Mirror, mirror on the wall, what’s the best factor model of them all? We at Quantpedia are probably not the only one asking this question. A lot of competing factor models are described in the academic literature and used in practice. That’s the reason why we consider a new research paper written by Matthias Hanauer really valuable. He compared several commonly employed factor models across non-U.S. developed and emerging market countries and answered the question from the beginning of this paragraph. Which model seems the winner? The six-factor model proposed in Barillas et al. (2019) that substitutes the classic value factor in the Fama and French (2018) six-factor model for a monthly updated value factor …
Authors: Hanauer
Title: A Comparison of Global Factor Models
Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3546295
Abstract:
I compare commonly employed factor models across 47 non-U.S. developed and emerging market countries by ranking them based on their maximum Sharpe ratios. Consistent with the U.S. evidence presented in Barillas, Kan, Robotti, and Shanken (2019), I find that the factor models of Fama and French (2015, 2018), Hou, Xue, and Zhang (2015), and Stambaugh and Yuan (2017) are dominated by a six-factor model that includes cash-based profitability and momentum factors, as well as a value factor that is updated monthly. The result is robust in out-of-sample tests, across subperiods, across global regions, and to methodological changes. The main problem for the dominated factors models is that they do not explain the monthly updated value factor. Hence, I conclude that the value factor is not redundant.
Notable quotations from the academic research paper:
“Researchers attempt to explain differences in expected returns with factor models that use a parsimonious set of factors. The capital asset pricing model (CAPM) developed by Sharpe (1964) and Lintner (1965) was one of the earliest of these models and contains only one factor, the value-weighted market portfolio of all financial assets. If one controls for size effects, market beta does not, whereas size and book-to-market equity explain cross-sectional differences in average returns. This analysis led to the Fama and French (1993) three-factor model, which contains market, size, and value factors. This model was for many years the industry standard, sometimes augmented with the momentum factor of Jegadeesh and Titman (1993). Fama and French (2015) extend their three-factor model to a five-factor model by including profitability and investment factors.
| What about Data? Look at Quantpedia’s Algo Trading Promo Codes. |
An important limitation of the papers mentioned above is that all of them are based solely on United States (U.S.) market data. This observation reflects the findings of Karolyi (2016, p. 2049) that empirical research focused on non-U.S. studies are underrepresented, as only “16% (23%) of all empirical studies published in the top four (fourteen) Finance journals examine non-US markets. Comparisons of a broad set of popular factor models for international markets are scarce.
This study is the first to compare a broad set of common and recently proposed factor models using a comprehensive non-U.S. sample. Specifically, I investigate the following models for 47 international markets from 1990 to 2018:
(i) the CAPM,
(ii) the Fama and French (1993) three-factor model,
(iii) the Fama and French (2015) five-factor model,
(iv) the Fama and French six-factor model (the five-factor model augmented with momentum),
(v) the Fama and French (2018) six-factor model that substitutes the operating profitability factor used in their original six-factor
(vi) the Hou et al. (2015) q-factor model that includes profitability and investment factors in addition to market and size factors,
(vii) the Stambaugh and Yuan (2017) mispricing model that extends the CAPM by adding a size factor and two composite mispricing factors, management and performance
(viii) the six-factor model proposed in Barillas et al. (2019) that substitutes the classic value factor in the Fama and French (2018) six-factor model for a monthly updated value factor
My main findings are summarized as follows.
First, I document that all employed factors exhibit positive and, other than the market and size factors, significant average returns outside the U.S. Furthermore, the documented patterns are quite similar to what is reported in Barillas et al. (2019) for the U.S.
Second, I find that the six-factor model proposed in Barillas et al. (2019) spans an annualized maximum Sharpe ratio of 2.36 that is substantially and significantly higher than those of competing factor models. The winning model shows a maximum Sharpe ratio improvement of about 20% and 50% compared to the Fama and French six-factor models with cash-based operating profitability and operating profitability factors, respectively. Compared to the remaining models, the improvement is even larger. Therefore, I conclude that a six-factor model that includes factors for cash-based profitability and momentum factors, and a monthly updated value factor, dominates the factor models of Fama and French (1993, 2015, 2018), Hou et al. (2015), and Stambaugh and Yuan (2017) in international markets. This finding is consistent with the U.S. evidence.
Third, I demonstrate that the main problem with the dominated factors models is that they cannot explain the returns of the monthly updated value factor. Hence, I conclude in contrast to Fama and French (2015) that the value factor is not redundant. Finally, my results are robust in out-of-sample tests, across five-year subperiods, across different regions (Asia Pacific, Europe, Japan, and emerging markets), and to various methodological changes.”
Are you looking for strategies applicable in bear markets? Check Quantpedia’s Bear Market Strategies
Are you looking for more strategies to read about? Sign up for our newsletter or visit our Blog or Screener.
Do you want to learn more about Quantpedia Premium service? Check how Quantpedia works, our mission and Premium pricing offer.
Do you want to learn more about Quantpedia Pro service? Check its description, watch videos, review reporting capabilities and visit our pricing offer.
Are you looking for historical data or backtesting platforms? Check our list of Algo Trading Discounts.
Or follow us on:
Facebook Group, Facebook Page, Twitter, Linkedin, Medium or Youtube
Share onLinkedInTwitterFacebookRefer to a friendBe first to know, when we publish new content
