جستجوی مقالات مرتبط با کلیدواژه « مدل قیمت گذاری دارایی های سرمایه ای » در نشریات گروه « مدیریت »

Asset pricing models, especially CAPM, are used to determine the expected return on stocks, which is one of the main inputs of valuation using DCF method. Also, setting a rate appropriate to the industry risk, especially for companies that are in the second or subsequent rounds of capital raising, helps to maintain and increase the resources of the facility provider fund. The purpose of this research is to check the possibility of adding a new risk factor based on whether the company is knowledge-based or not to CAPM,. To investigate this, in the first stage (time series regressions) the betas of each portfolio are extracted. In the second stage (cross-sectional regressions) the explainability of the dispersion of the average excess returns of the portfolios using the sensitivity coefficients of each portfolio to the risk factors of the model, is checked. According to the results, being knowledge-based or not is not a new risk factor, but knowledge-based and non-knowledge-based portfolios in the same industries have different CAPM betas. Therefore, it is recommended to use the data of knowledge-based stock companies to find the expected rate of return for a knowledge-based company. Finally, a formula is proposed to relate the expected return found by CAPM to the interest rate of the granted loan.

Theoretically, firms should reduce information risks to provide a transparent environment for different groups in capital market to make decisions. Therefore, identifying potential risk factors is important. This paper investigated the impact of earnings forecast bias and information asymmetry in imperfect competition market on the idiosyncratic risk. It is used the standard deviation of residuals extracted from capital asset pricing model to measure the idiosyncratic risk. Earnings forecast bias is measured based on the absolute value of difference between actual value and forecasted value of earnings per share scaled by the beginning stock price. In addition, information asymmetry is assessed based on the stock price bid-ask spread. Using filtering method, 147 firms listed in Tehran Securities & Exchange during 2013 to 2018 selected as research population. Research hypotheses analyzed through multivariate regression models. Research results showed that more earnings forecast bias lead to increase the idiosyncratic risk. In addition, high level of information asymmetry caused to increase the idiosyncratic risk. Also information asymmetry lead to strengthen the positive relation between earnings forecast bias and idiosyncratic risk. As a whole, firms with high level of earnings forecast bias & information asymmetry as inverse proxies of information quality which have worse information environment have more idiosyncratic risk.

The main objective of this study is investigating the survey of relevance of momentum and liquidity market state on short-term (6 and 12 months), medium-term (24 months) and long-term (60 months). Statistical sample is 270 firms that accepted during years 82-85 in Tehran Stock Exchange and they are still working till end of Year 91. Hypothesis test results showed that liquidity market state as a factor for Separation of markets effects on excess returns in different period of times. So that the Momentum in Sets companies with high liquidity in 6 months formation and 6 & 12 months holding periods were positive and Momentum in Sets companies with low liquidity in 24 & 60 months holding periods were negative. Also, there is no significant difference between the profitability of momentum strategy in Sets companies with high and low liquidity.