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Factor Exposure Analysis 109: Linear vs Lasso vs Elastic Net

Finding the optimal regression method for factor exposure analysis

Abhik Roy, CFA
10 min read
14 Oct 2024

SUMMARY

  • Different regression techniques can be used to measure factor exposures
  • Linear regression provides the best in-sample fit
  • However, regularized models like Elastic Net and Lasso provide better out-of-sample fits in general

INTRODUCTION

Since the launch of the first U.S. ETF in 1993, which was the SPDR S&P 500 ETF, the industry has seen massive inflows into these ETFs with about $9 trillion in assets as of May 2024. Investors have a wide range of funds to choose from, some of which focus on equity factors like value or momentum. But this brings another challenge as measuring the exposure to these factors becomes pivotal to evaluating these funds.

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