The q-factor model and the redundancy of the value factor: An application to hedge funds

Racicot, François-Éric; Théoret, Raymond

doi:10.1057/jam.2016.22

Cited by 12 publications

(3 citation statements)

References 21 publications

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“…33. Using another large databasei.e., the Greenwich Alternative Investment databasewe also find the same investment profile for hedge funds (Racicot and Théoret, 2016b).…”

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confidence: 55%

Theq-factor and the Fama and French asset pricing models: hedge fund evidence

Gregoriou

Racicot

Théoret

2016

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Purpose The purpose of this paper is to test the new Fama and French (2015) five-factor model relying on a thorough sample of hedge fund strategies drawn from the Barclay’s Global hedge fund database. Design/methodology/approach The authors use a stepwise regression to identify the factors of the q-factor model which are relevant for the hedge fund strategy analysis. Doing so, the authors account for the Fung and Hsieh seven factors which prove very useful in the explanation of the hedge fund strategies. The authors introduce interaction terms to depict any interaction of the traditional Fama and French factors with the factors associated with the q-factor model. The authors also examine the dynamic dimensions of the risk-taking behavior of hedge funds using a BEKK procedure and the Kalman filter algorithm. Findings The results show that hedge funds seem to prefer stocks of firms with a high investment-to-assets ratio (low conservative minus aggressive (CMA)), on the one hand, and weak firms’ stocks (low robust minus weak (RMW)), on the other hand. This combination is not associated with the conventional properties of growth stocks – i.e., low high minus low (HML) stocks – which are related to firms which invest more (low CMA) and which are more profitable (high RMW). Finally, small minus big (SMB) interacts more with RMW while HML is more correlated with CMA. The conditional correlations between SMB and CMA, on the one hand, and HML and RMW, on the other hand, are less tight and may change sign over time. Originality/value To the best of the authors’ knowledge, the authors are the first to cast the new Fama and French five-factor model in a hedge fund setting which account for the Fung and Hsieh option-like trading strategies. This approach allows the authors to better understand hedge fund strategies because q-factors are useful to study the dynamic behavior of hedge funds.

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“…33. Using another large databasei.e., the Greenwich Alternative Investment databasewe also find the same investment profile for hedge funds (Racicot and Théoret, 2016b).…”

supporting

confidence: 55%

Theq-factor and the Fama and French asset pricing models: hedge fund evidence

Gregoriou

Racicot

Théoret

2016

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“…Almost all risk factors are insignificant, except for the value coefficient in Strategy 1, which is significant at 5%. Racicot and Thcicot concluded that the HML factor is not redundant for many strategies, the excess returns here can also be explained by the value factor [12].…”

Section: Constructing Portfolio Based On Q-factormentioning

confidence: 64%

Constructing Trading Strategies by Applying and Adapting Q-factor Model in the Australian Market

Zhang

2024

HBEM

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The Q-factor model is a quantitative pricing model similar to the Fama-French multi-factor model, which is an investment approach using investment (IA) and profitability (ROE) as the significant factors. This paper collects historical data (1987~2022) from Australian stocks and constructs long-short portfolios to investigate the effectiveness of applying this model in the Australian market. Net returns will be validated by Carhart regression. Finally, the optimal factor portfolios and trading strategies will be tested for factor substitution based on cumulative return trends and risk-return metrics. Overall, both the Q-factor model and the augmented Q-factor effectively analyzed investments in the Australian market. The difference between theoretical and practical-based long-short is mainly due to the abnormal ranking performance of individual factors, especially during the COVID-19 pandemic. In most cases, strategies based on actual data sorting generate better risk-return outcomes than theory-based approaches, suggesting that the models must be continually adapted to suit Australia's unique economic and market conditions.

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“…For the pricing of Australian equity market, Chiah et al (2016) finds that the value factor remains significant even with the inclusion of additional factors. Similarly, Racicot and Theoret (2016) finds that the value risk factor is not redundant when evaluating hedge fund strategies. Further, the value factor remains significant despite the inclusion of profitability and investment factors in explaining stock returns in Pakistan Shaikh et al (2019), South Korea Kang et al (2019), Jordan Gharaibeh & Al-Qudah (2020), Vietnam Ryan et al (2021), China and India (Singh et al, 2022).…”

Section: Research Themes and Discussionmentioning

confidence: 99%

How Well has Fama-French Five-Factor Model Explained Asset Returns? - A Systematic Literature Review

Sohor,

Low

2024

IJARAFMS

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Despite producing mixed findings, the Fama and French's (2015) model has been widely used to explain stock returns. This paper conducts a systematic literature review of the Fama and French's (2015) five factor model to evaluate its empirical validity in estimating the average returns of stocks. The review revolves around four major themes: performance of the fivefactor model in explaining stock returns and whether it outperforms the three-factor model in stock returns estimation; predictive power of the two new factors in the five-factor model namely profitability and investment factors; value factor's redundancy for describing average stock returns after accounting for profitability and investment factors; and the exploration of other factors that could enhance the model's explanatory power. The paper used the PRISMA (The Preferred Reporting Items for Systematic Reviews and Meta-Analysis) method as a search strategy to conduct the systematic reviews. Highly cited articles published the Web of Science database from 2015 to 2022 were explored and a final sample of 61 were used in the review. The reviews find that in most studies, the Fama-French five-factor model is superior to the three-factor model in predicting the average stock market return at the national and regional levels. On the predictive power of profitability and investment factors, the findings were mixed. Similar conclusion was reached for the redundancy of value factor in explaining stock returns. Several other factors have also been found to increase the explanatory power of the five-factor model. The systematic literature of this paper evaluates several specific research questions related to Fama-French models, thereby providing researchers an understanding of the research topic and its evolution over time. Future review could be further expanded further to include articles from the Scopus-indexed journals. Insights from this paper are also useful for investors engaging in factor investing and in formulating asset allocation strategy.

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The q-factor model and the redundancy of the value factor: An application to hedge funds

Cited by 12 publications

References 21 publications

Theq-factor and the Fama and French asset pricing models: hedge fund evidence

Theq-factor and the Fama and French asset pricing models: hedge fund evidence

Constructing Trading Strategies by Applying and Adapting Q-factor Model in the Australian Market

How Well has Fama-French Five-Factor Model Explained Asset Returns? - A Systematic Literature Review

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