"""SKH_P_RR — fine-sweep reward:risk on the ptn_n=55 V1 base. V1 base: SkyhookParams(ptn_n=55, sl_atr=2.5, tp_atr=6.0, vola_lo=35, vola_hi=95, vol_lo=0.0) -> minFull +0.69, HOLD +0.64 (BTC 0.64 / ETH 0.64), DD ~40-49% (HIGH). Sweep: sl_atr in {2.0,2.25,2.5,2.75,3.0,3.5} x tp_atr in {5,6,7,8,9,10}. Objective: maximize min-asset HOLD-OUT subject to minFull>=0.5, cut DD. Report best + plateau. """ from __future__ import annotations import sys sys.path.insert(0, "/opt/docker/PythagorasGoal/scripts/research/skyhook") import skyhooklib as sk from src.strategies.skyhook import SkyhookParams BASE = dict(ptn_n=55, vola_lo=35.0, vola_hi=95.0, vol_lo=0.0) SL_GRID = [2.0, 2.25, 2.5, 2.75, 3.0, 3.5] TP_GRID = [5.0, 6.0, 7.0, 8.0, 9.0, 10.0] def cell(sl, tp): p = SkyhookParams(sl_atr=sl, tp_atr=tp, **BASE) out = {} for a in ("BTC", "ETH"): r = sk.run_asset(a, p, fee_rt=sk.FEE_RT) out[a] = r min_full = min(out[a]["full"]["sharpe"] for a in out) min_hold = min(out[a]["holdout"]["sharpe"] for a in out) min_tr = min(out[a]["full"]["n_trades"] for a in out) max_dd = max(out[a]["full"]["maxdd"] for a in out) return dict(sl=sl, tp=tp, min_full=min_full, min_hold=min_hold, min_tr=min_tr, max_dd=max_dd, btc_full=out["BTC"]["full"]["sharpe"], eth_full=out["ETH"]["full"]["sharpe"], btc_hold=out["BTC"]["holdout"]["sharpe"], eth_hold=out["ETH"]["holdout"]["sharpe"], btc_dd=out["BTC"]["full"]["maxdd"], eth_dd=out["ETH"]["full"]["maxdd"]) print("=== SKH_P_RR sweep (ptn_n=55 base) — fee=0.10%RT ===") print(f"{'sl':>5} {'tp':>5} | {'minFull':>7} {'minHold':>7} {'minTr':>5} {'maxDD':>6} | " f"{'btcF':>5} {'ethF':>5} {'btcH':>5} {'ethH':>5} {'btcDD':>5} {'ethDD':>5}") results = [] for sl in SL_GRID: for tp in TP_GRID: if tp <= sl: # tp must exceed sl for a sensible R:R; skip degenerate continue c = cell(sl, tp) results.append(c) flag = "" if c["min_full"] >= 0.5 and c["min_tr"] >= 20: flag = " *" # eligible print(f"{sl:>5} {tp:>5} | {c['min_full']:>+7.2f} {c['min_hold']:>+7.2f} " f"{c['min_tr']:>5} {c['max_dd']*100:>5.0f}% | " f"{c['btc_full']:>+5.2f} {c['eth_full']:>+5.2f} " f"{c['btc_hold']:>+5.2f} {c['eth_hold']:>+5.2f} " f"{c['btc_dd']*100:>4.0f}% {c['eth_dd']*100:>4.0f}%{flag}") # Eligible = minFull>=0.5, minTrades>=20. Rank by min_hold, tie-break lower maxDD. elig = [c for c in results if c["min_full"] >= 0.5 and c["min_tr"] >= 20] print(f"\nEligible cells (minFull>=0.5, minTr>=20): {len(elig)}") if elig: elig_sorted = sorted(elig, key=lambda c: (-round(c["min_hold"], 3), c["max_dd"])) print("Top by minHold (tie-break lower maxDD):") for c in elig_sorted[:6]: print(f" sl={c['sl']} tp={c['tp']}: minHold={c['min_hold']:+.2f} " f"minFull={c['min_full']:+.2f} maxDD={c['max_dd']*100:.0f}% minTr={c['min_tr']}") best = elig_sorted[0] # DD-cutting candidate: best minHold among cells with maxDD < V1-ish (lower DD priority) dd_cands = sorted(elig, key=lambda c: (c["max_dd"], -round(c["min_hold"], 3))) print("\nTop by lowest maxDD (DD-cut objective):") for c in dd_cands[:6]: print(f" sl={c['sl']} tp={c['tp']}: maxDD={c['max_dd']*100:.0f}% " f"minHold={c['min_hold']:+.2f} minFull={c['min_full']:+.2f} minTr={c['min_tr']}") print("\n=== STUDY on best-by-minHold ===") pbest = SkyhookParams(sl_atr=best["sl"], tp_atr=best["tp"], **BASE) rep = sk.study(f"P_RR_sl{best['sl']}_tp{best['tp']}", pbest) print(sk.fmt(rep)) print("causality:", sk.causality(pbest)) print("marginal:", {k: v for k, v in sk.marginal(pbest).items() if k in ("corr_full","marginal_verdict","has_insample_edge","is_hedge","robust_oos")}) try: mg = sk.marginal(pbest) print("marginal-full-keys:", list(mg.keys())) print("blend w25 uplift_hold:", mg.get("blends",{}).get("w25",{}).get("uplift_hold")) except Exception as e: print("marginal err:", e) print("\nAS_JSON_STUDY:", sk.as_json(rep)) else: print("No eligible cell — V1 base may already be at the frontier.")