Build a pair trading strategy for two related instruments using their price ratio. Measure how far the ratio moves from its recent average, generate opposite buying and selling signals, and close positions when the ratio returns near that average.
Pair trading strategy. Trades mean reversion using the spread/ratio Z-score of two correlated instruments. Requires at least two instruments.
Review the instructions the agent will receive before you install.
Select two highly correlated instruments (such as stocks from the same industry or BTC/ETH), monitor how far their price ratio (or spread) deviates from the mean, and trade against extreme deviations while waiting for mean reversion.
ratio = close_A / close_Bmean = ratio.rolling(lookback).mean(), std = ratio.rolling(lookback).std()z = (ratio - mean) / stdcodes array length = 2)leg1), and the second is B (leg2)| Parameter | Default | Description |
|---|---|---|
| lookback | 60 | Lookback window for mean and standard deviation |
| entry_z | 2.0 | Entry Z-score threshold |
| exit_z | 0.5 | Exit Z-score threshold |
config.json{
"source": "tushare",
"codes": ["601318.SH", "601628.SH"],
"start_date": "2023-01-01",
"end_date": "2024-12-31",
"initial_cash": 1000000,
"commission": 0.001,
"extra_fields": null
}
Cryptocurrency version:
{
"source": "okx",
"codes": ["BTC-USDT", "ETH-USDT"],
"start_date": "2024-01-01",
"end_date": "2024-12-31",
"initial_cash": 1000000,
"commission": 0.001,
"extra_fields": null
}
codes must contain exactly 2 instruments, no more and no lessNaN, so fill signals with 0pip install pandas numpy
0.5 = long, -0.5 = short, 0 = flatNo reviews yet. Tell others what you thought.
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