The Smart Beta Mirage

77 Pages Posted: 1 Jul 2020 Last revised: 20 Mar 2023

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 Hong Kong Polytechnic University

Date Written: June 9, 2020

Abstract

We document and explain the sharp performance deterioration of smart beta indexes after the corresponding smart beta ETFs are launched for investment. While smart beta is purported to deliver excess returns through factor exposures, the market-adjusted return of smart beta indexes drops from about 3% “on paper” before ETF listings to about -0.50% to -1% after ETF listings. This performance decline cannot be explained by variation in factor premia, strategic timing, or diminishing returns to scale. Instead, we find strong evidence of data mining in the construction of smart beta indexes, which helps ETFs attract flows, as investors respond positively to 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 or http://dx.doi.org/10.2139/ssrn.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 Hong Kong Polytechnic University ( email )

Hong Kong
Hong Kong

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