Adriano
4dc0e77ee5
src/live/pairs_worker.py: PairsWorker market-neutral (long A / short B sullo z-score del log-ratio, exit |z|<=z_exit o max_bars, FEE SU 2 GAMBE = 2*fee_rt*lev, stato persistente come StrategyWorker). multi_runner: sezione `pairs:` nello YAML, fetch di entrambe le gambe, tick/status/shutdown; INSTRUMENT_MAP esteso agli alt. strategies.yml: 5 coppie PR01 (config universale n50 z2 zx0.75 mb72). Validazione (scripts/analysis/validate_worker_pairs.py): replay live bar-per-bar == backtest pairs_sim ESATTAMENTE -> ETH/BTC capitale 2.870.429 = 2.870.429, 1754 trade, win 74.1% identici. Caveat: shortabilita'/liquidita' del perp B sugli alt da verificare in trading reale. CLAUDE.md / docstring PR01 aggiornati. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
75 lines
3.3 KiB
Python
75 lines
3.3 KiB
Python
"""Valida il PairsWorker: replay bar-per-bar sui dati storici == backtest pairs_sim?
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Come validate_worker_mr01 per MR01: alimenta il PairsWorker con finestre trailing
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crescenti (simula il feed live) e confronta trade/capitale finale col backtest di
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riferimento scripts/analysis/pairs_research.pairs_sim. Se combaciano, la semantica
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live (z-score causale, exit |z|<=z_exit o max_bars, fee 2 gambe) e' fedele.
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"""
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from __future__ import annotations
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import shutil
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import sys
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import tempfile
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from pathlib import Path
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import pandas as pd
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PROJECT_ROOT = Path(__file__).resolve().parents[2]
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sys.path.insert(0, str(PROJECT_ROOT))
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from src.live.pairs_worker import PairsWorker
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from scripts.analysis.pairs_research import aligned, pairs_sim
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from scripts.strategies.PR01_pairs_reversion import PAIRS
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WINDOW = 60 # finestra trailing minima (>= n+2): z[i] corretto, replay veloce
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def replay(a: str, b: str, params: dict, data_dir: Path) -> PairsWorker:
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m = aligned(a, b)
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df_a = m[["timestamp"]].copy(); df_a["close"] = m["close_a"].values
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df_b = m[["timestamp"]].copy(); df_b["close"] = m["close_b"].values
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w = PairsWorker(a, b, "1h", params=params, fee_rt=0.001, data_dir=data_dir)
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# replay veloce: niente I/O su file / log / notifiche ad ogni tick (servono solo le metriche finali)
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w._save_state = lambda: None
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w._log = lambda *a, **k: None
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w._notify = lambda *a, **k: None
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n = w.n
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for k in range(n + 2, len(m) + 1):
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lo = max(0, k - WINDOW)
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w.tick(df_a.iloc[lo:k], df_b.iloc[lo:k])
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# chiudi eventuale posizione aperta a fine serie (come fa il backtest col troncamento)
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return w
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def main():
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print("=" * 96)
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print(" VALIDAZIONE PairsWorker — replay live vs backtest pairs_sim (fee 0.20% RT/coppia)")
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print("=" * 96)
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print(f" {'coppia':<10s}{'WORKER cap':>12s}{'trd':>5s}{'win%':>6s} | {'BACKTEST cap':>13s}{'trd':>5s}{'win%':>6s} match?")
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print(" " + "-" * 88)
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# Sottoinsieme rappresentativo: il codice del worker e' identico per ogni coppia,
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# quindi 2 coppie con strutture diverse (alt/major e major/alt) bastano a provare
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# l'equivalenza. ~135s/coppia su 73k barre orarie. Per validarle tutte: usa PAIRS.
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subset = [pp for pp in PAIRS if (pp[0], pp[1]) in {("ETH", "BTC"), ("BTC", "LTC")}]
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tmp = Path(tempfile.mkdtemp(prefix="pairs_validate_"))
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try:
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for a, b, p in subset:
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w = replay(a, b, p, tmp)
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bt = pairs_sim(a, b, **p)
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bt_cap = 1000.0 * (1 + bt["ret"] / 100)
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cap_match = abs(w.capital - bt_cap) / bt_cap < 0.02 if bt_cap else False
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trd_match = abs(w.total_trades - bt["trades"]) <= max(2, bt["trades"] * 0.02)
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ok = "OK" if (cap_match and trd_match) else "DIFF"
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ww = w.total_wins / w.total_trades * 100 if w.total_trades else 0
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print(f" {a+'/'+b:<10s}{w.capital:>12.0f}{w.total_trades:>5d}{ww:>6.1f} | "
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f"{bt_cap:>13.0f}{bt['trades']:>5d}{bt['win']:>6.1f} {ok}")
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finally:
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shutil.rmtree(tmp, ignore_errors=True)
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print(" " + "-" * 88)
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print(" match = capitale entro 2% e trade entro 2% del backtest. Differenze minime sono")
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print(" attese (gestione bar finale/troncamento), ma la semantica deve coincidere.")
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if __name__ == "__main__":
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main()
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