Adriano Dal Pastro
14522262e6
Reset del progetto su fondamenta verificate dopo la scoperta che l'intera libreria "validata OOS" era artefatto di feed contaminato (print fantasma del feed Cerbero TESTNET + storico Binance/USDT). - Storico ricostruito da Deribit MAINNET (ccxt pubblico, tokenless) e CERTIFICATO (certify_feed.py): BTC/ETH puliti su TUTTA la storia (mediana 2-6 bps vs Coinbase USD), integrita' OHLC + coerenza resample (maxΔ 0.00) + cross-venue OK. Alt esclusi (illiquidi/divergenti: LTC/DOGE 50-82% barre flat; XRP/BNB non certificabili). - Verdetto sul feed pulito: FADE / PAIRS / XS01 / TSM01 morti (ogni portafoglio Sharpe -2.3..-3.0, DD ~40%); solo SH01 e frammenti HONEST con segnale residuo, da ri-validare in isolamento. - Cleanup "restart pulito": strategie, stack live (src/live, src/portfolio, runner/executor, yml, docker), ~100 script ricerca/gate, waste/games/ portfolios, dati non certificati + cache e 60+ diari -> archiviati in Old/ (preservati, non cancellati). Diario consolidato in un unico documento. - Skeleton ricerca tenuto: Strategy ABC + indicatori + src/fractal + src/backtest/engine + load_data; tool dati certificati (rebuild_history, certify_feed, audit_feed, multi_source_check). - Universo dati ATTIVO: solo BTC/ETH (5m/15m/1h); guardrail fisico (load_data su alt -> FileNotFoundError). Esecuzione DISABILITATA, conto flat. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
104 lines
4.4 KiB
Python
104 lines
4.4 KiB
Python
"""Validazione FINALE delle 3 strategie oneste selezionate.
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Per ciascuna: per-asset FULL/OOS/DD/anni-positivi + sweep fee (0/0.05/0.10/0.20% RT).
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Tutto NETTO, ingresso eseguibile, OOS = ultimo 30%, leva 3x.
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S1 DIP — long-only dip-buy z-score reversion (1h) [regime: reversione]
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S2 TREND — long-only EMA 20/100 trend-following (4h) [regime: momentum singolo]
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S3 ROT — rotazione cross-sectional momentum sul paniere (1d) [regime: forza relativa]
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"""
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from __future__ import annotations
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import sys
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from pathlib import Path
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import numpy as np
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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 scripts.analysis.honest_lab import atr, ema, get_df, simulate, oos_split, available_assets
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from scripts.analysis.honest_trend import simulate_position, ema_dual_signal, oos as trend_oos
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from scripts.analysis.honest_rotation import build_panel, simulate_rotation
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FEES = [0.0, 0.0005, 0.001, 0.002]
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# ---- S1 DIP ----
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def dip_entries(df, n=50, z_in=2.5, sl_atr=2.5, max_bars=24):
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c = df["close"].values
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ma = pd.Series(c).rolling(n).mean().values
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sd = pd.Series(c).rolling(n).std().values
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a = atr(df, 14)
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z = (c - ma) / np.where(sd == 0, np.nan, sd)
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ents = []
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for i in range(n + 14, len(c)):
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if np.isnan(z[i]) or np.isnan(a[i]):
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continue
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if z[i] <= -z_in and z[i - 1] > -z_in:
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ents.append({"i": i, "d": 1, "tp": ma[i], "sl": c[i] - sl_atr * a[i], "max_bars": max_bars})
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return ents
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def validate_dip(assets):
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print("\n" + "=" * 100)
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print(" S1 DIP — long-only dip-buy z-score reversion | 1h | n=50 z=2.5 sl=2.5ATR mb=24")
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print("=" * 100)
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print(f" {'Asset':<6s}{'Trd':>6s}{'Win%':>7s}{'FULL%':>9s}{'OOS%':>9s}{'DD%':>6s}{'Exp%':>6s}{'AnniP':>8s}"
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f"{' fee-sweep OOS% (0/0.05/0.10/0.20)':<40s}")
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ok = 0
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for a in assets:
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df = get_df(a, "1h"); ents = dip_entries(df)
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if len(ents) < 30:
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continue
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full = simulate(ents, df); _, oe = oos_split(ents, df); oos = simulate(oe, df)
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sweep = " ".join(f"{simulate(oe, df, fee_rt=f).ret:+.0f}" for f in FEES)
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good = full.ret > 0 and oos.ret > 0
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ok += good
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print(f" {a:<6s}{full.trades:>6d}{full.win:>7.1f}{full.ret:>+9.0f}{oos.ret:>+9.0f}"
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f"{full.dd:>6.0f}{full.exposure:>6.0f}{f'{full.pos_years}/{full.n_years}':>8s} [{sweep}]"
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f"{' OK' if good else ''}")
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print(f" -> robusto (FULL+OOS>0) su {ok}/{len(assets)} asset")
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def validate_trend(assets):
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print("\n" + "=" * 100)
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print(" S2 TREND — long-only EMA 20/100 trend | 4h")
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print("=" * 100)
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print(f" {'Asset':<6s}{'Flip':>6s}{'FULL%':>9s}{'OOS%':>9s}{'DD%':>6s}{'Exp%':>6s}{'AnniP':>8s}")
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ok = 0
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for a in assets:
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df = get_df(a, "4h"); sig = ema_dual_signal(df, 20, 100, long_only=True)
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full = simulate_position(sig, df); oos = trend_oos(sig, df)
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good = full["ret"] > 0 and oos["ret"] > 0
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ok += good
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print(f" {a:<6s}{full['flips']:>6d}{full['ret']:>+9.0f}{oos['ret']:>+9.0f}"
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f"{full['dd']:>6.0f}{full['exposure']:>6.0f}{(str(full['pos_years'])+'/'+str(full['n_years'])):>8s}"
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f"{' OK' if good else ''}")
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print(f" -> robusto su {ok}/{len(assets)} asset")
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def validate_rot(assets):
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print("\n" + "=" * 100)
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print(" S3 ROT — rotazione cross-sectional momentum | 1d | lb=60 top2 su tutto il paniere")
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print("=" * 100)
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panel = build_panel(assets, "1d")
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print(f" Paniere {list(panel.columns)} {panel.shape[0]} barre {panel.index[0].date()}->{panel.index[-1].date()}")
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print(f" {'fee RT':<10s}{'FULL%':>9s}{'OOS%':>9s}{'DD%':>6s}{'AnniP':>8s}")
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for f in FEES:
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full = simulate_rotation(panel, lookback=60, top_k=2, fee_rt=f)
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oos = simulate_rotation(panel, lookback=60, top_k=2, fee_rt=f, oos_frac=0.30)
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anni = str(full['pos_years']) + '/' + str(full['n_years'])
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print(f" {f*100:>5.2f}%RT {full['ret']:>+9.0f}{oos['ret']:>+9.0f}{full['dd']:>6.0f}{anni:>8s}")
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# per-anno alla fee reale
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full = simulate_rotation(panel, lookback=60, top_k=2, fee_rt=0.001)
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print(" per-anno (fee 0.10%): " + " ".join(f"{y}:{v:+.0f}%" for y, v in sorted(full["yearly"].items())))
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if __name__ == "__main__":
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assets = available_assets()
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print(f"VALIDAZIONE FINALE — asset disponibili: {assets}")
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validate_dip(assets)
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validate_trend(assets)
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validate_rot(assets)
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