• Media type: E-Article
  • Title: Financial risk and better returns through smart beta exchange-traded funds?
  • Contributor: Bowes, Jordan [Author]; Ausloos, Marcel [Author]
  • imprint: Basel: MDPI, 2021
  • Language: English
  • DOI: https://doi.org/10.3390/jrfm14070283
  • ISSN: 1911-8074
  • Keywords: Carhart four-factor model ; G23 ; G12 ; exchange-traded funds ; Sharpe-Lintner capital asset pricing model ; Fama-French three-factor model ; smart beta
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  • Description: Smart beta exchange-traded funds (SB ETFs) have caught the attention of investors due to their supposed ability to offer a better risk-return trade-off than traditionally structured passive indices. Yet, research covering the performance of SB ETFs benchmarked to traditional cap-weighted market indices remains relatively scarce. There is a lack of empirical evidence enforcing this phenomenon. Extending the work of Glushkov ("How Smart are "Smart Beta" ETFs? …", 2016), we provide a quantitative analysis of the performance of 145 EU-domicile SB ETFs over a 12 year period, from 30 December 2005 to 31 December 2017, belonging to 9 sub-categories. We outline which criteria were retained such that the investigated ETFs had at least 12 consecutive monthly returns data. We consider three models: the Sharpe-Lintner capital asset pricing model, the Fama-French three-factor model, and the Carhart four-factor model, discussed in the literature review sections, in order to assess the factor exposure of each fund to market, size, value, and momentum factors, according to the pertinent model. In order to do so, the sample of SB ETFs and benchmarks underwent a series of numerical assessments in order to aim at explaining both performance and risk. The measures chosen are the Annualised Total Return, the Annualised Volatility, the Annualised Sharpe Ratio, and the Annualised Relative Return (ARR). Of the sub-categories that achieved greater ARRs, only two SB categories, equal and momentum, are able to certify better risk-adjusted returns.
  • Access State: Open Access
  • Rights information: Attribution (CC BY)