The Smart Beta Mirage

The Smart Beta Mirage

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Event type: Seminars

9 October 2020 from 2.00 pm - 3.30 pm 9 Oct 2020 2:00 pm 9 Oct 2020 3:30 pm


Speaker: Hong Xiang, The University of Hong Kong

Profile of Hong Xiang
Hong Xiang

Hong is a PhD candidate at The University of Hong Kong. Hong works on various topics in asset pricing and institutional investors.


  • Shiyang Huang, The University of Hong Kong
  • Yang Song, The University of Washington

Abstract: We document and explain sharp performance deterioration of smart beta indexes after the corresponding smart beta ETFs are listed for investments. While smart beta claims to provide excess returns through factor exposures,  adjusted by the aggregate market return, the 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. In contrast, we find strong 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 against the risk of data mining in the proliferation of ETF offerings as investors respond strongly to the stellar performance in backtests.