Adriano
a6056c4ac7
Strategie testate: - Mean reversion oraria: edge minimo - Funding rate proxy: edge minimo - Vol selling (straddle): 72% acc, 82% ann ✅ - Momentum 5m: fallita (20% acc) - Gap fade sessione: edge moderato ETH - Iron condor: non funziona simulato - VRP refined: 88-90% acc, 200-325% ann, DD 1.6-2.5% ✅✅ Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
133 lines
4.3 KiB
Python
133 lines
4.3 KiB
Python
"""S2-05: Gap fade + overnight reversal.
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Crypto non ha gap di apertura classici, ma ha "gap di sessione":
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- Asia open (00 UTC): tende a continuare il trend USA precedente
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- EU open (07 UTC): spesso corregge eccessi notturni
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- USA open (13-14 UTC): alta volatilità, breakout o reversal
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Strategia: fai fade dell'overextension al cambio sessione.
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Se il prezzo ha fatto >1.5% nella sessione precedente, aspettati reversal.
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"""
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from __future__ import annotations
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import sys
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sys.path.insert(0, ".")
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import numpy as np
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import pandas as pd
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from src.data.downloader import load_data
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FEE = 0.001
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INITIAL = 1000
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LEVERAGE = 3
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def run_gap_fade(asset, tf="1h"):
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print(f"\n{'#'*60}")
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print(f" {asset} {tf} — GAP FADE / SESSION REVERSAL")
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print(f"{'#'*60}")
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df = load_data(asset, tf)
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close = df["close"].values
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high = df["high"].values
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low = df["low"].values
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n = len(close)
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split = int(n * 0.7)
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timestamps = pd.to_datetime(df["timestamp"], unit="ms", utc=True)
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hours = timestamps.dt.hour.values
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session_opens = {
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"asia": 0,
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"eu": 7,
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"usa": 14,
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}
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configs = [
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# (session_name, lookback_hours, entry_thr, hold_hours, stop_pct, name)
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("eu", 7, 0.015, 4, 0.012, "eu_fade_1.5pct"),
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("eu", 7, 0.02, 4, 0.015, "eu_fade_2pct"),
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("eu", 7, 0.01, 6, 0.01, "eu_fade_1pct_6h"),
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("usa", 7, 0.015, 4, 0.012, "usa_fade_1.5pct"),
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("usa", 7, 0.02, 4, 0.015, "usa_fade_2pct"),
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("asia", 8, 0.02, 6, 0.015, "asia_fade_2pct"),
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("eu", 7, 0.025, 3, 0.015, "eu_fade_2.5pct_fast"),
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("usa", 6, 0.015, 3, 0.01, "usa_fade_fast"),
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]
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for session, lookback, entry_thr, hold, stop, name in configs:
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capital = float(INITIAL)
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correct = 0
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total = 0
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daily_trades = {}
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session_hour = session_opens[session]
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for i in range(max(split, lookback + 1), n - hold):
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if hours[i] != session_hour:
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continue
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day = timestamps.iloc[i].strftime("%Y-%m-%d")
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if daily_trades.get(day, 0) >= 1:
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continue
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prev_ret = (close[i] - close[i - lookback]) / close[i - lookback]
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direction = None
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if prev_ret > entry_thr:
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direction = "short" # fade the rally
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elif prev_ret < -entry_thr:
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direction = "long" # fade the dump
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if direction is None:
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continue
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entry = close[i]
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exit_price = close[min(i + hold, n - 1)]
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for j in range(i + 1, min(i + hold + 1, n)):
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if direction == "long":
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if (close[j] - entry) / entry >= stop * 2:
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exit_price = close[j]
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break
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if (entry - close[j]) / entry >= stop:
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exit_price = close[j]
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break
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else:
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if (entry - close[j]) / entry >= stop * 2:
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exit_price = close[j]
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break
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if (close[j] - entry) / entry >= stop:
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exit_price = close[j]
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break
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exit_price = close[j]
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if direction == "long":
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trade_ret = (exit_price - entry) / entry
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else:
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trade_ret = (entry - exit_price) / entry
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net = trade_ret * LEVERAGE - FEE * 2 * LEVERAGE
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capital += capital * 0.2 * net
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capital = max(capital, 0)
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total += 1
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if trade_ret > 0:
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correct += 1
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daily_trades[day] = daily_trades.get(day, 0) + 1
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if total < 15:
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continue
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acc = correct / total * 100
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ret = (capital - INITIAL) / INITIAL * 100
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test_days = (n - split) / 24
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test_years = test_days / 365.25
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ann = ((capital / INITIAL) ** (1 / test_years) - 1) * 100 if test_years > 0 and capital > 0 else -100
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dpnl = (capital - INITIAL) / test_days if test_days > 0 else 0
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days_active = len(daily_trades)
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tag = "✅" if acc >= 58 and ann >= 30 else ""
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print(f" {name:25s}: trades={total:4d} acc={acc:.1f}% ret={ret:+.1f}% ann={ann:+.1f}% €/day={dpnl:.2f} active={days_active} {tag}")
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for asset in ["ETH", "BTC"]:
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run_gap_fade(asset)
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