The Smart Beta Mirage

44 Pages Posted: 1 Jul 2020 Last revised: 24 Jul 2020

See all articles by Shiyang Huang

Shiyang Huang

The University of Hong Kong - Faculty of Business and Economics

Yang Song

University of Washington - Michael G. Foster School of Business

Hong Xiang

The University of Hong Kong

Date Written: June 9, 2020

Abstract

We document sharp performance deterioration of smart beta indexes after the corresponding smart beta ETFs are listed for investments. Adjusted by aggregate market return, the average return of smart beta indexes drops from 2.77% per year “on paper” before ETF listing to −0.44% per year after ETF listing. This performance deterioration cannot be explained by strategic timing in ETF listing nor explained by time trend in factor premia. We find evidence of data mining in constructing smart beta indexes as the post-ETF-listing performance decline is much sharper for indexes that are more susceptible to data mining in backtests. Our results caution the risk of data mining in the proliferation of ETF offerings as investors respond strongly to the stellar performance in backtests.

Keywords: ETFs, factor investing, smart beta, data mining

JEL Classification: G10, G20

Suggested Citation

Huang, Shiyang and Song, Yang and Xiang, Hong, The Smart Beta Mirage (June 9, 2020). Available at SSRN: https://ssrn.com/abstract=3622753

Shiyang Huang

The University of Hong Kong - Faculty of Business and Economics ( email )

Pokfulam Road
Hong Kong
China

Yang Song (Contact Author)

University of Washington - Michael G. Foster School of Business ( email )

Box 353200
Seattle, WA 98195-3200
United States

Hong Xiang

The University of Hong Kong ( email )

Hong Kong

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