scholarly journals DO THE FAMA AND FRENCH FIVE-FACTOR MODEL FORECAST WELL USING ANN?

2019 ◽  
Vol 20 (1) ◽  
pp. 168-191 ◽  
Author(s):  
Muhammad Naveed Jan ◽  
Usman Ayub

Forecasting the stock returns in the emerging markets is challenging due to their peculiar characteristics. These markets exhibit linear as well as nonlinear features and Conventional forecasting methods partially succeed in dealing with the nonlinear nature of stock returns. Contrarily, Artificial Neural Networks (ANN) is a flexible machine learning tool which caters both the linear and nonlinear markets. This paper investigates the forecasting ability of ANN by using Fama and French five-factor model. We construct ANN’s based on the composite factors of the FF5F model to predict portfolio returns in two stages; in stage one, the study identifies the best-fit combination of training, testing, and validation along with the number of neurons full sample period. In stage two, the study uses this best combination to forecast the model under 48-months rolling window analysis. In-sample and out-sample comparisons, regression, and goodness of fit test and actual and predicted values of the stock returns of our ANN model reveal that the proposed model accurately predicts the one-month ahead returns. Our findings reinforce the investment concept that the markets compensate the high-risk portfolios more than mid and low beta portfolios and the methodology will significantly improve the return on investment of the investors.

2018 ◽  
Vol 68 (4) ◽  
pp. 617-638 ◽  
Author(s):  
Francisco Jareño ◽  
María de la O González ◽  
Marta Tolentino ◽  
Sara Rodríguez

This paper studies the sensitivity of share prices of Spanish companies included in the IBEX-35 to changes in different explanatory variables, such as market returns, interest rates and factors proposed by Fama and French (1993, 2015) between 2000 and 2016. In addition, for robustness, this paper analyses whether the sensitivity of stock returns is different between two periods: precrisis and recent financial crisis. The results confirm that, in general, all the considered factors are relevant. Furthermore, “market return” and “size” factors show greater explanatory power, together with the “value” factor in the crisis period. Regarding the analysis at sector level, “Oil and Energy”, “Basic Materials, Industry and Construction” and “Financial and Real Estate Services” sectors appear to be highly sensitive to changes in the risk factors included in the asset pricing factor model.


2020 ◽  
Vol 13 (4) ◽  
pp. 127-146
Author(s):  
Fahim Ullah Khan ◽  
Ahmad Fraz ◽  
Asif Ali

This paper examines the role of financial distress premium in explaining the stock returns of banking sector in Pakistan using the sample of twenty listed banks for the period of 2008 to 2018. The study has used two methodologies. Firstly, multifactor model approach of Fama and French (1992) is used to test the financial distress premium (additional risk factor) where portfolio returns are regressed with factor premiums in time series framework. Fama and French (1993) argue that the relationship between the stock return and the selected characteristics occur for that reason these characteristics are proxies for non-diversifiable factor risk. So, the characteristic based model approach of Huang (2009) is used in cross-sectional regression framework where stock returns are regressed with the characteristics. The results indicate that the proposed four factor model is applicable in the banking sector of Pakistan where financial distress premium is priced by the market. The characteristic based model shows insignificant impact of distress proxy of Altman Z score on the banking returns. It suggests that the cross-sectional returns are explained on the covariance structure of returns not the characteristics in the Pakistani banking stocks. The findings of the study suggests that the financial distress is important and consider while forming their portfolios.


2018 ◽  
Vol 3 (1) ◽  
pp. 35
Author(s):  
Nsama Musawa ◽  
Prof. Sumbye Kapena ◽  
Dr . Chanda Shikaputo

Purpose: The capital asset pricing model (CAPM)  is one of  the basic models in the security price analysis.Many asset pricing models have been developed to improve the CAPM.Among such models is the latest  Fama and French five factor model which is being  empirically tested in various stock markets. This study tested the five factor model in comparison to the capital asset pricing model. Testing the Fama and French Five factor model in comparison to the CAPM was important because the CAPM is widely taken to be the basic model in the security price analysis. Methodology: The Fama and French methodology was used to test  the data from an emerging market, the Lusaka Securities Exchange. A deductive, quantitative research design and secondary data from the Lusaka Securities Exchange was used. Data was analyzed using multiple regression. Results: The results indicate that the Five Factor model is better than the CAPM in capturing variation in the stock returns. The Adjusted R-squared for the five factor model from all individual portfolio sorting was 0.9, while that for the CAPM was 0.13 Unique contribution to theory, practice and policy: This study has contributed to theory in that it has added a voice to the ongoing debt on the suitability of  the new Fama and French Five Factor model which is at the cutting hedge in finance theory.Further the study is from developing capital market. Keywords:, CAPM, Stock returns, Fama and French five factor model


2011 ◽  
Vol 9 (3) ◽  
pp. 383 ◽  
Author(s):  
Márcio André Veras Machado ◽  
Otávio Ribeiro de Medeiros

This paper is aims to analyze whether a liquidity premium exists in the Brazilian stock market. As a second goal, we include liquidity as an extra risk factor in asset pricing models and test whether this factor is priced and whether stock returns were explained not only by systematic risk, as proposed by the CAPM, by Fama and French’s (1993) three-factor model, and by Carhart’s (1997) momentum-factor model, but also by liquidity, as suggested by Amihud and Mendelson (1986). To achieve this, we used stock portfolios and five measures of liquidity. Among the asset pricing models tested, the CAPM was the least capable of explaining returns. We found that the inclusion of size and book-to-market factors in the CAPM, a momentum factor in the three-factor model, and a liquidity factor in the four-factor model improve their explanatory power of portfolio returns. In addition, we found that the five-factor model is marginally superior to the other asset pricing models tested.


2020 ◽  
Vol 14 (2) ◽  
pp. 77-102
Author(s):  
Simon M. S. So

This paper aimed to evaluate and compare individual performances and contributions of seven well-known factors, selected from four widely cited asset pricing models: (1) the capital asset pricing model of Sharpe (1964), (2) the three-factor model of Fama and French (1993) the augmented four-factor model of Carhart (1997), (3) the five-factor model of Fama and French (2015), and (4) the illiquidity model of Amihud, et al. (2015) in capturing the time-series variation of stock returns and absorbing the 12 prominent anomalies. The anomalies were constructed by forming long-short portfolios, and regressions were run to examine their monthly returns from 2000 to 2019. We found that there is no definite and absolute “king” in the factor zoo in the Chinese stock market, and size is the relative “king” that can absorb the maximum number of anomalies. Evidence also indicates that the three-factor model of Fama and French may still play an important role in pricing assets in the Chinese stock market. The results can provide investors with a reliable risk factor and help investors form an effective investment strategy. This paper contributes to asset pricing literature in the Chinese market.G1


2017 ◽  
Vol 21 (6) ◽  
pp. 851-874 ◽  
Author(s):  
Márcio André Veras Machado ◽  
Robert Faff ◽  
Suelle Cariele de Souza e Silva

Abstract This study aims to investigate whether investment and profitability are priced and if they partially explain the variations of stock returns in the Brazilian stock market, according to the Fama and French's (2015) five-factor model. By using time series and cross-section regression, we found that book-to-market, momentum and liquidity are associated with stock returns whereas investment and profitability were not significant. We also found that there is no investment premium in Brazil. Therefore, motivated by the importance of B/M, momentum and liquidity to the Brazilian stock market, as well as by the poor performance of profitability and investment, we document that Keene and Peterson's (2007) five-factor model is superior to all other models, especially the five-factor model by Fama and French (2015).


2021 ◽  
pp. 135481662199298
Author(s):  
Francisco Jareño ◽  
Ana Escribano ◽  
M Pilar Torres

This research explores the sensitivity of the returns of some selected European companies to changes in the explanatory factors proposed during the sample period between January 2000 and December 2019. We focus on listed companies in the tourism and services sector and estimate an extension of the Fama and French five-factor model (2015) by applying the quantile regression approach. Specifically, this study starts from the Fama and French risk factors and adds the nominal interest rates, a momentum and momentum reversal factors and a traded liquidity factor. For robustness, this research divides the whole sample period into three sub-periods: pre-crisis, crisis and post-crisis. In line with the previous literature, the explanatory power of this factor model shows a U-shape, which is compatible with the highest R2 coefficients in the extreme quantiles, as well as in extreme stages of the economy, that is, in the bullish and bearish market states.


2016 ◽  
Vol 42 (12) ◽  
pp. 1180-1207 ◽  
Author(s):  
Greg Gregoriou ◽  
François-Éric Racicot ◽  
Raymond Théoret

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.


2018 ◽  
Vol 3 (4) ◽  
pp. 77-83
Author(s):  
Ferikawita M. Sembiring

Objective - Previous research by this author has stated that the market overreaction phenomenon occurs in the Indonesian capital market and the CAPM (Capital Asset Pricing Model) is able to explain portfolio returns. However, CAPM is still debated along with the emergence of the other asset pricing models, such as the multifactor model proposed by Fama and French. The aim of this research is to test the ability of that model to explain the returns of portfolios formed under market overreaction conditions. Methodology/Technique - The data used in this study is the same as that of the previous research, which includes winner and loser portfolio data formed in market overreaction conditions, particularly on the Indonesian Stock Exchange, between July 2005 and December 2015. The multifactor models used include a three-factor model consisting of the factors of market, firm size, firm value, and a five-factor model with the added factors of profitability and investment. To obtain more accurate results, GARCH econometric models were also used in addition to standard test models for obtaining unbiased results. Findings - This research concludes that market factors (Rm-Rf), firm size (SMB), and firm value (HML), are able to explain the winner and loser portfolio returns well. However, when the factors of profitability (RMW) and investment (CMA) are added into the three-factor model, the RMW and CMA explained the returns negatively and inconsistently when the GARCH model is implemented. Novelty – These results imply that the three-factor model is more accurate than the five-factor model, contrary to the previous findings of Fama and French. Type of Paper - Empirical. Keywords: Fama and French Model; Five-factor Model; Market Overreaction; Three-factor Model; Portfolio. JEL Classification: G11, G12, G14


2021 ◽  
Vol 14 (3) ◽  
pp. 96
Author(s):  
Nina Ryan ◽  
Xinfeng Ruan ◽  
Jin E. Zhang ◽  
Jing A. Zhang

In this paper, we test the applicability of different Fama–French (FF) factor models in Vietnam, we investigate the value factor redundancy and examine the choice of the profitability factor. Our empirical evidence shows that the FF five-factor model has more explanatory power than the FF three-factor model. The value factor remains important after the inclusion of profitability and investment factors. Operating profitability performs better than cash and return-on-equity (ROE) profitability as a proxy for the profitability factor in FF factor modeling. The value factor and operating profitability have the biggest marginal contribution to a maximum squared Sharpe ratio for the five-factor model factors, highlighting the value factor (HML) non-redundancy in describing stock returns in Vietnam.


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