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Multifactor Capital Asset Pricing Model in the Jordanian Stock Market

A valid and accurate capital asset pricing model (CAPM) may help investors and mutual funds managers in determining expected returns and thus, may increase profits which can be reflected on the 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 the validity of 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. The results of this study may contribute to positive social change by changing the way the individual investors and mutual funds managers select their investing portfolios which can lead to better resource distribution in the economy.

Identiferoai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-6465
Date01 January 2018
CreatorsElshqirat, Mohammad Kamel
PublisherScholarWorks
Source SetsWalden University
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceWalden Dissertations and Doctoral Studies

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