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https://github.com/KhizarImran/backtestingfx.git
synced 2026-07-27 20:17:44 +00:00
Khizar
62 lines
1.6 KiB
Python
62 lines
1.6 KiB
Python
import math
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import pandas as pd
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from backtestingfx import Backtest, Strategy
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class MovingAverageCycle(Strategy):
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fast = 8
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slow = 24
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def next(self):
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if self.index + 1 < self.slow:
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return
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closes = [bar.close for bar in self.data[-self.slow :]]
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fast_average = sum(closes[-self.fast :]) / self.fast
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slow_average = sum(closes) / self.slow
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should_be_long = fast_average > slow_average
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if self.positions and self.positions[0].is_long != should_be_long:
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self.close_all()
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if not self.positions:
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if should_be_long:
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self.buy(0.1)
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else:
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self.sell(0.1)
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def sample_data():
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timestamps = pd.date_range("2025-01-01", periods=360, freq="h", tz="UTC")
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closes = [
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1.1000 + 0.0040 * math.sin(i / 13) + 0.0010 * math.sin(i / 3)
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for i in range(len(timestamps))
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]
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opens = [closes[0], *closes[:-1]]
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return pd.DataFrame(
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{
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"open": opens,
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"high": [max(open_, close) + 0.0004 for open_, close in zip(opens, closes)],
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"low": [min(open_, close) - 0.0004 for open_, close in zip(opens, closes)],
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"close": closes,
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"volume": [800 + int(300 * abs(math.sin(i / 9))) for i in range(len(timestamps))],
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},
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index=timestamps,
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)
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data = sample_data()
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backtest = Backtest(
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data,
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MovingAverageCycle,
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cash=10_000,
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commission=3.5,
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spread=0.00002,
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)
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print(backtest.run())
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print(f"\nReport written to: {backtest.plot('backtestingfx-report.html')}")
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