Mathematical Nonlinear Modeling of Information Environment Risk Factor Pricing with Generalized Method of Moments (GMM) Approach in Tehran Stock Exchange

Transparency of the information environment and proper pricing system can lead to the allocation efficiency of financial markets in the long run. Information risk is one of the factors through which the impact of the company's information environment on the discovery of companies' stock prices can be examined. The purpose of this study is to evaluate the information risk factor in increasing the power to explain the excess return on companies' stocks. Using the monthly stock' excess return data of 201 companies listed on the Tehran Stock Exchange during the period 2012 to 2021, combined information risk factor (information asymmetry, stock price synchronicity, stock price delay reaction and conservatism) was added to the five-factor model of Fama and French (2013) and by the Generalized Method of Moments (GMM) method on the monthly return of excess stock regressed. The results showed that by adding the combined information risk factor nonlinearly to the five-factor model of Fama and French (2013), its explanatory power increases by 4.5% and can explain approximately 18.5% of the monthly excess return on risk of the company's stock.