research: add strategy evaluation and exploration scripts

Add 28 research scripts covering DCA simulation, momentum evaluation,
Sharpe optimization, trend rider analysis, and US fundamentals exploration.

research/v5_drawdown_trace.py

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+"""Trace where V3/V5 maximum drawdowns occur and what holdings they had."""
+from __future__ import annotations
+
+import os
+import sys
+from itertools import product
+
+import numpy as np
+import pandas as pd
+
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from research.trend_rider_robustness import (
+    load_price_panel,
+    portfolio_returns,
+)
+from strategies.permanent import TrendRiderV3
+from strategies.trend_rider_v5 import TrendRiderV5
+
+
+def trace(name: str, weights: pd.DataFrame, prices: pd.DataFrame,
+          start: str = "2015-01-02") -> None:
+    rets = portfolio_returns(weights, prices[weights.columns], 0.001)
+    rets = rets[rets.index >= start]
+    eq = (1 + rets).cumprod()
+    dd = eq / eq.cummax() - 1
+    trough = dd.idxmin()
+    peak = eq.loc[:trough].idxmax()
+    recover = eq.loc[trough:][eq.loc[trough:] >= eq.loc[peak]]
+    rec_dt = recover.index[0] if len(recover) else None
+
+    print(f"\n=== {name} ===")
+    print(f"  MDD = {dd.min()*100:.2f}%")
+    print(f"  Peak  : {peak.date()}  equity={eq.loc[peak]:.3f}")
+    print(f"  Trough: {trough.date()}  equity={eq.loc[trough]:.3f}")
+    print(f"  Recovered: {rec_dt.date() if rec_dt is not None else 'NOT YET'}")
+    print(f"  Days to trough: {(trough - peak).days}")
+
+    # Show holdings around the drawdown
+    print(f"\n  Holdings 5 days before peak through 5 days after trough:")
+    sl = weights.loc[peak - pd.Timedelta(days=10): trough + pd.Timedelta(days=10)]
+    nonzero = (sl != 0).any(axis=0)
+    sl = sl.loc[:, nonzero]
+    sl_disp = sl.copy()
+    # Show only days when holdings change
+    changes = (sl_disp != sl_disp.shift(1)).any(axis=1)
+    sl_disp = sl_disp.loc[changes]
+    print(sl_disp.round(3).head(40).to_string())
+
+
+def main() -> None:
+    prices = load_price_panel()
+    print(f"Panel: {prices.index.min().date()} to {prices.index.max().date()}")
+
+    candidates = {
+        "V3 default": TrendRiderV3(),
+        "V5 default (panic 1.6/4%)": TrendRiderV5(),
+        "V5 panic 1.8/5%": TrendRiderV5(panic_vol_ratio=1.8, panic_peak_drop_pct=0.05),
+    }
+    for name, strat in candidates.items():
+        w = strat.generate_signals(prices)
+        trace(name, w, prices)
+
+
+if __name__ == "__main__":
+    main()