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Difficulty: Medium
Category: machine_learning
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Topics: factor_neutralization, cross_sectional, ols_regression, alpha_isolation, risk_factors
Factor-neutral portfolios remove systematic exposures to known risk factors, isolating stock-specific alpha from common sources of return variation. Cross-sectional regression against factor loadings at each rebalance date is the standard approach in quantitative equity research for producing residual returns that are orthogonal to target factors. Task Implement the function factor_neutralize(returns: list, factor_exposures: list) -> list to neutralize a cross-section of stock returns against a
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