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Can Machine Learning Help to Select Portfolios of Mutual Funds?

Part of the Bath AFL - QF & Fintech Research Seminar Series

  • 28 Jun 2021, 2.00pm to 28 Jun 2021, 3.00pm BST (GMT +01:00)
  • This is an online event.
  • This event is free

Victor DeMiguel, London Business School, will discuss his paper.

Abstract

Identifying outperforming mutual funds ex-ante is a notoriously difficult task. We use machine learning to exploit numerous fund characteristics and construct portfolios of equity funds that earn out-of-sample annual alpha of 4.2% net of costs. We show that such performance is the joint outcome of both exploiting multiple fund characteristics and allowing for flexibility in the relation between characteristics and performance. We demonstrate that even retail investors can benefit from investing in actively managed funds. The performance of our portfolios has declined over time, however, consistent with increased competition in asset markets and diseconomies of scale at the industry level.

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