مجله راهبرد مدیریت مالی
سال دهم شماره 1 (پیاپی 36، بهار 1401)

The present study compares the performance of optimal portfolio based on Value at Risk and Upside Risk with conventional models (the optimal portfolio based on Markowitz model). The purpose of this study is to select the optimal portfolio based on the proposed model in three scenarios: 1- potential and risk averse investor 2- neutral potential and risk averse 3- avertive potential and risk aversion; perform them with optimal portfolio Compare to the Markowitz model. For this aim, we calculated the monthly returns of 50 most active Tehran Stock Exchange companies over a seven-year period of 91-97. Used four years of data(91-94) to build the model and determine the efficient frontier. Use the criterion of value at risk as undesirable risk measure and covariance upper partial moment- CUPM as desirable potential measure. And this procedure was repeated for 36 months of model test data. To calculation of model parameters using Eviews11 software.To solve the Markowitz quadratic programming from MATLAB software and to solve the proposed nonlinear programming problem from GAMS software and to test the hypotheses and compare the results of the two models with longitudinal studies method with repeated measurements to SPSS software was used.The results show that  Updating the model, efficient frontier, as well as applying the criterion of value at risk and paying attention to investor orientations in terms of tendency to optimal potentials and risk aversion lead to optimized portfolio performance.

Investors' overreaction is one of the most important behavioral biases which might affect stocks returns so they can be priced. Furthermore, investors' overreaction increases trading volume, therefore it can be captured by using a measure based on trading volume and return sign. In this paper, we use a measure of signed volume (Continuous Overreaction) for calculating investors' overreaction and its relation with stock return in Tehran Stock Exchange using Fama-Mcbeth's (1973) regression. Also, we survey the return statistical significance of a trading strategy based on continuous overreaction measures. For doing so, we study companies listed on TSE between 2009 to 2018. This period contains 102 months and, on average, 241 companies were studied. Our results show that investors' overreaction affects stock return in Tehran Stock Exchange. Also, the return of the trading strategy based on investors' overreaction is statistically significant for 12 months portfolio formation period and 6, 9, and 12 months holding periods

Following the consequences of the recent financial crisis, measuring, analyzing, and understanding the systemic risk of the financial system has become very important in new economic studies. Systemic stress is another form of systemic risk that has been occurred. The purpose of this paper is to quantify systemic stress and financial stress by identifying the main actor as the main source of financial stress. In this study, the systemic stress index and dynamic financial stress of Iran's economy are estimated monthly from January 2008 to January 2017 with the EWMA approach and dynamic factor analysis method. The systemic stress index is estimated to be non-recursive and real-time (the usual systemic stress index). One of the important achievements of this research is the one-lag and two-lag adaptation between the highest amounts of financial stress and the crises of Iran's economy. So that the fluctuations of the financial stress index of 2017 and 2012 show the financial crises in these years perfectly. Another result of the study shows that the stock market fluctuations and the banking and foreign exchange sector are the most important stressor in the financial stress index.

purpose of this study is to investigate the relationship between asset growth and the future stock price crash risk concerning the moderating effects of agency problems and accounting conservatism. Method To test The the research hypotheses, 102 companies were examined among the companies listed on the Tehran Stock Exchange between 2010 to 2019. To test the research hypotheses, a multivariate regression model and panel data have been used. The results indicate that the growth of assets has a positive and significant effect on the future stock price crash risk. The findings also showed that the agency problem increases the impact of asset growth on the future stock price crash risk. In addition, accounting conservatism has no significant effect on the relationship between asset growth and the future stock price crash risk.

With the recent extension of markets and increasing financial interactions, institutions are affected by their systemic risk and the systemic risk of other institutions and markets. Also, by changing the structure and characteristics of institutions in their complex network, the Systemic risk contribution of these institutions will be different. It is important for lawmakers, investors, and others to control, manage and reduce systemic relationship between local topology structure and systemic risk contribution by panel data regression analysis, it found that there is a significant relationship between the change of Conditional Value-at-Risk (∆CoVaR) and the local topology structure such as node closeness centrality, node strength, and node degree. So, there is a significant relationship between systemic risk contribution and the local topology structure. The results show that there is a positive relationship between systemic risk contribution and node closeness centrality, so financial institutions with larger node closeness centrality have higher systemic risk contributions. Also, there is a negative relationship between systemic risk contribution and node strength and node degree. Therefore, financial institutions with greater node strength and larger node degrees have lower systemic risk contributions. But with the data analyzed in this study, no significant relationship is found between node betweenness centrality and systemic risk contributions.risk. The purpose of this paper is to analyze the structure of the financial institutions' local topology on their systemic risk contribution. The purpose of this study is to investigate the contribution of systemic risk, using Tehran stock exchange data (on twenty stock companies from March 2014 to March 2019) with the change of Conditional Value-at-Risk (∆CoVaR). Initially, a dynamic conditional correlation multivariate GARCH model (DCC-MVGARCH) is used to calculate the conditional correlation matrix and the minimum spanning tree (MST) is constructed. Then, the topology structure of the financial institutions' network and relationships between these characteristics and systemic risk is estimated. By quantifying the

The purpose of this study is to investigate the effect of political connections on financial constraints and financial distress risk, as well as the effect of political connections on the relationship between financial constraint and financial distress risk with the abnormal return of accepted firms in Tehran Stock Exchange. The statistical sample includes 162 accepted firms in Tehran Stock Exchange between 1391-1397. In this study, a multivariate linear regression model is used. The results show that political connections have a negative and significant effect on financial constraints and financial distress risk. Also, it amplifies the intensity of the negative relationship between the financial constraint and the abnormal return. The firms that are suffering from a financial constraint, and at the same time, benefit from political connections have less abnormal returns than non-politically connected firms which are suffering from a financial constraint. Furthermore, it changes the direction of the relationship between financial distress risk and abnormal return from negative to positive. In other words, firms that are suffering from financial distress with political connections have more abnormal returns than non-politically connected firms which are suffering from financial distress.

The purpose of this study is to identify and prioritize the factors affecting the presence of emerging actors in the Iranian financial markets. In the financial crisis started in 1396, the general public, along with the three other actors (government, central bank, and dealers), as the fourth actor, entered the financial markets and had the most significant impact on causing inflammation and environmental expansion of the market. In this paper, using the opinions of 85 economic experts and implementing exploratory factor analysis, the effective parameters in the presence of emerging actors in the four criteria of "rules and regulations", "psychological factors", "market performance and response", and “financial awareness" category has been classified. In this study, using pairwise comparisons of 15 economic experts in monetary and financial policy institutions and implementing DANP and VIKOR processes, it was found that the criteria of "psychological factors", "market performance and reaction", "rules and regulations", and "financial awareness" are influential in the presence of emerging financial market players. In other words, the psychological factors resulting from unrealistic information for the growth of false demand and market contraction and expansion shocks have been more influential than any other parameter in the unbridled entry of fourth actors into the financial markets.

Since the testosterone level has a significant impact on the corporate finance managers' decisions, the higher level of testosterone in the CEO, the managers will benefit from the more aggressive policies. Therefore, the testosterone level in managers may play a key role in decisions related to corporate investments. According to this argument, the purpose of the study is to investigate the effect of the head-to-face ratio of the CEO as one of the testing criteria of testosterone levels on the financial decisions of the corporates' managers. For this purpose, a sample consisting of 63 corporates listed in the Tehran Stock Exchange was selected in 2013-2017 and was tested using a logistic regression model. The results of the first hypothesis showed that a high level of testosterone had led to an increase in the investment decisions less than the managers' capacity in line with appropriate and efficient investments in the corporate. Also, the results of the second hypothesis suggested that the high level of testosterone in the CEO had led to an increase in financial leverage over the investment opportunities.

When investigating projects and companies for investment purposes, most analysts use a discount rate that is derived from CAPM model. The calculated beta of this model is usually a representor of risks and opportunities of the relative industry but has almost no attention to risks and opportunities of the project or firm that is being investigated. This ignorance to risk measurement could make a poor discount rate which would lead to incorrect evaluation and reduction of Equity value. In most cases, correcting for risks and opportunities of beta, would make a big difference in the results. The goal of this paper is to provide a more accurate measurement of systematic risk of investment projects by considering it's relative risks and opportunities.In this research the adjusted beta from the model of Bernardo and others was calculated using 10 years of monthly return of all companies listed in Tehran Stock Exchange and Iran Farabourse. Then by mixing Grey Theory with the model, we tried improving the mentioned model. The grey beta of growth opportunities and grey beta of existing assets was calculated for all firms. Finally, to test the variables, some robustness checks was performed using Durbin test and Wu-Housman test. The results shows better performance of Grey BCG model. The calculated beta could be used to improve risk measurement of industries and firms. It also could help discount rate calculation and valuation of companies, projects and startups.

This paper investigates the behavior of the differences between bid and ask prices and spread and the factors affecting them. The bid and ask price differences are one of the criteria for assessing the liquidity risk of stocks and the selection of stocks in the investment portfolio. Therefore, this study seeks to provide a solution to reduce the bid-ask price differences in an investment portfolio, by estimating the effect of companies' financial variables on the amount of the bid and ask price differences in the form of the linear Panel Data model. Accordingly, among the companies listed on the Tehran Stock Exchange, 129 companies have been selected for the period 1386-1396. The findings show that the Average Daily Stock Turnover and Liquidity Rating of the company, respectively, had the most significant effect on the bid and ask price differences of stocks. Also, based on our results, the first hypothesis, that stock price volatility has a positive and significant effect on the dependent variable BAS, is confirmed. On the other hand, coefficients of stock percentage in stock block holders, total company shares, and financial leverage in the linear model are not statistically significant, and asset liquidity rating does not have the greatest impact on the BAS dependent variable. So, the second hypothesis is not accepted. Also, the effect of the variable of company size (volume of company's assets) was not statistically significant and was considered equal to zero. Therefore, the third hypothesis was accepted.