scholarly journals A Comparative Study between the Fama and French Three-Factor Model and the Fama and French Five-Factor Model: Evidence from the Egyptian Stock Market

2019 ◽  
Vol 12 (1) ◽  
pp. 52 ◽  
Author(s):  
Nada S. Ragab ◽  
Rabab K. Abdou ◽  
Ahmed M. Sakr
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Factor Model ◽  
Five Factor Model ◽  
Pricing Models ◽  
Asset Pricing Models ◽  
Time Period ◽  
Model Evidence ◽  
Fama And French ◽  
Three Factor

The focus of this paper is to test whether the Fama and French three-factor and five factor models can capture the variations of returns in the Egyptian stock market as one of the growing emerging markets over the time-period July 2005 to June 2016. To achieve this aim, following Fama and French (2015), the authors construct the Fama and French factors and three sets of test portfolios which are: 10 portfolios double-sorted on size and the BE/ME ratio, 10 portfolios double-sorted on size and operating profitability, and 10 portfolios double-sorted on size and investment for the Egyptian stock market. Using time-series regressions and the GRS test, the results show that although both models cannot be rejected as valid asset pricing models when applied to portfolios double-sorted on size and the BE/ME ratio, they still leave substantial variations in returns unexplained given their low adjusted R2 values. Similarly, when the two models are applied to portfolios double-sorted on size and investment, the results of the GRS test show that both models cannot be rejected. However, when the two models are applied to portfolios double-sorted on size and operating profitability, the results of the GRS test show that both models are strongly rejected which imply that both models leave substantial variations in returns related to size and profitability unexplained. Specifically, the biggest challenge to the two models is the big portfolio with weak profitability which generate a significantly negative intercept implying that the models overestimate its return.

scholarly journals Applicability of Investment and Profitability Effects in Asset Pricing Models

2017 ◽  
Vol 21 (6) ◽  
pp. 851-874 ◽  
Author(s):  
Márcio André Veras Machado ◽  
Robert Faff ◽  
Suelle Cariele de Souza e Silva
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Stock Returns ◽  
Factor Model ◽  
Five Factor Model ◽  
Poor Performance ◽  
Pricing Models ◽  
Asset Pricing Models ◽  
The Poor ◽  
Fama And French

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).

scholarly journals Examining asset pricing models in emerging markets: Evidence from Egypt

2018 ◽  
Vol 16 (1) ◽  
pp. 50-57 ◽  
Author(s):  
Mohamed A. Shaker ◽  
Marwan M. Abdeldayem
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
Stock Exchange ◽  
Research Effort ◽  
Five Factor Model ◽  
Pricing Models ◽  
Time Series Regression ◽  
Asset Pricing Models ◽  
Time Period ◽  
Three Factor

The study aims at executing five tantamount asset pricing models in Egypt, in particular: 1) “the CAPM”, 2) “the Fama-French three-factor model (1993)”, 3) “the Carhart model (1997)”, 4) “the four-factor model of Chan and Faff (2005)”, and 5) “the five-factor model (Liquidity and Momentum-Augmented Fama-French three factor model)”. This research effort pursues Fama-French arranging approach in view of the size and Book-to-Market proportion (B-M ratio) for 55 securities out of the most 100 stocks in the Egyptian Stock Exchange (EGX) over a five years’ time period. We utilized “the time series regression of Black, Jensen and Scholes (1972)”. The findings of the study revealed that in terms of predictability, FF three-factor model prompts a significant improvement over the CAPM, while alternate models do not demonstrate a noteworthy increment over the FF three factor model.

Market anomalies, asset pricing models, and stock returns: evidence from the Indian stock market

2015 ◽  
Vol 9 (3) ◽  
pp. 306-328 ◽  
Author(s):  
Saumya Ranjan Dash ◽  
Jitendra Mahakud
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Pricing Models ◽  
Market Anomalies ◽  
Content Type ◽  
Asset Pricing Models ◽  
Asset Pricing Anomalies ◽  
Pricing Anomalies ◽  
Fama And French ◽  
Three Factor

Purpose – This paper aims to investigate whether the use of conditional and unconditional Fama and French (1993) three-factor and Carhart (1997) four-factor asset pricing models (APMs) captures the role of asset pricing anomalies in the context of emerging stock market like India. Design/methodology/approach – The first step time series regression approach has been used to drive the risk-adjusted returns of individual securities. For examining the predictability of firm characteristics or asset pricing anomalies on the risk-adjusted returns of individual securities, the panel data estimation technique has been used. Findings – Fama and French (1993) three-factor and Carhart (1997) four-factor model in their unconditional specifications capture the impact of book-to-market price and liquidity effects completely. When alternative APMs in their conditional specifications are tested, the importance of medium- and long-term momentum effects has been captured to a greater extent. The size, market leverage and short-term momentum effects still persist even in the case of alternative unconditional and conditional APMs. Research limitations/implications – The empirical analysis does not extend for different market scenarios like high and low volatile market or good and bad macroeconomic environment. Because of the constraint of data availability, the authors could not include certain important anomalies like net operating assets, change in gross profit margin, external equity and debt financing and idiosyncratic risk. Practical implications – Although the active investment approach in stock market shares a common ground of semi-strong form of market efficiency hypothesis which also supports the presence of asset pricing anomalies, less empirical evidence has been explored in this regard to support or repute such belief of practitioners. Our empirical findings make an attempt in this regard to suggest certain anomaly-based trading strategy that can be followed for active portfolio management. Originality/value – From an emerging market perspective, this paper provides out-of-sample empirical evidence toward the use of conditional Fama and French three-factor and Carhart four-factor APMs for the complete explanation of market anomalies. This approach retains its importance with respect to the comprehensiveness of analysis considering alternative APMs for capturing unique effects of market anomalies.

scholarly journals Modelos de Precificação de Ativos e o Efeito Liquidez: Evidências Empíricas no Mercado Acionário Brasileiro

2011 ◽  
Vol 9 (3) ◽  
pp. 383 ◽  
Author(s):  
Márcio André Veras Machado ◽  
Otávio Ribeiro de Medeiros
Keyword(s):  
Asset Pricing ◽  
Stock Returns ◽  
Factor Model ◽  
Five Factor Model ◽  
Explanatory Power ◽  
Liquidity Premium ◽  
Pricing Models ◽  
Portfolio Returns ◽  
Asset Pricing Models ◽  
Three Factor

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.

Who is King in Factor Zoo? Case of the Chinese Stock Market

2020 ◽  
Vol 14 (2) ◽  
pp. 77-102
Author(s):  
Simon M. S. So
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Stock Returns ◽  
Factor Model ◽  
Five Factor Model ◽  
Investment Strategy ◽  
Capital Asset Pricing ◽  
Chinese Stock Market ◽  
Fama And French ◽  
Three Factor

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

scholarly journals Role of leverage and liquidity risk in asset pricing: evidence from Indian stock market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mehak Jain ◽  
Ravi Singla
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
Five Factor Model ◽  
Explanatory Power ◽  
Liquidity Risk ◽  
Pricing Models ◽  
Content Type ◽  
Asset Pricing Models ◽  
Three Factor ◽  
Better Than

Purpose Asset pricing revolves around the core aspects of risk and expected return. The main objective of the study is to test different asset pricing models for the Indian securities market. This paper aims to analyse whether leverage and liquidity augmented five-factor model performs better than Capital Asset Pricing Model (CAPM), Fama and French three-factor model, leverage augmented four-factor model and liquidity augmented four-factor model. Design/methodology/approach The data for the current study comprises records on prices of securities that are part of the Nifty 500 index for a time frame of 14 years, that is, from October 2004 to September 2017 consisting of 183 companies using time series regression. Findings The results indicate that the five-factor model performs better than CAPM and the three-factor model. The model outperforms leverage augmented and liquidity augmented four-factor models. The empirical evidence shows that the five-factor model has the highest explanatory power among the entire asset pricing models considered. Practical implications The present study bears certain useful implications for various stakeholders including fund managers, investors and academicians. Originality/value This study presents a five-factor model containing two additional factors, that is, leverage and liquidity risk along with the Fama-French three-factor model. These factors are expected to give more value to the model in comparison to the Fama-French three-factor model.

Evaluating alternative performance benchmarks for Indian mutual fund industry

2017 ◽  
Vol 14 (2) ◽  
pp. 222-250 ◽  
Author(s):  
Sanjay Sehgal ◽  
Sonal Babbar
Keyword(s):  
Asset Pricing ◽  
Mutual Fund ◽  
Factor Model ◽  
Five Factor Model ◽  
Content Type ◽  
Asset Pricing Model ◽  
Fund Managers ◽  
Asset Pricing Models ◽  
Performance Benchmarks ◽  
Fama And French

Purpose The purpose of this paper is to perform a relative assessment of performance benchmarks based on alternative asset pricing models to evaluate performance of mutual funds and suggest the best approach in Indian context. Design/methodology/approach Sample of 237 open-ended Indian equity (growth) schemes from April 2003 to March 2013 is used. Both unconditional and conditional versions of eight performance models are employed, namely, Jensen (1968) measure, three-moment asset pricing model, four-moment asset pricing model, Fama and French (1993) three-factor model, Carhart (1997) four-factor model, Elton et al. (1999) five-index model, Fama and French (2015) five-factor model and firm quality five-factor model. Findings Conditional version of Carhart (1997) model is found to be the most appropriate performance benchmark in the Indian context. Success of conditional models over unconditional models highlights that fund managers dynamically manage their portfolios. Practical implications A significant α generated over and above the return estimated using Carhart’s (1997) model reflects true stock-picking skills of fund managers and it is, therefore, worth paying an active management fee. Stock exchanges and credit rating agencies in India should construct indices incorporating size, value and momentum factors to be used for purpose of benchmarking. Originality/value The study adds new evidence as to applicability of established asset pricing models as performance benchmarks in emerging market India. It examines role of higher order moments in explaining mutual fund returns which is an under researched area.

scholarly journals Identifying outliers in asset pricing data with a new weighted forward search estimator

2020 ◽  
Vol 31 (84) ◽  
pp. 458-472
Author(s):  
Alexandre Aronne ◽  
Luigi Grossi ◽  
Aureliano Angel Bressan
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
The United States ◽  
Estimation Methods ◽  
Annual Data ◽  
Forward Search ◽  
Pricing Models ◽  
Asset Pricing Models ◽  
The Impact ◽  
Three Factor

ABSTRACT The purpose of this work is to present the Weighted Forward Search (FSW) method for the detection of outliers in asset pricing data. This new estimator, which is based on an algorithm that downweights the most anomalous observations of the dataset, is tested using both simulated and empirical asset pricing data. The impact of outliers on the estimation of asset pricing models is assessed under different scenarios, and the results are evaluated with associated statistical tests based on this new approach. Our proposal generates an alternative procedure for robust estimation of portfolio betas, allowing for the comparison between concurrent asset pricing models. The algorithm, which is both efficient and robust to outliers, is used to provide robust estimates of the models’ parameters in a comparison with traditional econometric estimation methods usually used in the literature. In particular, the precision of the alphas is highly increased when the Forward Search (FS) method is used. We use Monte Carlo simulations, and also the well-known dataset of equity factor returns provided by Prof. Kenneth French, consisting of the 25 Fama-French portfolios on the United States of America equity market using single and three-factor models, on monthly and annual basis. Our results indicate that the marginal rejection of the Fama-French three-factor model is influenced by the presence of outliers in the portfolios, when using monthly returns. In annual data, the use of robust methods increases the rejection level of null alphas in the Capital Asset Pricing Model (CAPM) and the Fama-French three-factor model, with more efficient estimates in the absence of outliers and consistent alphas when outliers are present.

scholarly journals MULTIFACTOR ASSET PRICING ANALYSIS OF THE BALTIC STOCK MARKET

Ekonomika ◽  
2010 ◽  
Vol 89 (4) ◽  
pp. 85-95 ◽  
Author(s):  
Raimonds Lieksnis
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Factor Model ◽  
Stock Market Index ◽  
Cross Sectional ◽  
Economic Significance ◽  
Market Index ◽  
Fama And French ◽  
The Baltic ◽  
Three Factor

This study investigates whether the Fama–French three-factor asset pricing model is applicable for explaining cross-sectional returns of stocks listed in the Baltic stock exchanges. Findings confirm the validity and economic significance of the three-factor model for the Baltic stock market: only investors who chose to invest in value stocks during the reference period achieved positive returns by matching or beating the returns of the stock market index. The monthly returns of 8 Latvian, 13 Estonian and 27 Lithuanian company stocks are analyzed for the time period from June 2002 till February 2010 by the methodology presented in Davis, Fama, and French (2000). Cross-sectional multivariate regression is calculated with stock portfolios representing the book-to-market and capitalization of companies as independent variables along with the stock market index. The study concludes that these three factors in the three-factor model are statistically significant, but, in line with earlier studies, regression intercepts are significantly different from zero and the model is not statistically confirmed.p>

Multi-factor asset pricing models in emerging and developed markets

2019 ◽  
Vol 46 (3) ◽  
pp. 360-380
Author(s):  
Vaibhav Lalwani ◽  
Madhumita Chakraborty
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
Five Factor Model ◽  
Superior Performance ◽  
International Studies ◽  
Pricing Models ◽  
Content Type ◽  
Developed Markets ◽  
Asset Pricing Models ◽  
Pricing Errors

Purpose The purpose of this paper is to compare the performance of various multifactor asset pricing models across ten emerging and developed markets. Design/methodology/approach The general methodology to test asset pricing models involves regressing test asset returns (left-hand side assets) on pricing factors (right-hand side assets). Then the performance of different models is evaluated based on how well they price multiple test assets together. The parameters used to compare relative performance of different models are their pricing errors (GRS statistic and average absolute intercepts) and explained variation (average adjusted R2). Findings The Fama-French five-factor model improves the pricing performance for stocks in Australia, Canada, China and the USA. The pricing in these countries appears to be more integrated. However, the superior performance in these four countries is not consistent across a variety of test assets and the magnitude of reduction in pricing errors vis-à-vis three- or four-factor models is often economically insignificant. For other markets, the parsimonious three-factor model or its four-factor variants appear to be more suitable. Originality/value Unlike most asset pricing studies that use test assets based on variables that are already used to construct RHS factors, this study uses test assets that are generally different from RHS sorts. This makes the tests more robust and less biased to be in favour of any multifactor model. Also, most international studies of asset pricing tests use data for different markets and combine them into regions. This study provides the evidence from ten countries separately because prior research has shown that locally constructed factors are more suitable to explain asset prices. Further, this study also tests for the usefulness of adding a quality factor in the existing asset pricing models.

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