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

Several studies have been conducted on the impact of unique fundamental factors of companies on their stock returns. The capital asset pricing model (CAPM) developed by Sharpe (1964) and Lintner (1965) and the three-factor model of Fama and French (1993) are the most famous models resulting from these studies. These two models have been widely accepted by academics and used in numerous types of research since its presentation. Significant studies such as those of Fama and French (2012 and 2017) and Hou et al. (2015) show the validity of some global factor models. Nevertheless, Findanza and Morsi (2015) believe that, despite numerous studies on the efficiency of factor models in non-financial companies, few pieces of research have been conducted on the explanatory capability of these models in financial companies. At the same time, a more recent stream of studies in the finance field, including the research of Baker and Wergler (2007) and Sime et al. (2013), show that the performance of traditional factor models may be improved by adding various behavioral factors such as investors' sentiment factor. The paradox of the efficiency of markets depends on the efforts of investors to find opportunities to earn abnormal returns by discovering anomalies. By trying to discover these opportunities, many researchers have focused on the investor sentiment factor and studied its effect on the stock price. The current research seeks to investigate the effectiveness of Fama and French's three-factor model and CAPM in the banking and credit institutions industry, as well as the role of investors' sentiment in this industry to increase the explanatory power of the aforementioned factor models.

The current research is applied in terms of purpose. In terms of method, the research uses regression analysis along with the generalized least squares (GLS) model. The statistical population of the research includes all the listed banks in Tehran Stock Exchange and IRAN FARA BOURSE (IFB). Also, the time domain of the research includes the monthly periods from April 2012 to November 2022. The sampling is based on the methodical elimination of the banks that make up the statistical population. After removing the banks with a shorter acceptance period than the period of the research, 10 banks make up the sample size of the research. The Excel software is used to classify the data and calculate the research variables. Also, the data are analyzed with the Eviews (13 edition) and Stata (17 edition) software programs.Due to cross-sectional dependence, which causes the efficiency of the ordinary least squares method to reduce, the model used the generalized least squares (GLS) method in the Eviews software. To eliminate the problem of heterogeneity of variance, White’s correction (Period Cluster) has been used.

According to the cross-sectional dependence identified in the model, the final estimation of the research model has been done using the generalized least squares (GLS) method and White's correction to solve the heterogeneity of variance. The probability of F statistic related to the significance of all the models is equal to 0.0000. As a result, all the research models are significant. The findings show that adding variables related to the investor sentiment to the asset pricing factor models increases the explanatory power of these models. The excess market return factor was found to be significant in all the models, and the value factor was found to have no significant effect on banks' excess return in any model. The factors related to the investor sentiment are significant in both combined models. At the same time, the addition of the investor's sentiment index to the CAPM and Fama and French three-factor model has increased the adjusted coefficient of determining these models.

Conclusions and policy implications: 

The purpose of this research is to investigate the effectiveness of the CAPM and Fama and French three-factor model in the banking industry and the role of investor sentiment in strengthening the explanatory power of these models. The findings of the research show the significant and positive effect of excess market returns on the risk-adjusted performance of the studied banks. The size factor also has a significant and positive effect on the excess return of the investigated banks, which shows that there is a direct relationship between the excess return of banks and the performance of the size portfolio or the performance superiority of large market companies. Market performance has had the strongest effect on the excess returns of banks. However, the positive effect of the value portfolio performance on the excess return of banks is not statistically significant. This indicates that, although the expectations of investors incited by future developments, regarding the growth of stock returns with a high ratio of book value to market value, increase the return of this type of stock in the medium term, the factors influencing the stock returns are not counted in the long term. Therefore, the factor of market value to book value does not have a significant relationship with the risk-adjusted performance of banks. The findings of the research also show the significant and positive impact of the investor's sentiment index on the excess returns of banks. The sentiment of investors, thus, has a direct relationship with the excess returns, and the increase of the sentiment of investors and the strengthening of their optimism towards the banking industry cause an increase in the excess returns.

The main purpose of this study, is to evaluate the effect of diversion earnings forecast and earnings realized on returns stocks in Tehran Stock Exchange. In fact, this research aims to examine the diversion of earnings resulting from the diversion of corporates managers forecasts earnings, what impact these diversion of earnings have on the returns of stock price. To achieve this, 194 companies listed in the Tehran Stock Exchange selected in the period of 2005-2013.
In this study, two groups of companies experienced the highest returns and lowest returns over the period studied, have been selected. Multi-factor model of Fama and French (1993) was used as the theoretical basis. The results indicate that forecasts of companies have experienced highest returns in comparison with lowest returns are more cautious and accurate than prediction of their future earnings. Changes in earnings realized and Tehran Stock Exchange index returns have positive and considerable relationship with stock returns as well, but these relationships for companies with highest returns are stronger than companies with lowest returns.

In any market, knowing the best method of measuring risk can be very useful for investors and policymakers. In this regard, twenty of best seller corporations of Tehran Stock Exchange (TSE) were studied using monthly historical data (from April 2004 to March 2011). Several variations of the capital asset pricing model (CAPM), such as Lower Partial Moment-Capital Asset Pricing Model (LPM-CAPM), Asymmetric Response Model (ARM), and traditional CAPM were empirically tested. The results show that the traditional Capital Asset Pricing Model is the best model at the present period.
Theoretical Framework: A plethora of empirical tests of the CAPM that implicitly assume the mean-variance based preference of the investors have been performed. However, statistical tractability of mean-variance analysis based on multivariate normality is a more important consideration in the development of the theory than the explicit recognition of investor preferences. Beginning from about the last quarter of the twentieth century, alternative theories based on different perceptions of systematic risk have challenged the dominance of the mean-variance notion of risk-return relationship. The most prominent of these is the asset pricing theory which recognizes risk as the deviation below a target rate of return. Downside risk measures and the associated asset pricing models are motivated by economic and statistical considerations; investor psychology is consistent with asymmetric treatment of the variations in the returns and empirical return distributions appear to be non-normal. Bawa and Lindenberg (1977) developed an asset pricing model, which we refer to as the mean-lower partial moment (MLPM) model, based on downside risk. In the MLPM model, risk is defined as the deviation below the risk-free rate. For normal and student-t-distributions of returns, the MLPM model reduces to the conventional CAPM. In the MLPM model, the downside beta simply replaces the CAPM beta. Bawa and Lindenberg (1977) argue that their model explains the data at least as well as the CAPM does. Harlow and Rao (1989) developed an asset pricing model in the downside framework that is more general in that the risk is defined as the deviation below an arbitrary target rate.
Twenty of best seller corporations of Tehran Stock Exchange (TSE) were studied using monthly historical data (from April 2004 to March 2011). Several variations of the capital asset pricing model (CAPM), such as Lower Partial Moment-Capital Asset Pricing Model (LPM-CAPM), Asymmetric Response Model (ARM) and traditional CAPM, were empirically tested.
The results show that, traditional Capital Asset Pricing Model, is better than Lower Partial Moment-Capital Asset Pricing Model (LPM-CAPM) and Asymmetric Response Model (ARM) in our selected period (from April 2004 to March 2011).
Conclusions and Suggestions: The results show that despite some empirical tests in recent years, it seems that by using long samples, traditional CAPM model could be a reliable test. Finally, authors suggest that to achieve more reliable results in CAPM models, researchers have to consider environmental conditions to use the best model.

This study provides a dynamic estimation of Capital Asset Pricing Model in optimal dynamic household decisions during its life cycle based on Dynamic Conditional Correlation (DCC) and State-Space Models. In this regard, for daily time series data of Vehicle and parts manufacturing stock price for the period of 2006 to the end of sixth month of 2011, dynamic estimation of Beta-index time series which obtained from DCC and State-Space models has been compared with static linear regression model. The results show that the DCC model has minimum error in out-of-sample forecasting of stock returns based on Root Mean Square Error (RMSE) criterion. However, state-space model has minimum error for in-sample forecasting based on RMSE criterion.

Risk and benefit are key concepts of capital market. This issue has been studied sufficiently in various models of the conventional literature, with all its advantages and disadvantages. Islamic capital market often faces with new instrument. Thus, risk management in its discussions suffers from noticeable poverty. Sukuk Manfeah (benefit securities) is one of the latest instruments for Islamic capital market. This paper assumes the readers are familiar with the nature of sukuk manfeah (benefit securities), so it explains the risks in this market and the sides who take that. Then this paper tries to analysis the risk and the benefit of the sukuk manfeah (benefit securities) according to the capital asset pricing model (CAPM). Undoubtedly, the main role of this paper in knowkedge production, is to use the capital asset pricing model (CAPM) in Islamic capital market, which so far is unprecedented.

This article reviews accurately of Capital Asset Pricing model and Reward Beta model in prediction of expected return of Tehran Stock Exchange. In this study, to test research hypotheses, the stock return data of sample companies and market returns for the sample period of Esfand 1386 to Farvardin 1375 are used and these sample companies in 25 portfolios have been classified based on size and book value to market value ratio. The results showed that the reward beta model in a short-term period (one year) and long-term period (three years) predict future stock returns better than CAPM. Moreover, the reward beta model factors have more positive correlation and are more significant than capital asset pricing model factor of stock returns.

Markowitz's model which determines the weight of each stock in the portfolio is based on the optimal choice of stocks in order to maximize the expected returns. However, this theory through paying special attention to the concept of total risk reaches to an efficient frontier which undoubtedly the portion of unsystematic risk that the market doesn’t reward will not stand in the minimum level. Besides, Sharpe’s theory presents a model using some simplifying assumptions which attains a new efficient frontier in which although the concept of systematic risk governs it, its fundamental defect will absolutely be applying market portfolio in the case of investing. This article aims to combine the theories of Markowitz and Sharpe to introduce a new model. This new model is much better and more efficient in comparison to Markowitz’s efficient frontier. Moreover, it reforms the exiting defect in Sharpe’s model The superiority of proposed model over Markowitz and Sharpe's traditional models from the view point of theory is definitely proven through paying attention to unsystematic risk, eliminating some assumptions of the traditional models and finally through finding the optimal portfolio of stocks for large cement corporations in Tehran stock exchange market.