Good fit of new models of stock return forecasting using conditional dual beta

Subject Areas : Renewable Energy

Hossein Aboutalebi ¹ , mohsen dastgir ² , Qplamreza Soleymani Amiri ³

1 - PhD student, Department of Accounting, Isfahan Branch (Khorasgan), Islamic Azad University, Isfahan, Iran
2 - Professors, Department of Accounting, Isfahan Branch (Khorasgan), Islamic Azad University, Isfahan, Iran (Correspondent)
3 - Associate Professor, Department of Accounting, Al-Zahra University, Tehran, Iran

Received: 2020-12-26 Accepted : 2021-07-04 Published : 2021-11-22

Keywords: conditional dual beta, The power to explain stock returns, fama french 5 factor model, carhart 4 factor model, hxz q factor model,

Abstract :

Various criteria have been introduced to evaluate the expected returns of companies, which are considered by investors and creditors. The purpose of this study is to compare the explanatory power of stock return models of companies listed on the Tehran Stock Exchange using conditional beta. For this purpose, the information of 161 companies listed on the Tehran Stock Exchange from the beginning of 1394 to the end of 1398 was examined and tested. In this study, the explanatory power of 5-factor Fama French, Q-factor HXZ and 4-factor Carhart models was compared using conditional beta. Also, this study is descriptive-correlational in nature and time series regression has been used to estimate the models.The results showed that the explanatory power of the 5-factor model of Fama French using conditional beta is more than the 4-factor models of Carhart and the Q-factor of HXZ. Also, the use of GRS test, whose analysis is mainly based on the width of the origin of regressions, did not show a significant difference between the research models.