Objective: The aim of the present study is to analyze and test the power of Conditional Capital Asset Pricing Model (CAPM) with Time Variant Beta against Standard Capital Asset Pricing Model to find the better model to explain expected return of stocks. Methods: Using monthly data, beta value was estimated using standard CAPM and Multivariate GARCH methods for companies included in the statistical sample. Based on these two methods, the expected returns of the next year to test out-of-sample performance were calculated by eliminating 12 months from the top and adding 12 months from the bottom. The same process was repeated for the following years. Then, the accuracy of each of these models was examined using criteria MAE and MSE. Results: Using paired t-test and Diebold-Mariano test, we tested the research hypotheses and the results were presented based on MAE and MSE indices. The results showed that according to both criteria in MAE and MSE, the conditional CAPM models, whether based on full rank BEKK or diagonal BEKK, can have better performance than the standard CAPM model. Conclusion: Regarding the findings and better predictive power of conditional CAPM based on full rank BEKK and/or diagonal BEKK, in terms of MAE and MSE criteria, replacing the standard model with these models can result in higher accuracy.

In this paper, conditional model of downside Capital Asset pricing and conditional model of Capital Asset pricing in periods from 2001 to 2008 in Tehran stock exchange are compared. At first, the coefficients of b and negative b D, market rate of return of variables, risk premium in two models are calculated and next, the expected rate of return is estimated.Then rate of return of independent variable and expected rate of return of dependent variable are separated in two models in accordance to market risk premium positive or negative. By doing so, the initial data of main and secondary hypothesis are defined. Then by using statistical software and average difference regression test and least significant difference research hypothesis are confirmed or rejected. Results of this research show when the market risk premium is positive, the conditional model of D-CAPM is more efficient than the conditional model of CAPM and when the market risk premium is negative, the conditional model of D-CAPM is more efficient than conditional model of CAPM too. Also the conditional model of D-CAPM shows the relation between risk and return better than conditional model of CAPM and portfolio selected by this model is more efficient than conditional model of CAPM.

A new area in Capital Asset pricing is violation of direct investment assumption leading to agency CAPM. The aim of this study is to make a comparative analysis between direct and agency Capital Asset pricing models. So, we compared single-factor, FF three-factor and five-factor CAPM concerning agency and direct investment using the data obtained from Tehran Stock Exchange from 2009 to 2016. To test the Capital Asset pricing models, two methods of zero Alpha of time series models (using GRS statistics) and Beta pricing (based on Fama-Macbeth test) were used. The results of Fama-Macbeth test showed that all the Capital Asset pricing model, three-factor and five-Factor Model of Fama & French would yield better results in agency conditions compared to the direct conditions.

In this paper, we will intend to introduce a new model of Capital Asset pricing model which is called Revised Capital Asset Pricing Model. First we calculate degree of economic leverage. We investigate five economical variables (Inflation rate, financial expenditure, unemployment rate, exchange rate and export) for calculating DEL. Then by combining Capital Assets Pricing Model with leverages (financial, operational and economic leverages), we found a new model which in title Revised CAPM (R-CAPM) and compared the model with traditional CAPM, Downside Capital Asset pricing model and Adjusted Capital Asset pricing model.We compared these models through experimental testing, for the case of 67 firms listed on the stock exchange of Iran for the period 2000-2007. For testing the research hypotheses, liner regression, Friedman and Wilcoxon Test is used. After theoretical conceptual studies, it was confirmed that there is a meaningful difference between measures of the R-CAPM expected return and the other models expected return. The best model which can use for predicting expected return in Iran stock exchange market is R-CAPM.