Comparison of the Seven-Factor Model with the Capital Assets Pricing Model and the Fama and French Three-Factor Model to Predict the Expected Returns of Stock in the Tehran Stock Exchange

Understanding why and how asset prices rise is a major concern for industry, policymakers and investors. This has attracted the attention of researchers to the issue of asset pricing, especially high-risk assets such as stocks. The single-factor capital asset pricing model (CAPM) and the Fama and French (1993) three-factor model are some of the well-known models that seek to explain investors' expectations for high-risk asset returns, and various multifactorial extensions of these models have been proposed. One of the latest versions of these models is the seven-factor model, which is expected to have a higher explanatory power than the CAPM model and the Fama and French three-factor model. The purpose of this study is to evaluate the seven-factor model in Tehran Stock Exchange and compare it with CAPM model and Fama and French model in order to predict the expected returns of companies operating in the financial sector of Tehran Stock Exchange during the period 2016: 1 to 2019: 12. In this study, the estimation method is the Auto Regressive Distributed Lag (ARDL). The results of the study show that the seven-factor model gives a better estimate of the expected return than the CAPM and Fama and French models. Also in the seven-factor model, the variables of book value to market value ratio, momentum, liquidity turnover ratio and commodity index have a negative and significant effect on expected returns. But market factor, government bond index and company size factors do not have a significant effect on expected returns.