feat: creative alpha models + portfolio layer targeting Sharpe > 1.5
New strategies: - Cross-Sectional Momentum: long top-N, short bottom-N across HL universe - Spot-Perp Basis Arbitrage: delta-neutral spot vs perp price gap trading - Regime-Switching Ensemble: dynamically allocates strategies by market regime - Portfolio Construction: risk parity, vol targeting, correlation penalty Infrastructure: - DuckDBDataProvider: real tick/candle data for backtests (replaces synthetic) - Walk-Forward Validation: systematic IS/OOS across all 12 strategies - 3 Jupyter research notebooks (EDA, strategy research, portfolio) Pipeline integration: - deploy.py registry, sweep_runner, vbt_runner all updated - fee_tiers support for new strategies - All modules syntax-validated and import-tested
This commit is contained in:
ramseshk
@@ -0,0 +1,246 @@
|
||||
"""
|
||||
Systematic walk-forward validation across all strategies.
|
||||
|
||||
Runs every strategy through walk-forward IS/OOS backtesting with
|
||||
statistical significance testing (DSR, PSR, Sharpe Haircut).
|
||||
|
||||
Produces:
|
||||
- Per-strategy walk-forward reports
|
||||
- Composite significance scores
|
||||
- Strategy ranking by robustness
|
||||
- Deploy/simulate/discard recommendations
|
||||
|
||||
Usage:
|
||||
python strategies/wf_validate_all.py # all strategies, 1h interval
|
||||
python strategies/wf_validate_all.py --strategy pairs # single strategy
|
||||
python strategies/wf_validate_all.py --interval 4h # different interval
|
||||
python strategies/wf_validate_all.py --n-windows 5 # more windows
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import logging
|
||||
import sys
|
||||
import time
|
||||
from datetime import datetime, timezone
|
||||
from pathlib import Path
|
||||
|
||||
import numpy as np
|
||||
|
||||
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
|
||||
|
||||
from quant.walkforward import WalkForwardRunner
|
||||
from quant.significance import QuantVerdict, validate_strategy
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
VALIDATION_STRATEGIES = [
|
||||
"pairs",
|
||||
"hurst_vpin",
|
||||
"as_mm",
|
||||
"obi",
|
||||
"grid_mm",
|
||||
"composite_mm",
|
||||
"iceberg",
|
||||
"momentum",
|
||||
"mean_rev",
|
||||
"cross_sectional",
|
||||
"spot_perp_basis",
|
||||
"regime_ensemble",
|
||||
]
|
||||
|
||||
INTERVALS = ["1h", "4h", "1d"]
|
||||
|
||||
|
||||
def run_full_validation(
|
||||
strategies: list[str] | None = None,
|
||||
intervals: list[str] | None = None,
|
||||
n_windows: int = 5,
|
||||
fee_tier: int = 0,
|
||||
staking_tier: str = "none",
|
||||
save_results: bool = True,
|
||||
) -> dict:
|
||||
"""Run walk-forward validation on all specified strategies and intervals.
|
||||
|
||||
Returns a dict with strategy → interval → report.
|
||||
"""
|
||||
strats = strategies or VALIDATION_STRATEGIES
|
||||
ints = intervals or INTERVALS
|
||||
|
||||
results: dict[str, dict] = {}
|
||||
total = len(strats) * len(ints)
|
||||
completed = 0
|
||||
|
||||
logger.info("=" * 60)
|
||||
logger.info("Walk-Forward Validation: %d strategies × %d intervals = %d runs",
|
||||
len(strats), len(ints), total)
|
||||
logger.info("Windows: %d | Fee tier: %d | Staking: %s", n_windows, fee_tier, staking_tier)
|
||||
logger.info("=" * 60)
|
||||
|
||||
for strategy in strats:
|
||||
results[strategy] = {}
|
||||
for interval in ints:
|
||||
completed += 1
|
||||
t_start = time.time()
|
||||
|
||||
logger.info("[%d/%d] %s @ %s...", completed, total, strategy, interval)
|
||||
|
||||
try:
|
||||
wfr = WalkForwardRunner(
|
||||
n_windows=n_windows,
|
||||
fee_tier=fee_tier,
|
||||
staking_tier=staking_tier,
|
||||
)
|
||||
report = wfr.run(strategy=strategy, interval=interval)
|
||||
elapsed = time.time() - t_start
|
||||
|
||||
if report.windows:
|
||||
sig = report.significance_report(n_trials=len(strats) * len(ints))
|
||||
ver = validate_strategy(
|
||||
sharpe=report.avg_oos_sharpe,
|
||||
n_trades=max(report.total_oos_trades, 1),
|
||||
n_trials=len(strats) * len(ints),
|
||||
wf_consistency=report.consistency,
|
||||
)
|
||||
results[strategy][interval] = {
|
||||
"strategy": strategy,
|
||||
"interval": interval,
|
||||
"n_windows": report.n_windows,
|
||||
"consistency": round(report.consistency, 3),
|
||||
"avg_oos_sharpe": round(report.avg_oos_sharpe, 3),
|
||||
"oos_sharpe": round(report.oos_sharpe, 3),
|
||||
"performance_decay": round(report.performance_decay, 3),
|
||||
"total_trades": report.total_oos_trades,
|
||||
"deflated_sharpe": sig["deflated_sharpe"],
|
||||
"psr": sig["psr"],
|
||||
"haircut_sharpe": sig["haircut_sharpe"],
|
||||
"verdict": sig["verdict"],
|
||||
"score": sig["score"],
|
||||
"recommendation": sig["recommendation"],
|
||||
"elapsed_s": round(elapsed, 1),
|
||||
}
|
||||
logger.info(" → W%d WF=%.2f S=%.2f DSR=%.3f %s @ %.1fs",
|
||||
len(report.windows), report.consistency,
|
||||
report.avg_oos_sharpe, sig["deflated_sharpe"],
|
||||
sig["verdict"], elapsed)
|
||||
else:
|
||||
results[strategy][interval] = {
|
||||
"strategy": strategy,
|
||||
"interval": interval,
|
||||
"error": "no_windows",
|
||||
"elapsed_s": round(elapsed, 1),
|
||||
}
|
||||
logger.info(" → No windows (insufficient data)")
|
||||
|
||||
except Exception as e:
|
||||
elapsed = time.time() - t_start
|
||||
results[strategy][interval] = {
|
||||
"strategy": strategy,
|
||||
"interval": interval,
|
||||
"error": str(e)[:100],
|
||||
"elapsed_s": round(elapsed, 1),
|
||||
}
|
||||
logger.warning(" → Error: %s", e)
|
||||
|
||||
# Print unified summary
|
||||
_print_summary(results)
|
||||
|
||||
if save_results:
|
||||
_save_results(results)
|
||||
|
||||
return results
|
||||
|
||||
|
||||
def _print_summary(results: dict):
|
||||
print(f"\n{'=' * 80}")
|
||||
print(f" Walk-Forward Validation Summary")
|
||||
print(f"{'=' * 80}")
|
||||
print(f"{'Strategy':<20} {'Int':>4} {'W':>3} {'Consist':>8} {'OOS Sh':>7} {'Decay':>7} {'DSR':>6} {'Verdict':>10}")
|
||||
print("-" * 80)
|
||||
|
||||
rankings = []
|
||||
for strategy in sorted(results):
|
||||
for interval in sorted(results.get(strategy, {})):
|
||||
r = results[strategy][interval]
|
||||
if r.get("error"):
|
||||
continue
|
||||
rankings.append(r)
|
||||
print(f"{r['strategy']:<20} {r['interval']:>4} {r['n_windows']:>3} "
|
||||
f"{r['consistency']:>7.0%} {r['avg_oos_sharpe']:>7.2f} "
|
||||
f"{r['performance_decay']:>7.2f} {r['deflated_sharpe']:>6.3f} "
|
||||
f"{r['verdict']:>10}")
|
||||
|
||||
rankings.sort(key=lambda x: x.get("deflated_sharpe", 0), reverse=True)
|
||||
|
||||
print(f"\n--- Top 10 by Deflated Sharpe Ratio ---")
|
||||
for i, r in enumerate(rankings[:10]):
|
||||
deploy_mark = " ✅" if r["verdict"] == "DEPLOY" else (" ⚠️" if r["verdict"] == "SIMULATE" else " ❌")
|
||||
print(f" {i+1:2d}. {r['strategy']:<20s} {r['interval']:>4s} "
|
||||
f"DSR={r['deflated_sharpe']:>6.3f} {r['verdict']}{deploy_mark}")
|
||||
|
||||
deployable = [r for r in rankings if r["verdict"] == "DEPLOY"]
|
||||
simulate = [r for r in rankings if r["verdict"] == "SIMULATE"]
|
||||
discarded = [r for r in rankings if r["verdict"] == "DISCARD"]
|
||||
|
||||
print(f"\nVerdict breakdown:")
|
||||
print(f" DEPLOY: {len(deployable)}")
|
||||
print(f" SIMULATE: {len(simulate)}")
|
||||
print(f" DISCARD: {len(discarded)}")
|
||||
|
||||
if deployable:
|
||||
print(f"\nDeployable strategies (sorted by DSR):")
|
||||
for r in sorted(deployable, key=lambda x: x["deflated_sharpe"], reverse=True):
|
||||
print(f" ✅ {r['strategy']}/{r['interval']}: "
|
||||
f"OOS Sharpe={r['avg_oos_sharpe']:.2f}, DSR={r['deflated_sharpe']:.3f}")
|
||||
|
||||
|
||||
def _save_results(results: dict):
|
||||
timestamp = datetime.now(timezone.utc).strftime("%Y%m%d-%H%M%S")
|
||||
out_path = Path(__file__).resolve().parent.parent / "backtests" / "results" / f"wf_validation_{timestamp}.json"
|
||||
|
||||
flat = {}
|
||||
for strategy, intervals in results.items():
|
||||
for interval, report in intervals.items():
|
||||
flat[f"{strategy}/{interval}"] = report
|
||||
|
||||
out_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
with open(out_path, "w") as f:
|
||||
json.dump(flat, f, indent=2, default=str)
|
||||
logger.info("Results saved to %s", out_path)
|
||||
|
||||
|
||||
def main():
|
||||
p = argparse.ArgumentParser(description="Walk-Forward Validation — All Strategies")
|
||||
p.add_argument("--strategy", "-s", nargs="+",
|
||||
help="Strategies to validate (default: all)")
|
||||
p.add_argument("--interval", "-i", nargs="+",
|
||||
help="Intervals to test (default: 1h,4h,1d)")
|
||||
p.add_argument("--n-windows", type=int, default=5,
|
||||
help="Number of walk-forward windows (default: 5)")
|
||||
p.add_argument("--fee-tier", type=int, default=0,
|
||||
help="VIP fee tier 0-6 (default: 0)")
|
||||
p.add_argument("--staking-tier", default="none",
|
||||
help="Staking tier (default: none)")
|
||||
p.add_argument("--no-save", action="store_true",
|
||||
help="Don't save results to disk")
|
||||
args = p.parse_args()
|
||||
|
||||
logging.basicConfig(
|
||||
level=logging.INFO,
|
||||
format="%(asctime)s %(message)s",
|
||||
datefmt="%H:%M:%S",
|
||||
)
|
||||
|
||||
run_full_validation(
|
||||
strategies=args.strategy,
|
||||
intervals=args.interval,
|
||||
n_windows=args.n_windows,
|
||||
fee_tier=args.fee_tier,
|
||||
staking_tier=args.staking_tier,
|
||||
save_results=not args.no_save,
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user