Testing the CAPM Theory Based on a New Model for Fama-French 25 Portfolio  Returns

Li, Liuling; Gan, Quan; Zhuo, Ziyue; Mizrach, Bruce

doi:10.4236/tel.2014.48085

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…The results of hypotheses testing revealed the single-factor capital asset pricing model is invalid in the Jordanian stock market. This conclusion is in line with the results of studies of many researchers who reached the same conclusion about this market (Alqisie & Alqurran, 2016;Alrgaibat, 2015;Blitz et al, 2013) and about many other countries (Dajčman et al, 2013;Dzaja, & Aljinovic, 2013;Li, Gan, Zhuo, & Mizrach, 2014;Nyangara et al, 2016;Obrimah et al, 2015;Saji, 2014;Wu et al, 2017). The hypothesized relationship between the expected rate of return and variables of size, financial leverage, and market rate of return was found to be insignificant ; the expected rate of return for a stock is directly related to the operating leverage of the stock.…”

Section: Discussionsupporting

confidence: 86%

Testing a Multi-factor Capital Asset Pricing Model in the Jordanian Stock Market

Elshqirat¹,

Sharifzadeh²

2018

IBR

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A valid and accurate capital asset pricing model (CAPM) may help investors and mutual funds managers in determining expected returns which may lead to increase their profits and community resources. The problem is that the traditional CAPM does not accurately predict the expected rate of return. A more accurate model is needed to help investors in determining the intrinsic price of the financial asset they want to sell or buy. The purpose of this study was to examine the validity of the single-factor CAPM and then develop and test a multifactor CAPM in the Jordanian stock market. The study was informed by the modern portfolio theory and specifically by the single-factor CAPM developed by Sharpe, Lintner, and Mossin. The research questions for the study examined the factors that may explain the variation in the expected rate of return on stocks in the Jordanian stock market and the relationship between the expected rate of return and factors of market return, company size, financial leverage, and operating leverage. A causal-comparative quantitative research design was employed to achieve the purpose of the study by testing the listed companies on the Amman stock exchange (ASE) for the period from 2000 to 2015. Data were collected from the ASE database and analyzed using the multiple regression model and t test. The results revealed that market return, company size, and financial leverage are not predictors of the expected rate of return while operating leverage is a predictor.

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Section: Discussionsupporting

confidence: 86%

Testing a Multi-factor Capital Asset Pricing Model in the Jordanian Stock Market

Elshqirat¹,

Sharifzadeh²

2018

IBR

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“…These two papers are part of a wide range of research on the empirical relevance of the CAPM theory, considering non-standard stochastic assumptions that explicitly allow for heavy tails and/or asymmetry in the underlying distributions. Other works by Affleck-Graves [27] , MacKinlay and Richardson [28] , Zhou [29] , Harvey and Siddique [30] , Li [31] , Theodosiou and Theodossiou [32] , and more recently, Bao et al [33] , are examples of extensive research on the application of flexible non-Gaussian families of distributions in the problem of risk assessment using the CAPM.…”

Section: Kaplan and Petersonmentioning

confidence: 99%

“…Li et al [31] , Bao et al [33] , and others modelled the distribution of the error term in Equation (8) using asymmetric power distributions or asymmetric exponential power distributions. Theodossiou and Theodossiou [32] analyzed the sensitivity of β parameter estimates in light of outliers in the series of stock market returns, revealing substantial bias in OLS estimates in the case of non-normal empirical distributions of financial returns. While Theodossiou and Theodossiou's [32] feasible estimation procedure does not explicitly define the distribution of the error term in CAPM regressions, it is equivalent to the OLS procedure (under the Gaussian model) and importantly, yields significantly different β estimates in the case of heavy-tailed and asymmetric data.…”

Section: Empirical Insights Into Capm Regressionmentioning

confidence: 99%

“…Theodossiou and Theodossiou [32] analyzed the sensitivity of β parameter estimates in light of outliers in the series of stock market returns, revealing substantial bias in OLS estimates in the case of non-normal empirical distributions of financial returns. While Theodossiou and Theodossiou's [32] feasible estimation procedure does not explicitly define the distribution of the error term in CAPM regressions, it is equivalent to the OLS procedure (under the Gaussian model) and importantly, yields significantly different β estimates in the case of heavy-tailed and asymmetric data. The pursuit of reliable inference in linear regression models with heavy-tailed errors has a longstanding tradition in empirical sciences and has been of particular interest in financial economics for decades.…”

Section: Empirical Insights Into Capm Regressionmentioning

confidence: 99%

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Estimating parameters of the CAPM under generalised asymmetric student-t distribution—The case of the Warsaw Stock Exchange sectoral indices

Pipień

2024

Financ. Stat. J.

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This paper analyses selected sub-indices listed on the Warsaw Stock Exchange (WSE) covering seven sectors: construction, IT, media, real estate, fuel, food, and telecommunications, from 3 January 2006 to 29 May 2020. We use daily, weekly, monthly, and quarterly data, resulting in 3600 daily, 751 weekly, 172 monthly, and 56 quarterly observations. The WIG index quotations were used to approximate the market portfolio and the Poland 10Y government bond yields for the risk-free rate. We have estimated the parameter β in CAPM regression using three different stochastic assumptions for the error term. The basic stochastic framework of the model utilises the generalised asymmetric student-t distribution (GAST). We have also estimated the parameter β based on the symmetric version of the GAST distribution and on the Gaussian one. These models can be treated as a special case of the basic framework. The estimates of the β parameter are influenced by the assumptions made about the error term. The data indicates that except for WIG-Paliwa, the Gaussian error term leads to larger β estimates than other non-Gaussian specifications. The inference about the shape parameters is not very certain, and the data does not strongly support the two-piece mechanism that enforces the asymmetry of the error term distribution. Furthermore, the estimates of the β parameter depend strongly on the frequency of the analysed series.

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Measuring Systemic Risk in the Chinese Financial System Based on Asymmetric Exponential Power Distribution

Luo

et al. 2018

Recent Developments in Data Science and Business Analytics

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Testing the CAPM Theory Based on a New Model for Fama-French 25 Portfolio Returns

Cited by 4 publications

References 9 publications

Testing a Multi-factor Capital Asset Pricing Model in the Jordanian Stock Market

Testing a Multi-factor Capital Asset Pricing Model in the Jordanian Stock Market

Estimating parameters of the CAPM under generalised asymmetric student-t distribution—The case of the Warsaw Stock Exchange sectoral indices

Measuring Systemic Risk in the Chinese Financial System Based on Asymmetric Exponential Power Distribution

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