chore(reset): v2.0.0 — storico certificato Deribit mainnet, ripartenza pulita

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>

Old/scripts/strategies/DIP01_dip_buy.py

@@ -0,0 +1,58 @@
+"""DIP01 — Dip-buy mean-reversion single-asset (z-score sotto-banda). Honest family.
+
+Replica live della logica validata in scripts/analysis/honest_improve2.dip_market_gated
+(con market_n=0, come lo sleeve DIP01_BTC del portafoglio): compra quando lo z-score del
+prezzo rispetto a SMA(n) incrocia sotto -z_in; esce a TP=SMA, SL=close-sl_atr*ATR, o max_bars.
+"""
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+
+PROJECT_ROOT = Path(__file__).resolve().parents[2]
+sys.path.insert(0, str(PROJECT_ROOT))
+
+from src.strategies.base import Strategy, Signal  # noqa: E402
+
+
+def _atr(df, n=14):
+    h, l, c = df["high"].values, df["low"].values, df["close"].values
+    pc = np.roll(c, 1); pc[0] = c[0]
+    tr = np.maximum(h - l, np.maximum(np.abs(h - pc), np.abs(l - pc)))
+    return pd.Series(tr).rolling(n).mean().values
+
+
+class Dip01DipBuy(Strategy):
+    name = "DIP01_dip_buy"
+    description = "Dip-buy mean-reversion single-asset (z-score), exit TP=SMA/SL=ATR/max_bars"
+    default_assets = ["BTC"]
+    default_timeframes = ["1h"]
+    fee_rt = 0.001
+    leverage = 3.0
+    position_size = 0.15
+
+    def generate_signals(self, df: pd.DataFrame, ts: pd.DatetimeIndex,
+                         n: int = 50, z_in: float = 2.5, sl_atr: float = 2.5,
+                         max_bars: int = 24, **params) -> list[Signal]:
+        c = df["close"].values
+        ma = pd.Series(c).rolling(n).mean().values
+        sd = pd.Series(c).rolling(n).std().values
+        a = _atr(df, 14)
+        z = (c - ma) / np.where(sd == 0, np.nan, sd)
+        # Edge minimo: salta i dip il cui TP (la media) è entro il costo round-trip. 0 = off.
+        min_tp_frac = params.get("min_tp_frac", 0.0)
+        out: list[Signal] = []
+        for i in range(n + 14, len(c)):
+            if np.isnan(z[i]) or np.isnan(a[i]) or np.isnan(ma[i]):
+                continue
+            if z[i] <= -z_in and z[i - 1] > -z_in:
+                if min_tp_frac > 0 and abs(ma[i] - c[i]) / c[i] <= min_tp_frac:
+                    continue                          # TP entro le fee -> non eseguibile in utile
+                out.append(Signal(idx=i, direction=1, entry_price=float(c[i]),
+                                  metadata={"tp": float(ma[i]),
+                                            "sl": float(c[i] - sl_atr * a[i]),
+                                            "max_bars": int(max_bars)}))
+        return out