Files
PythagorasGoal/Old/scripts/waste/W23_inside_bar.py
Adriano Dal Pastro 14522262e6 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>
2026-06-19 15:20:59 +00:00

132 lines
4.1 KiB
Python

"""IB01 — Inside Bar Breakout.
Pattern di compressione a singola candela: quando una barra ha high < prev high
E low > prev low, il prezzo si sta comprimendo. Al breakout del range della
inside bar, segui la direzione.
17% delle candele 15m sono inside bars → frequenza altissima.
IN:
- OHLCV DataFrame
- Parametri: min_consecutive (N inside bars consecutivi),
volume_filter, breakout_confirm
OUT:
- Signal al breakout del range dell'inside bar
- BacktestResult
Logica:
1. Identifica N inside bars consecutivi (compressione)
2. Quando il prezzo rompe il range → entra nella direzione del breakout
3. Filtro: volume al breakout > media
4. Hold fisso
"""
from __future__ import annotations
import sys
sys.path.insert(0, ".")
import numpy as np
import pandas as pd
from src.strategies.base import Strategy, Signal
class InsideBarBreakout(Strategy):
name = "IB01_inside_bar"
description = "Inside bar breakout — compressione a singola candela"
default_assets = ["BTC", "ETH"]
default_timeframes = ["15m", "1h"]
fee_rt = 0.002
def generate_signals(self, df, ts, **params):
c = df["close"].values
h = df["high"].values
l = df["low"].values
v = df["volume"].values
n = len(c)
min_consec = params.get("min_consecutive", 2)
use_vol = params.get("vol_filter", False)
min_range_pct = params.get("min_range_pct", 0.002)
# Volume media
vol_ma = np.full(n, np.nan)
for i in range(20, n):
vol_ma[i] = np.mean(v[i - 20:i])
signals = []
consec = 0
mother_high = 0.0
mother_low = 0.0
for i in range(1, n - 1):
is_inside = h[i] <= h[i - 1] and l[i] >= l[i - 1]
if is_inside:
if consec == 0:
mother_high = h[i - 1]
mother_low = l[i - 1]
consec += 1
else:
if consec >= min_consec:
range_pct = (mother_high - mother_low) / mother_low if mother_low > 0 else 0
if range_pct < min_range_pct:
consec = 0
continue
# Breakout detection sulla barra corrente
if c[i] > mother_high:
direction = 1
elif c[i] < mother_low:
direction = -1
else:
consec = 0
continue
# Volume filter
if use_vol and not np.isnan(vol_ma[i]):
if v[i] < vol_ma[i] * 1.2:
consec = 0
continue
signals.append(Signal(
idx=i, direction=direction, entry_price=c[i],
metadata={"consec": consec, "range_pct": round(range_pct * 100, 3)},
))
consec = 0
return signals
if __name__ == "__main__":
strategy = InsideBarBreakout()
configs = [
("2ib", {"min_consecutive": 2}),
("3ib", {"min_consecutive": 3}),
("4ib", {"min_consecutive": 4}),
("2ib+vol", {"min_consecutive": 2, "vol_filter": True}),
("3ib+vol", {"min_consecutive": 3, "vol_filter": True}),
("2ib r>0.3%", {"min_consecutive": 2, "min_range_pct": 0.003}),
("3ib r>0.3%", {"min_consecutive": 3, "min_range_pct": 0.003}),
]
all_results = []
for label, params in configs:
for asset in ["BTC", "ETH"]:
for tf in ["15m", "1h"]:
for hold in [3, 6]:
r = strategy.backtest(asset, tf, hold=hold, **params)
if r and r.trades >= 30:
r.strategy_name = f"IB01 {label} h={hold}"
all_results.append(r)
all_results.sort(key=lambda r: r.accuracy, reverse=True)
print(f"\n{'=' * 120}")
print(f" IB01 INSIDE BAR BREAKOUT — TOP 20")
print(f"{'=' * 120}")
for r in all_results[:20]:
r.print_summary()
if all_results:
all_results[0].print_yearly()