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76 lines
2.5 KiB
Python
76 lines
2.5 KiB
Python
"""Multi-Asset Momentum -- relative strength across 5 assets.
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Demonstrates:
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- Multi-asset universe (5 symbols)
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- Momentum via smoothed ROC on 12h bars
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- Volatility-adjusted sizing
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Data: shared store — real market data from `data/` (see examples/README.md)
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Usage:
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python examples/03_multi_asset_momentum.py
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"""
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import os
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import time
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import manifoldbt as mbt
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from manifoldbt.indicators import close, ema, roc, high, low
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from manifoldbt.helpers import time_range, Slippage, Interval
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# -- Indicators ---------------------------------------------------------------
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mom = ema(roc(close, 14), 6) # 7-day momentum, smoothed
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avg_range = (high - low).rolling_mean(14)
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norm_vol = avg_range / (close + mbt.lit(1e-12)) # normalized volatility
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safe_vol = mbt.when(norm_vol > 0.0005, norm_vol, 0.0005)
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# -- Strategy -----------------------------------------------------------------
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signal = mbt.when(mom > 0.0, mom / safe_vol, 0.0)
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strategy = (
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mbt.Strategy.create("multi_momentum")
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.signal("momentum", mom)
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.signal("norm_vol", norm_vol)
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.size(signal * 0.01)
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.describe("Multi-asset momentum with volatility-adjusted sizing")
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)
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# -- Config -------------------------------------------------------------------
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start, end = time_range("2022-01-01", "2025-01-01")
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config = mbt.BacktestConfig(
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universe={
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"binance": ["BTC-USDT:perp", "ETH-USDT:perp", "LTC-USDT:perp",
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"DOT-USDT:perp", "XRP-USDT:perp"],
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},
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# Legacy equivalent: universe=[201, 202, 204, 206, 208]
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time_range_start=start,
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time_range_end=end,
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bar_interval=Interval.hours(12),
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initial_capital=10_000,
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execution=mbt.ExecutionConfig(
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signal_delay=1,
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max_position_pct=0.3,
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allow_short=False,
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),
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fees=mbt.FeeConfig.binance_perps(),
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slippage=Slippage.fixed_bps(2),
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warmup_bars=25,
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)
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# -- Run ----------------------------------------------------------------------
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if __name__ == "__main__":
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root = os.path.join(os.path.dirname(__file__), "..")
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data_root = os.path.abspath(os.path.join(root, "data"))
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store = mbt.DataStore(
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data_root=data_root,
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metadata_db=os.path.abspath(os.path.join(root, "metadata", "metadata.sqlite")),
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arrow_dir=os.path.join(data_root, "mega"),
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)
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t0 = time.perf_counter()
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result = mbt.run(strategy, config, store)
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elapsed = time.perf_counter() - t0
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print(result.summary())
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print(f"\nElapsed: {elapsed:.3f}s")
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mbt.plot.summary(result)
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