mirror of
https://github.com/manifoldbt/manifoldbt.git
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Jimmy7892
6ba4691a02
- Cross-exchange backtesting (Pro) - Dict universe format (provider-based symbol resolution) - Exogenous data support (register_exo + exo() expressions) - Provider-based data layout (binance/1h/TICKER.arrow) - Preload fix for provider layout - Exo column resampling for multi-resolution - Pro gate for cross-exchange (clean exit) - ATR/ADX rolling SMA fix - Precise mode hybrid fills
76 lines
2.4 KiB
Python
76 lines
2.4 KiB
Python
"""Strategy template — copy this file and modify.
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Usage:
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python examples/00_template.py
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"""
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import os
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from time import perf_counter
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import manifoldbt as mbt
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from manifoldbt.indicators import close
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from manifoldbt.helpers import time_range, Slippage, Interval
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# -- Indicators ---------------------------------------------------------------
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# All 45+ indicators available: rsi, ema, sma, bollinger, macd, atr, etc.
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# See: from manifoldbt.indicators import <tab> for full list
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zscore = close.zscore(60)
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# -- Strategy -----------------------------------------------------------------
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# mbt.when(condition, value_if_true, value_if_false)
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# - Omit 3rd arg → hold current position
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# - Nest mbt.when() for multiple conditions
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#
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# Examples:
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# signal = mbt.when(rsi < 30, 0.5, mbt.when(rsi > 70, 0.0))
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# signal = mbt.when(fast_ema > slow_ema, 1.0, -1.0)
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signal = mbt.when(zscore < -1.0, 1.0, # oversold → long
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mbt.when(zscore > 1.0, 0.0)) # overbought → exit, else hold
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strategy = (
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mbt.Strategy.create("my_strategy")
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.signal("zscore", zscore)
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.size(signal)
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.describe("Z-score mean reversion")
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# .stop_loss(pct=3.0)
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# .take_profit(pct=5.0)
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# .trailing_stop(pct=2.0)
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)
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# -- Config -------------------------------------------------------------------
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start, end = time_range("2021-01-01", "2026-01-01")
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config = mbt.BacktestConfig(
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universe={"binance": ["BTC-USDT:perp"]},
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time_range_start=start,
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time_range_end=end,
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bar_interval=Interval.minutes(1), # bar resolution
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initial_capital=10_000,
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execution=mbt.ExecutionConfig(
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allow_short=False,
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max_position_pct=1.0,
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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=60,
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output_resolution=Interval.hours(1), # Pro: sub-daily, Community: capped to daily
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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 = perf_counter()
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result = mbt.run(strategy, config, store)
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print(result.summary())
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print(f"\nElapsed: {perf_counter() - t0:.2f}s")
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mbt.plot.tearsheet(result, show=True)
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