Feature Neutralization (Residualization) - Quant Researcher Interview Question
Difficulty: Medium
Category: machine_learning
Asked at: D.E. Shaw, Numerai, Citadel, Two Sigma, WorldQuant
Topics: linear_regression, statistics, numpy, alpha_research
Problem Description
Feature neutralization is a critical preprocessing step in quantitative finance used to isolate "pure alpha" by removing linear exposure to common risk factors like the market. This process involves regressing a raw trading signal against a risk factor and extracting the residuals, ensuring the strategy bets on unique insights rather than broad market movements.
Task
Implement a function solution(signal, market) that neutralizes a raw alpha signal with respect to a market risk factor using line
Practice this medium researcher interview question on MyntBit - the LeetCode for quants with 200+ quant interview questions for Jane Street, Citadel, Two Sigma, and other top quantitative finance firms.