Evaluating stock returns using a combination of multi-factor pricing model for capital assets and the function of penalty in Tehran Stock Exchange market and its comparison with five factors Fama and French Model

evaluating the return on investment is one of the main concerns of investors, which is conducted using different models including the single-factor model CAPM, three and five factors Fama and French, and six factors Roy and Shijin, etc. known as multifactorial models. In spite of the widespread use of the models, their main disadvantages include sensitivity to unexpected changes, sudden shocks, severe turbulence of price bubble, and so on. To solve the disadvantages, a multi-factor model is estimated based on the use of the penalty function method, instead of using the average method, which would act based on optimization and avoiding the impact of unusual changes and other factors affecting the capital market. It is possible to select effective factors and model to evaluate stock returns and present a model appropriate to the conditions prevailing in the Iranian capital market. In this article, the classification and estimation of the integrated model of penalty and multi-factor (P & PCA) was performed by forming investment portfolios and identifying the effective factors and refining it based on performance data over a period of time. The study results showed that the use of an extensive simulation algorithm for penalty function by estimation method (P & PCA) improves the efficiency of multifactorial methods in evaluating stock returns. The use of the finite and multi-factor combination algorithm has higher accuracy and explanatory power during the review period in estimating stock returns than the 5-factor Fama and French model.