The comparison of explanatory power of Hou et al. four-factor model and Fama and French’s five-factor model to forecast expected return

The purpose of this paper is to examine the explanatory power of Hou et al. four-factor model and Fama and French’s five-factor model to predict the expected stock return in listed companies in Tehran Stock Exchange. For this purpose, a sample consisting of 147 firms during the period of 2006 to 2015 has been selected. To analyze the data, descriptive and inferential statistics were incorporated and to test the research hypotheses, multiple regression approach with the pooled data approach through the software’s Eviews and Stata has been used. The findings indicate that the adjusted coefficient of determination, which shows the explanatory power of their two models together, is equal. The mean squared error and mean absolute error of both models also are not significantly different. Thus, the results demonstrated that in the course of the study, the explanatory power of the French’s five-factor model with Hou et al. four-factor model, in anticipation of expected returns is not significantly different from each other.  Therefore, investors can use both models to predict expected returns to form their investment portfolio.
Journal fo Iranian Accounting Review, Volume:5 Issue: 19, 2019
113 to 133  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 1,390,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
In order to view content subscription is required

Personal subscription
Subscribe for 70 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!