danielmjrr
160ed2f948
Memory-mapped tickstores, a nogil numba replay kernel validated trade-for-trade against an independent reference implementation, purged walk-forward CV, an append-only FDR registry, tick-exact labels, and online changepoint detection. 129 tests, 4 runnable examples on synthetic data, CI for linux/macos.
47 lines
1.6 KiB
Python
47 lines
1.6 KiB
Python
"""N-bar breakout on M5 bars, exiting on the opposite breakout.
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Run: python examples/breakout.py
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"""
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import numpy as np
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import tickreplay as tr
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LOOKBACK = 20
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def main():
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time_ns, bid, ask = tr.synth.generate_ticks(days=30, seed=11)
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store = tr.TickStore(time_ns, bid, ask)
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bars = store.bars("M5")
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# shift(1) keeps the current bar out of its own reference range.
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prior_high = bars["high"].shift(1).rolling(LOOKBACK).max()
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prior_low = bars["low"].shift(1).rolling(LOOKBACK).min()
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state = np.where(bars["close"] > prior_high, 1,
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np.where(bars["close"] < prior_low, -1, 0)).astype("int8")
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# Fire on the bar that breaks out, not on every bar that stays beyond the range.
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signal = np.where(state != np.r_[np.int8(0), state[:-1]], state, 0).astype("int8")
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config = tr.Config(sl=4.0, tp=8.0, max_hold="8h", exit_on_opposite=True, cost=0.05)
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result = tr.replay(store, bars, signal, config)
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print(f"ticks {len(store):>12,}")
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print(f"M5 bars {len(bars):>12,}")
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print(f"signals {int((signal != 0).sum()):>12,} ({LOOKBACK}-bar breakout)")
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print("config sl=4.0 tp=8.0 max_hold=8h exit_on_opposite=True cost=0.05")
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print()
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for key, value in result.summary().items():
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print(f"{key:<14}{value:>12.4f}" if isinstance(value, float)
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else f"{key:<14}{value:>12,}")
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print()
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print("exit reasons")
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counts = result.trades["exit_reason"].value_counts()
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for reason, count in counts.items():
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print(f" {reason:<10}{count:>6,}{count / counts.sum():>8.1%}")
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if __name__ == "__main__":
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main()
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