scholarly journals Comparing Asset Pricing Factor Models under Multivariate t-Distribution: Evidence from China

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xi Sun ◽  
Yihao Chen ◽  
Yulin Chen ◽  
Zhusheng Lou ◽  
Lingfeng Tao ◽  
...  
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Stock Return ◽  
Model Comparison ◽  
Factor Model ◽  
Factor Models ◽  
Comparison Results ◽  
Distributional Assumptions ◽  
Stock Return Anomalies ◽  
T Distribution

Factor models provide a cornerstone for understanding financial asset pricing; however, research on China’s stock market risk premia is still limited. Motivated by this, this paper proposes a four-factor model for China’s stock market that includes a market factor, a size factor, a value factor, and a liquidity factor. We compare our four-factor model with a set of prominent factor models based on newly developed likelihood-ratio tests and Bayesian methods. Along with the comparison, we also find supporting evidence for the alternative t-distribution assumption for empirical asset pricing studies. Our results show the following: (1) distributional tests suggest that the returns of factors and stock return anomalies are fat-tailed and therefore are better captured by t-distributions than by normality; (2) under t-distribution assumptions, our four-factor model outperforms a set of prominent factor models in terms of explaining the factors in each other, pricing a comprehensive list of stock return anomalies, and Bayesian marginal likelihoods; (3) model comparison results vary across normality and t-distribution assumptions, which suggests that distributional assumptions matter for asset pricing studies. This paper contributes to the literature by proposing an effective asset pricing factor model and providing factor model comparison tests under non-normal distributional assumptions in the context of China.

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>

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 Asset growth and stock return: evidence in the Brazilian market

2018 ◽  
Vol 29 (78) ◽  
pp. 418-434
Author(s):  
Márcio André Veras Machado ◽  
Robert William Faff
Keyword(s):  
Risk Factor ◽  
Asset Pricing ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Return ◽  
Operating Performance ◽  
Growth Effect ◽  
Capital Investments ◽  
Limits To Arbitrage ◽  
Asset Growth

Abstract Empirical evidence suggests that firms which have experienced fast growth, through increased external funding and by making capital investments and acquisitions, tend to show bad operating performance and lower stock returns, whereas firms that have experienced contraction, through divestiture, share repurchase and debt retirement, tend to show good operating performance and higher stock returns. So, this study aimed to analyze the relationship between asset growth and stock return in the Brazilian stock market, and it tested the hypothesis that asset growth is negatively related to future stock return. To do this, the methodology was divided into 3 steps: verifying 1) if asset growth anomaly exists; 2) if this relation may be explained by the investment friction hypothesis and/or by the limits-to-arbitrage hypothesis; and 3) if asset growth is a risk factor or mispricing. In addition, the analysis was carried out both at a portfolio level and an individual assets level. The sample included all the non-financial firms listed at B3 from June 1997 to June 2014. As for the main results, this study found that the asset growth effect exists, both at the portfolio level and the individual assets level, although it is sensitive to the proxy. About the effect’s materiality, this study concluded that the asset growth effect is not economically relevant, since it is not observed in big firms, regardless of the proxy used, a fact that makes it difficult to explore this effect. Another finding is that the asset growth effect may not be related to the limits-to-arbitrage hypothesis and to the financial constraint hypothesis; also, this effect may be considered a risk factor, suggesting that the investment effect documented in the Brazilian stock market may be explained by the rational asset pricing perspective. Therefore, capital market professionals should take into account the asset growth factor in asset pricing models for better investment risk assessment.

Grey system based novel forecasting and portfolio mechanism on CSE

2016 ◽  
Vol 6 (2) ◽  
pp. 126-142 ◽  
Author(s):  
R.M. Kapila Tharanga Rathnayaka ◽  
D.M.K.N Seneviratna ◽  
Wei Jianguo
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Model Comparison ◽  
Model Building ◽  
Price Indices ◽  
Grey System ◽  
Content Type ◽  
Ex Post ◽  
Comparison Results ◽  
The Future

Purpose – Because of the high volatility with unstable data patterns in the real world, the ability of forecasting price indices is notoriously embarrassing and represents a major challenge with traditional time series mechanisms; especially, most of the traditional approaches are weak to forecast future predictions in the high volatile and unbalanced frameworks under the global and local financial depressions. The purpose of this paper is to propose a new statistical approach for portfolio selection and stock market forecasting to assist investors as well as stock brokers to predict the future behaviors. Design/methodology/approach – This study mainly takes an attempt to understand the trends, behavioral patterns and predict the future estimations under the new proposed frame for the Colombo Stock Exchange (CSE), Sri Lanka. The methodology of this study is carried out under the two main phases. In the first phase, constructed a new portfolio mechanism based on k-means clustering. In the second stage, proposed a nonlinear forecasting methodology based on grey mechanism for forecasting stock market indices under the high-volatile fluctuations. The autoregressive integrated moving average (ARIMA) predictions are used as comparison mode. Findings – Initially, the k-mean clustering was applied to pick out the profitable sectors running under the CSE and results indicated that BFI is more significant than other 20 sectors. Second, the MAE, MAPE and MAD model comparison results clearly suggested that, the newly proposed nonlinear grey Bernoulli model (NGBM) is more appropriate than traditional ARIMA methods to forecast stock price indices under the non-stationary market conditions. Practical implications – Because of the flexible nonlinear modeling capability, proposed novel concepts are more suitable for applying in various areas in the field of financial, economic, military, geological and agricultural systems for pattern recognition, classification, time series forecasting, etc. Originality/value – For the large sample of data forecasting under the normality assumptions, the traditional time series methodologies are more suitable than grey methodologies. However, the NGBM is better both in model building and ex post testing stagers under the s-distributed data patterns with limited data forecastings.

Bayesian Selection of Asset Pricing Factors Using Individual Stocks*

2020 ◽  
Author(s):  
Soosung Hwang ◽  
Alexandre Rubesam
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
Factor Models ◽  
Bayesian Variable Selection ◽  
Large Set ◽  
Definitive Answer ◽  
Linear Factor ◽  
Empirical Performance ◽  
Pricing Factors ◽  
Fama And French

Abstract We apply Bayesian variable selection to investigate linear factor asset pricing models for a large set of candidate factors identified in the literature. We extract model and factor posterior probabilities from thousands of individual stocks via Markov Chain Monte Carlo estimation together with the exact distribution of pricing statistics. Our results show that only a small number of factors are relevant and, except for the market and size factors, these are not the factors in widely used linear factor models such as Fama and French (2015, Journal of Financial Economics 116, 1–22) or Hou et al. (2015, The Review of Financial Studies 28, 650–705). Moreover, many different linear factor models achieve similar empirical performance, suggesting that the search for a single linear factor model is unlikely to yield a definitive answer.

scholarly journals Do select macroeconomic factors drive momentum returns?

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
A. Balakrishnan ◽  
Nirakar Barik
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Factor Model ◽  
Capital Asset Pricing ◽  
Short Term ◽  
Macroeconomic Factors ◽  
Macroeconomic Variables ◽  
Asset Pricing Models ◽  
Indian Stock Market

AbstractIn this paper, we examine the presence of short-term and long-term momentum returns in Indian stock market. The study also tries to shed light on the power of asset pricing models and select macroeconomic variables in explaining momentum returns. The results confirm the presence of short-term and long-term momentum returns in Indian stock market. It is also found that Carhart four-factor model’s performance is relatively superior to other factor models such as one factor capital asset pricing model and Fama–French three-factor model in terms of capturing momentum returns. Finally, macroeconomic variables which are considered for analysis do not have any power to explain momentum returns.

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 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).

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