scholarly journals FAMA FRENCH 5 FACTOR MODEL VERSUS ALTERNATIVE FAMA FRENCH 5 FACTOR MODEL: EVIDENCE FROM SELECTED ISLAMIC COUNTRIES

Bilimname ◽  
2021 ◽  
Author(s):  
Nevin ÖZER ◽  
Mehmet Akif ÖNCÜ ◽  
Ali ÖZER ◽  
İstemi ÇÖMLEKÇİ
Keyword(s):  
Factor Model ◽  
Islamic Countries ◽  
Model Evidence ◽  
Model Versus

Four-moment CAPM Model: Evidence from the Indian Stock Market

2019 ◽  
Vol 18 (1_suppl) ◽  
pp. S137-S166
Author(s):  
Dheeraj Misra ◽  
Sushma Vishnani ◽  
Ankit Mehrotra
Keyword(s):  
Factor Model ◽  
Jel Classification ◽  
Capital Asset Pricing ◽  
Capital Asset ◽  
Asset Pricing Model ◽  
Model Evidence ◽  
Fama And French ◽  
Capm Model ◽  
Indian Stock Market ◽  
The Impact

This study aims at analysing the impact of co-skewness and co-kurtosis on the returns of the Indian stocks by incorporating co-skewness and co-kurtosis in the traditional capital asset pricing model (CAPM) of Sharpe, in a three-factor model of Fama and French and in a four-factor model of Carhart. The results of the study show that co-skewness and co-kurtosis have significant impact on the returns of the Indian stock. However, the impact of co-skewness is higher than co-kurtosis. JEL Classification: G11, G12

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.

Index Tracking with Factor Model: Evidence from Shanghai 50

2012 ◽  
Vol 7 (19) ◽  
pp. 347-356
Author(s):  
LIU Jianhe ◽  
Wu Xin ◽  
CHEN Keyi
Keyword(s):  
Factor Model ◽  
Index Tracking ◽  
Model Evidence

scholarly journals New JLS-Factor Model versus the Standard JLS Model: A Case Study on Chinese Stock Bubbles

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Zongyi Hu ◽  
Chao Li
Keyword(s):  
Factor Model ◽  
Statistical Tests ◽  
Explanatory Power ◽  
Critical Time ◽  
Flexible Tool ◽  
Regime Changes ◽  
Chinese Characteristics ◽  
Model Versus ◽  
The Interest Rate ◽  
Equity Indices

In this paper, we extend the Johansen-Ledoit-Sornette (JLS) model by introducing fundamental economic factors in China (including the interest rate and deposit reserve rate) and the historical volatilities of targeted and US equity indices into the original model, which is a flexible tool to detect bubbles and predict regime changes in financial markets. We then derive a general method to incorporate these selected factors in addition to the log-periodic power law signature of herding and compare the prediction accuracy of the critical time between the original and the new JLS models (termed the JLS-factor model) by applying these two models to fit two well-known Chinese stock indices in three bubble periods. The results show that the JLS-factor model with Chinese characteristics successfully depicts the evolutions of bubbles and “antibubbles” and constructs efficient end-of-bubble signals for all bubbles in Chinese stock markets. In addition, the results of standard statistical tests demonstrate the excellent explanatory power of these additive factors and confirm that the new JLS model provides useful improvements over the standard JLS model.

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