scholarly journals Empirical Test of Fama and French Three-Factor Model in the Egyptian Stock Exchange

2020 ◽  
Vol 11 (2) ◽  
pp. 5-18
Author(s):  
Mustafa Hussein Abd-Alla ◽  
Mahmoud Sobh
Keyword(s):  
Stock Returns ◽  
Factor Model ◽  
Stock Exchange ◽  
Empirical Test ◽  
Expected Return ◽  
Book To Market Ratio ◽  
Excess Stock Returns ◽  
Fama And French ◽  
Egyptian Stock Exchange ◽  
Three Factor

We test the empirical validity of the three-factor model of Fama and French in the Egyptian Stock Exchange (EGX) using monthly excess stock returns of 50 stocks listed on the EGX from January 2014 to December 2018. Our findings do not support Fama and French three-factor model, where the coefficient of the beta was insignificant. The “SBM” coefficient and the “HML” coefficient were equal to zero and insignificant, which confirms the absence of the small firm effect and book-to-market ratio effect in the market. We conclude that there is no relation between expected return and Fama-French risk factors.

scholarly journals THE FOUR-FACTOR MODEL AND STOCK RETURNS IN BANGLADESH

2021 ◽  
Vol 6 (2) ◽  
pp. 133-149
Author(s):  
Muhammad Saifuddin Khan ◽  
Md. Miad Uddin Fahim
Keyword(s):  
Asset Pricing ◽  
Stock Returns ◽  
Factor Model ◽  
Stock Exchange ◽  
Explanatory Power ◽  
Jel Classification ◽  
Expected Return ◽  
Market Factors ◽  
Fama And French ◽  
Three Factor

For determining the expected return, and asset pricing, CAPM (Capital asset pricing model) is being used dominantly grounded on only the market (systematic) risk-factor though several anomalies have been revealed in this model. Fama and French (1993) have addressed those anomalies and developed the Three-factor model by combining size and value factors besides market factors. Over time, Carhart (1997) has further developed a model addressing momentum factor besides the three factors of Fama and French (1993) which is known as the Carhart four-factor model. Though several kinds of research have been conducted on the CAPM and three-factor model, little works have been accompanied by the Carhart four-factor model in an evolving market like Bangladesh. The goal of this work is to examine the validity of the Carhart four-factor model and examine the loftier explanatory power in Dhaka Stock Exchange (DSE). From the regression analysis of the Carhart model, we have found that market, size, value, and momentum explain the excess stock return. This study indicates that the Carhart model has the lowest GRS F-statistic, highest adjusted R-squared, and lowest Sharpe ratio in contrast to the CAPM and three-factor model which indicates the superior explanatory power and statistical validity of the Carhart model. JEL Classification Codes: G12, G13, G14.

scholarly journals The Impact of Herding on the Risk Pricing in the Egyptian Stock Exchange

2020 ◽  
Vol 11 (2) ◽  
pp. 19-37
Author(s):  
Mustafa Hussein Abd-Alla ◽  
Mahmoud Sobh
Keyword(s):  
Factor Model ◽  
Stock Exchange ◽  
Additional Risk Factor ◽  
Additional Risk ◽  
Behaviour Factor ◽  
Risk Pricing ◽  
Fama And French ◽  
The Impact ◽  
Egyptian Stock Exchange ◽  
Three Factor

We test the impact of herding behaviour on the risk pricing in the Egyptian Stock Exchange (EGX) by adding an additional risk factor reflecting herding behaviour to the Fama and French three-factor model. We construct a portfolio to mimic an additional risk factor related to herding behaviour, in addition to the original risk factors in the Fama and French three-factor model. The three-factor model will be tested in its original form and re-tested after adding the herding behaviour factor. The study is based on Hwang and Salmon methodology, in which the state space approach based on Kaman’s filter was used to measure herding behaviour. We used monthly excess stock returns of 50 stocks listed on the EGX from January 2014 to December 2018. The results do not support Fama and French model before and after adding the herding behaviour factor, therefore, there is no effect of herding behaviour on the risk pricing in the Egyptian Stock Exchange.

scholarly journals Size and Value Premium in Karachi Stock Exchange

2008 ◽  
Vol 13 (2) ◽  
pp. 1-26 ◽  
Author(s):  
Nawazish Mirza ◽  
Saima Shahid
Keyword(s):  
Stock Returns ◽  
Cross Section ◽  
Factor Model ◽  
Stock Exchange ◽  
Capital Budgeting ◽  
Market Size ◽  
Fund Managers ◽  
Fama And French ◽  
Daily Returns ◽  
Three Factor

This study evaluates the ability of the Fama and French Three Factor model to explain a cross section of stock returns in the Karachi Stock Exchange (KSE). Following Fama and French factor approach, we sorted six portfolios by size and book to market. The sorted portfolios were constituted to represent stocks from each and every sector of KSE. Using Daily returns from January 2003 to December 2007, the excess returns for each portfolio were regressed on market, size and value factors. Our findings, in general, supported the notion of the three factor model. The three factor model was able to explain the variations in returns for most of the portfolios and the results remain robust when the sample was reduced to control for the size effect. Our findings are consistent with most of the studies that suggested the validity of the three factor model in emerging markets. These results warrant for the inclusion of size and value factors for valuation, capital budgeting and project appraisals, thus, having substantial implications for fund managers, analysts and investors.

scholarly journals The Impact of the Financial Sector on Asset Pricing Tests: Evidence from the Colombo Stock Exchange

2016 ◽  
Vol 8 (2) ◽  
pp. 113
Author(s):  
Amal Peter Abeysekera ◽  
Nimal Pulukkuttige Don
Keyword(s):  
Asset Pricing ◽  
Stock Returns ◽  
Factor Model ◽  
Stock Exchange ◽  
Financial Sector ◽  
Size Premium ◽  
Fama And French ◽  
The Impact ◽  
Three Factor ◽  
Better Than

<p>This paper aims to identify how the inclusion of financial sector affects the ability of asset pricing models to explain the average stock returns in the CSE.  Most of the asset pricing researches, the firms in the financial sector are excluded on the basis that their characteristics and the leverage are notably different than firms in other industries. Therefore the objective of this study is to identify the impact of the inclusion of financial sector on the ability of the Carhart four-factor model to explain the average stock returns in the CSE and to compare its performance with the Capital Asset Pricing Model (CAPM) and the Fama and French three-factor model. The study finds that the four-factor model; incorporating the market premium, size premium, value premium and momentum premium provides a satisfactory explanation of the variation in the cross-section of average stock returns in the CSE, even when the financial sector is included. It is found that the Carhart four-factor model performs better than the CAPM in all scenarios; and that it performs notably better than the Fama and French three-factor model.However, there is no notable difference in the findings either the financial sector is included or not. </p>

Overreaction evidence from large-cap stocks

2014 ◽  
Vol 13 (4) ◽  
pp. 310-325 ◽  
Author(s):  
Tibebe Abebe Assefa ◽  
Omar A. Esqueda ◽  
Emilios C. Galariotis
Keyword(s):  
Stock Returns ◽  
Factor Model ◽  
Investment Strategy ◽  
Past Performance ◽  
Content Type ◽  
Multifactor Models ◽  
Contrarian Strategy ◽  
Fama And French ◽  
Investment Portfolios ◽  
Three Factor

Purpose – The purpose of this paper is to assess the performance of a contrarian investment strategy focusing on frequently traded large-cap US stocks. Previous criticisms that losers’ gains are not due to overreaction but due to their tendency to be thinly traded and smaller-sized firms than winners are addressed. Design/methodology/approach – Portfolios based on past performance are constructed and it is examined whether contrarian returns exist. The Capital Asset Pricing Model (CAPM), Fama and French three-factor model and the Carhart’s (1997) momentum portfolio are used to test whether excess returns are feasible in a contrarian strategy. Findings – The results show an asymmetric performance following portfolio formation. Although both, winners and losers portfolios, have gains during holding periods, losers outperform winners at all times, and with a differential of up to 29.2 per cent 36 months after portfolio formation. Furthermore, the loser and the winner portfolios’ alphas are significant, suggesting that the CAPM and the multifactor models are unable to explain return differentials between winners and losers. Our evidence supports two main conclusions. First, stock market overreaction still holds for a sample of large firms. Second, this is robust to the Fama and French’s (1993, 1996) three-factor model and Carhart’s (1997) momentum portfolio. Findings emphasize the relevance of a contrarian strategy when rebalancing investment portfolios. Practical implications – Portfolio managers can improve stock returns by selling past winners and buying previous loser large-cap US stocks. Originality/value – This paper is the first, to the authors’ knowledge, to examine frequently traded large-cap US stocks to avoid infrequent trading and size concerns.

scholarly journals Multilayer Network Risk Factor Pricing Model

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Yu Liu ◽  
Conglin Hu ◽  
Lei Wang ◽  
Kun Yang
Keyword(s):  
Risk Factor ◽  
Stock Returns ◽  
Factor Model ◽  
Positive Impact ◽  
Pricing Model ◽  
Multilayer Network ◽  
Excess Stock Returns ◽  
Network Risk ◽  
The Impact ◽  
Three Factor

This paper proposes a multilayer network risk factor pricing model to depict the impact of interactions between stocks on excess stock returns by constructing the network risk factor based on the stock multilayer network and introducing it to the traditional three-factor pricing model. According to China’s stock market data, we find that compared with the traditional three-factor model, the multilayer network risk factor pricing model can achieve higher fitting degree. Meanwhile, the multilayer network risk factor has a significant positive impact on the excess stock returns in most cases.

An Empirical Test of Capital Asset-pricing Model and Three-factor Model of Fama in Indian Stock Exchange

2018 ◽  
Vol 43 (4) ◽  
pp. 294-307
Author(s):  
Nenavath Sreenu
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
Stock Exchange ◽  
Capital Asset Pricing Model ◽  
Capital Asset Pricing ◽  
Pricing Model ◽  
Capital Asset ◽  
Expected Return ◽  
Asset Pricing Model ◽  
Three Factor

This article aims to test the capital asset-pricing model (CAPM) and three-factor model of Fama in Indian Stock Exchange, and it has focused on the recent growth of capital markets in India and the need of practitioners in these markets to determine a stable price for securities, and achieving expected returns has brought into consideration the theories predicting price securities Among different models the CAPM of Sharp. The study uses a sample of daily data and annual average for 54 companies listed on the National Stock Exchange, during the period from 2010 to 2016. The research article’s intention is to find whether the relationship between expected return and risk is linear, if beta is a complete measure of the risk and if a higher risk is compensated by a higher expected return. The results confirm that the intercept is statistically insignificant, upholding theory, for both individual assets and portfolios. The tests do not essentially provide validation against CAPM and Fama; however, other simulations can be built, more close to reality, by improving the model and offering an alternative which also takes into account the specific conditions of the Indian capital market and the global financial crisis consequences.

scholarly journals How Well the Implementation of Carhart Model in Market Overreaction Condition? Evidence in Indonesia Stock Exchange

2018 ◽  
Vol 7 (4.38) ◽  
pp. 928
Author(s):  
Ferikawita M. Sembiring ◽  
. .
Keyword(s):  
Stock Price ◽  
Factor Model ◽  
Stock Exchange ◽  
Market Condition ◽  
Portfolio Returns ◽  
Price Momentum ◽  
Book To Market Ratio ◽  
The Difference ◽  
Fama And French ◽  
Portfolio Return

This study aims to determine an ability of the four-factor model of Carhart in explaining the portfolio returns formed in condition of market overreaction. The four-factor model is basically a model proposed by Fama and French and then developed by Carhart which adds price momentum factor into the model. While market overreaction is a market condition caused by excessive reactions from investors when receiving information. The portfolios used are the winner and loser formed based on the returns of each portfolio to the average of the returns. Both portfolio consist are the stocks of non-financial sector in Indonesia Stock Exchange during the period July 2005 - December 2015. The data used are the Composite Stock Price Index (CSPI), stock market capitalization, book to market ratio of each shares and the difference of returns of the loser over of the winner, as an indicator of price momentum factor that formed in market overreaction condition characterized by occurance the reversal of returns.The results show that the four-factor model can explain the portfolio return well. Implementation of the GARCH (1,1) model to improve the accuracy of the estimation results also shows similar findings.     

scholarly journals FAMA AND FRENCH THREE FACTOR MODEL APPLICATION IN THE PAKISTAN STOCK EXCHANGE (PSE)

2017 ◽  
Vol 13 (1) ◽  
pp. 1-11
Author(s):  
Athar Iqbal ◽  
Keyword(s):  
Factor Model ◽  
Stock Exchange ◽  
Least Square Method ◽  
Least Square ◽  
Annual Data ◽  
Theoretical Understanding ◽  
Independent Variables ◽  
Multiple Variable ◽  
Fama And French ◽  
Three Factor

Purpose: This research has been carried out to test empirically the application of Fama and French three factor model on Pakistan Stock Exchange covering forty listed companies using annual data from 1984 to 2012. Methodology: Author selected excess return as dependent variable and three independent variables market risk, size of the firm and the book to market value of the firms in the portfolio. To test the hypotheses, author used panel least square method. Findings: Result shows that all independent variables are significant and have sign as predicted by theoretical understanding. From our result we interpret that three factors model explain returns in its simplified form on long term horizon better than single factor model like CAPM. Implication: The findings of the research paper suggest that developing economy like Pakistan investor and portfolio manager can better understand by applying multiple variable models and its modified form rather than only relying on CAMP covariance sensitivity model.

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