fithia2/_tune_v7356_sweep.py

"""Sweep v7.356 parameters to reduce MDD and improve SQS.

Base: v7.356_composed_gld_compound. SQS risk component=50, MDD=14.5% — bottleneck.

Sweep strategy:
- Phase 1: single-param sweeps (max_pos_value, risk_off_scaler, stop_atr)
- Phase 2: top-2 from phase 1 combined
"""
import json
import subprocess
import shutil
from pathlib import Path

BASE = "configs/experiments/return_max_long_v7.356_composed_gld_compound.json"
SWEEP_DIR = Path("configs/experiments/_tune_v7356_sweep")
SWEEP_DIR.mkdir(exist_ok=True)
SNAPSHOT = "midlarge-liquid-long-v1_bucketfix_full_audit_canonical_ftb_fix_v2"


def make_config(name: str, risk_overrides: dict, exec_overrides: dict = None) -> str:
    with open(BASE) as f:
        cfg = json.load(f)
    cfg["experiment_name"] = name
    cfg["overrides"]["risk"].update(risk_overrides)
    if exec_overrides:
        cfg["overrides"]["execution"].update(exec_overrides)
    path = SWEEP_DIR / f"{name}.json"
    path.write_text(json.dumps(cfg, indent=2))
    return str(path)


def run_backtest(config_path: str) -> dict:
    cmd = [
        "python3", "-m", "apps.backtester.run",
        "--manifest", config_path,
        "--start", "2022-01-01",
        "--split", "all",
        "--initial-equity", "10000",
        "--snapshot-id", SNAPSHOT,
    ]
    # Clean runtime cache to ensure fresh load
    cache = Path(f"data/parquet/{SNAPSHOT}/.runtime_cache")
    if cache.exists():
        shutil.rmtree(cache)
    proc = subprocess.run(cmd, capture_output=True, text=True, timeout=300)
    tail = proc.stdout.split("\n")[-10:]
    run_id = None
    return_pct = None
    sqs_total = None
    sqs_parts = None
    trades = None
    for line in tail:
        if "Run complete:" in line:
            run_id = line.split("Run complete:")[1].strip()
        elif "Total return:" in line:
            return_pct = float(line.split(":")[1].strip().rstrip("%"))
        elif "SQS:" in line:
            parts = line.split("SQS:")[1].strip()
            sqs_total = float(parts.split(" ")[0])
            sqs_parts = parts
        elif "Trades:" in line:
            trades = int(line.split(":")[1].strip())

    # Get MDD from metrics
    mdd = sharpe = pf = None
    if run_id:
        m_path = Path(f"runs/{run_id}/metrics/metrics_summary.json")
        if m_path.exists():
            m = json.loads(m_path.read_text())
            mdd = m["max_drawdown_pct"]
            sharpe = m["sharpe_ratio"]
            pf = m["profit_factor"]
    return {
        "return": return_pct,
        "trades": trades,
        "mdd": mdd,
        "sharpe": sharpe,
        "pf": pf,
        "sqs": sqs_total,
        "sqs_parts": sqs_parts,
        "run_id": run_id,
    }


SWEEPS = [
    # (name, risk overrides, execution overrides)
    ("v7.356_T01_pos20", {"max_position_value_pct": 20}, None),
    ("v7.356_T02_pos15", {"max_position_value_pct": 15}, None),
    ("v7.356_T03_ro_07", {"macro_regime_risk_off_size_scaler": 0.7}, None),
    ("v7.356_T04_ro_05", {"macro_regime_risk_off_size_scaler": 0.5}, None),
    ("v7.356_T05_stop_25", {"stop_atr_multiplier": 2.5}, None),
    ("v7.356_T06_stop_35", {"stop_atr_multiplier": 3.5}, None),
    ("v7.356_T07_sec3", {"max_positions_per_sector": 3}, None),
    ("v7.356_T08_sec4", {"max_positions_per_sector": 4}, None),
]


def main():
    baseline = {"return": 2236.1, "mdd": 14.50, "sharpe": 2.72, "pf": 4.38, "sqs": 87.1, "trades": 293}
    print(f"BASELINE: ret={baseline['return']}% MDD={baseline['mdd']}% Sharpe={baseline['sharpe']} SQS={baseline['sqs']} trades={baseline['trades']}")
    print("=" * 100)
    results = []
    for name, risk_ov, exec_ov in SWEEPS:
        path = make_config(name, risk_ov, exec_ov)
        print(f"\n>>> {name}: risk={risk_ov} exec={exec_ov}")
        try:
            r = run_backtest(path)
            r["name"] = name
            d_ret = r["return"] - baseline["return"] if r["return"] else None
            d_mdd = r["mdd"] - baseline["mdd"] if r["mdd"] else None
            d_sqs = r["sqs"] - baseline["sqs"] if r["sqs"] else None
            print(f"    ret={r['return']:.0f}% (Δ{d_ret:+.0f}) MDD={r['mdd']:.2f}% (Δ{d_mdd:+.2f}) Sharpe={r['sharpe']:.2f} PF={r['pf']:.2f} SQS={r['sqs']:.1f} (Δ{d_sqs:+.1f}) trades={r['trades']}")
            results.append(r)
        except Exception as e:
            print(f"    FAILED: {e}")

    # Print summary table
    print("\n" + "=" * 100)
    print("SUMMARY (sorted by SQS):")
    results.sort(key=lambda x: x.get("sqs") or 0, reverse=True)
    print(f"{'name':30s} {'return':>10s} {'MDD':>8s} {'Sharpe':>8s} {'PF':>6s} {'SQS':>6s} {'trades':>7s}")
    print(f"{'BASELINE':30s} {baseline['return']:>9.0f}% {baseline['mdd']:>7.2f}% {baseline['sharpe']:>8.2f} {baseline['pf']:>6.2f} {baseline['sqs']:>6.1f} {baseline['trades']:>7d}")
    for r in results:
        print(f"{r['name']:30s} {r['return']:>9.0f}% {r['mdd']:>7.2f}% {r['sharpe']:>8.2f} {r['pf']:>6.2f} {r['sqs']:>6.1f} {r['trades']:>7d}")


if __name__ == "__main__":
    main()