Algorithmic Trading, Quantified.

import polars as pl
from adrs import Alpha
from adrs.data import DataInfo, DataColumn, DataProcessor

class SpreadZScore(Alpha):
    def __init__(self, window: int = 20):
        self.window = window

    def next(self, data_df: pl.DataFrame) -> pl.DataFrame:
        spread = pl.col("close_bybit") - pl.col("close_binance")
        zscore = (
            (spread - spread.rolling_mean(self.window))
            / spread.rolling_std(self.window, ddof=1)
        )
        df = (
            data_df.with_columns(zscore.alias("zscore"))
            .filter(pl.col("zscore").is_finite())
        )
        df = df.with_columns(
            pl.when(pl.col("zscore") >= 1.5)
              .then(1)
              .when(pl.col("zscore") <= -1.5)
              .then(0)
              .otherwise(None)
              .forward_fill()
              .fill_null(strategy="zero")
              .alias("signal")
        )
        return df