_final["strategy"],
-                        df_final["benchmark"],
+                        _benchmark_series,
                         title=title,
                         output=tearsheet_file,
                         download_filename=tearsheet_file,
@@ -1941,7 +1943,7 @@ def _write_tearsheet_metrics_json_fallback() -> None:
         with open(os.devnull, "w") as f, contextlib.redirect_stdout(f), contextlib.redirect_stderr(f):
             metrics_df = qs.reports.metrics(
                 df_final["strategy"],
-                df_final["benchmark"],
+                _benchmark_series,
                 rf=risk_free_rate,
                 display=False,
                 custom_metrics=custom_metrics,
@@ -1992,7 +1994,7 @@ def _write_tearsheet_metrics_json_fallback() -> None:
                 with open(os.devnull, "w") as f, contextlib.redirect_stdout(f), contextlib.redirect_stderr(f):
                     metrics_json_fn(
                         df_final["strategy"],
-                        df_final["benchmark"],
+                        _benchmark_series,
                         rf=risk_free_rate,
                         output=tearsheet_metrics_file,
                         summary_only=True,

@@ -0,0 +1,93 @@
+from __future__ import annotations
+
+from datetime import datetime
+
+import pandas as pd
+
+from lumibot.tools.indicators import create_tearsheet
+
+
+def _make_inputs(tmp_path):
+    idx = pd.date_range(datetime(2025, 12, 8), periods=5, freq="1D")
+    strategy_df = pd.DataFrame({"portfolio_value": [100, 101, 99, 102, 103]}, index=idx)
+    benchmark_df = pd.DataFrame({"symbol_cumprod": [1.0, 1.005, 1.002, 1.01, 1.011]}, index=idx)
+    return strategy_df, benchmark_df, tmp_path / "tearsheet.html"
+
+
+def _base_kwargs(tearsheet_file, benchmark_asset):
+    return dict(
+        strat_name="TestStrategy",
+        tearsheet_file=str(tearsheet_file),
+        benchmark_asset=benchmark_asset,
+        show_tearsheet=False,
+        save_tearsheet=True,
+        risk_free_rate=0.0,
+        strategy_parameters={},
+        lumibot_version="dev",
+        backtesting_data_source="yahoo",
+        backtesting_data_sources="yahoo",
+        backtest_time_seconds=1.0,
+    )
+
+
+def _fake_html_writer(output):
+    with open(output, "w", encoding="utf-8") as f:
+        f.write("<html><body>ok</body></html>")
+    return pd.DataFrame({"Metric": ["Total Return"], "Strategy": ["1.00%"]})
+
+
+def test_benchmark_series_name_passed_to_quantstats(monkeypatch, tmp_path):
+    """Regression: benchmark label must be the asset symbol, not 'benchmark' / 'BENCHMARK'.
+
+    df_final["benchmark"] returns a new Series on each access, so assigning to .name on
+    that throwaway object is a no-op. The fix captures the series with .rename() before
+    passing to qs.reports.html. Without the fix, QuantStats uppercases the column name
+    and shows 'BENCHMARK' in the tearsheet instead of the actual symbol (e.g. 'SPY').
+    """
+    import quantstats_lumi as qs
+
+    captured = {}
+
+    def fake_html(returns, benchmark=None, **kwargs):
+        captured["benchmark_name"] = getattr(benchmark, "name", None)
+        return _fake_html_writer(kwargs.get("output"))
+
+    monkeypatch.setattr(qs.reports, "html", fake_html)
+
+    strategy_df, benchmark_df, out = _make_inputs(tmp_path)
+    create_tearsheet(strategy_df=strategy_df, benchmark_df=benchmark_df, **_base_kwargs(out, "SPY"))
+
+    assert captured.get("benchmark_name") == "SPY", (
+        f"Expected benchmark Series name 'SPY' but got {captured.get('benchmark_name')!r}. "
+        "The no-op .name assignment bug causes QuantStats to see name='benchmark' and "
+        "uppercase it to 'BENCHMARK' in the tearsheet header."
+    )
+
+
+def test_benchmark_series_name_preserved_on_kde_retry(monkeypatch, tmp_path):
+    """Regression: benchmark label must also be correct on the KDE-failure retry path.
+
+    The fix assigns _benchmark_series once before both qs.reports.html call sites.
+    This test verifies the retry path receives the same named Series as the primary path.
+    """
+    import quantstats_lumi as qs
+
+    benchmark_names = []
+
+    def fake_html(returns, benchmark=None, **kwargs):
+        benchmark_names.append(getattr(benchmark, "name", None))
+        if len(benchmark_names) == 1:
+            raise RuntimeError("singular data covariance matrix ... gaussian_kde")
+        return _fake_html_writer(kwargs.get("output"))
+
+    monkeypatch.setattr(qs.reports, "html", fake_html)
+
+    strategy_df, benchmark_df, out = _make_inputs(tmp_path)
+    create_tearsheet(strategy_df=strategy_df, benchmark_df=benchmark_df, **_base_kwargs(out, "QQQ"))
+
+    assert len(benchmark_names) == 2, f"Expected 2 qs.reports.html calls (primary + retry), got {len(benchmark_names)}"
+    for i, name in enumerate(benchmark_names):
+        assert name == "QQQ", (
+            f"Call {i + 1}: expected benchmark Series name 'QQQ' but got {name!r}. "
+            "The retry path must use _benchmark_series, not df_final['benchmark']."
+        )