68 lines
2.7 KiB
Python
68 lines
2.7 KiB
Python
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"""Mini 5Y test - first 10 dates only"""
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import sys, time
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sys.stdout.reconfigure(encoding='utf-8', errors='replace')
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print('MINI 5Y BACKTEST (first 10 dates only)')
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print('='*50)
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t0 = time.time()
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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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from nautilus_dolphin.nautilus.esf_alpha_orchestrator import NDAlphaEngine
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from nautilus_dolphin.nautilus.adaptive_circuit_breaker import AdaptiveCircuitBreaker
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VBT_DIR = Path(r"C:\Users\Lenovo\Documents\- DOLPHIN NG HD HCM TSF Predict\vbt_cache_klines")
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META_COLS = {'timestamp', 'scan_number', 'v50_lambda_max_velocity', 'v150_lambda_max_velocity',
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'v300_lambda_max_velocity', 'v750_lambda_max_velocity', 'vel_div',
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'instability_50', 'instability_150'}
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parquet_files = sorted(VBT_DIR.glob("*.parquet"))[:10] # Only 10 files
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print(f'Processing {len(parquet_files)} files...')
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# ACB
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acb = AdaptiveCircuitBreaker()
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date_strings = [pf.stem for pf in parquet_files]
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acb.preload_w750(date_strings)
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print(f'ACB w750 threshold: {acb._w750_threshold:.6f}')
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# Engine
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engine = NDAlphaEngine(
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initial_capital=25000.0, vel_div_threshold=-0.02, vel_div_extreme=-0.05,
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min_leverage=0.5, max_leverage=5.0, leverage_convexity=3.0,
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fraction=0.20, fixed_tp_pct=0.0095, stop_pct=1.0, max_hold_bars=120,
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use_direction_confirm=True, dc_lookback_bars=7, dc_min_magnitude_bps=0.75,
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dc_skip_contradicts=True, dc_leverage_boost=1.0, dc_leverage_reduce=0.5,
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use_asset_selection=True, min_irp_alignment=0.45,
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use_sp_fees=True, use_sp_slippage=True,
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sp_maker_entry_rate=0.62, sp_maker_exit_rate=0.50,
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use_ob_edge=True, ob_edge_bps=5.0, ob_confirm_rate=0.40,
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lookback=100, use_alpha_layers=True, use_dynamic_leverage=True, seed=42,
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)
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engine.set_acb(acb)
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engine.set_esoteric_hazard_multiplier(0.0)
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# Process
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for i, pf in enumerate(parquet_files):
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ds = pf.stem
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df = pd.read_parquet(pf)
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acols = [c for c in df.columns if c not in META_COLS]
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# Compute vol regime
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bp = df['BTCUSDT'].values if 'BTCUSDT' in df.columns else None
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dvol = np.full(len(df), np.nan)
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if bp is not None:
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for j in range(50, len(bp)):
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seg = bp[max(0,j-50):j]
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if len(seg)<10: continue
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dvol[j] = float(np.std(np.diff(seg)/seg[:-1]))
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vol_p60 = 0.001 # Fixed for mini test
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vol_ok = np.where(np.isfinite(dvol), dvol > vol_p60, False)
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stats = engine.process_day(ds, df, acols, vol_regime_ok=vol_ok)
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print(f" [{i+1}] {ds}: trades={stats['trades']} P&L=${stats['pnl']:+.0f} cap=${engine.capital:,.0f}")
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print('='*50)
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print(f'DONE in {time.time()-t0:.1f}s')
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print(f'Final capital: ${engine.capital:,.2f}')
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print(f'Total trades: {len(engine.trade_history)}')
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