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Code reviewHardcr-g626
Subject Feature engineeringLevel Senior–Staff~20 minCommon in Algorithms & data structures interviewsIndustries Software development

Question

Review this Python sliding-window feature builder for next-day return prediction.

Backtests look unusually profitable. Find the bug.

What a strong answer looks like

Separate real bugs from style. Rank issues by severity, point at the root cause rather than the symptom, and suggest a concrete fix — specific and kind.

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Code to reviewpython
import numpy as npimport pandas as pd def make_window_features(prices: pd.Series, window: int = 5):    feats, targets = [], []    p = prices.values    # predict next-day return from the trailing `window` returns    rets = np.diff(p) / p[:-1]    for i in range(window, len(rets)):        x = rets[i - window : i + 1]   # trailing window of returns        y = rets[i + 1] if i + 1 < len(rets) else 0.0        feats.append(x)        targets.append(y)    return np.array(feats), np.array(targets)
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