محمدرضا ستایش

Investment capital funds, like all other sectors of the capital market, are affected by economic variables, and its quality and type of effectiveness can be found in how to guide this financial institution in the face of search. Objectives and

In this study, using the integrated model of Lit et al. (2003), we will evaluate the performance of Iranian investment funds in the years 2016-2019 using soft panel transfer regression (PSTR) by MATLAB software and check whether the investment funds have been able to reduce the nonlinear effects. Recognize macro variables on fund returns and change the composition of your portfolio based on that?

The results indicate the existence of a non-linear relationship between macroeconomic variables and the return of investment funds by considering a transfer function and a threshold parameter and a two-regime model.

Considering the asymmetric relationship between macroeconomic variables and the returns of funds, the ability to recognize this issue, identifying the appropriate stocks in each regime and the positioning of investment funds can, in addition to creating competition between funds in having superior performance, lead to their ranking by institutions. supervisory help.

In this study, the behavioral biases and decisions of real and legal investors under conditions of uncertainty in the Tehran Stock Exchange were investigated. For this purpose, two market conditions including uncertainty due to uptrend without resistance and uncertainty due to downtrend without support are studied as conditions of uncertainty in investment decisions and the effect of 15 behavioral biases of investors in two groups of investors. Real and legal were tested on financial decisions based on buying, selling or not taking action for the transaction. The statistical population of the study included real and legal investors in the Tehran Stock Exchange, of which 385 real investors and 100 legal investors were selected by available sampling method and research questionnaires were provided to them. In order to analyze the data obtained from the distribution of the questionnaire, the fitting of polynomial logistic regression models was used and the results showed that the behavioral biases of real and legal investors had different effects on their investment decisions and also the type of influence of each. Behavioral biases on a variety of investment decisions have varied due to market uncertainty. Finally, models were proposed to predict the investment decisions of both groups of real and legal investors using their behavioral biases.

Today, investing in gold markets is an important part of any country's economy, so estimating the price of gold is one of the most important topics of study for economists and financial analysts who have developed different approaches and perspectives. Naturally, methods can be durable and suitable for use that have the least investment error and risk. In developing countries such as Iran, due to inflation and uncertainty about the future, the demand for gold to cover the risk of inflation is high.The formation of the Bahar Azadi coin futures contract market in the Commodity Exchange in recent years has also helped to create an organized market to cover risk and also to use arbitrage opportunities in the gold market. The trading statistics of Bahar Azadi coin futures contract have grown significantly since the entry of its first symbol in the trading table of Iran Commodity Exchange, so that it has created an organized market with high trading volume and appropriate liquidity in the field of derivatives trading in the country. In this study, we decided to use two models of stochastic differential equations (Heston and Merton) to predict the price of futures contracts and compare the results.

In this study, the behavioral biases and decisions of individual and institutional investors based on technical information in the Tehran Stock Exchange were investigated. For this purpose, two market situations, including the passage of support and proximity to resistance, and the decline of resistance and proximity to support as technical levels in investment decisions have been studied and the effect of 15 behavioral biases of investors in both groups of individual and institutional investors on financial decisions based on buying, selling or not taking action for the transaction were tested. The statistical population of the study included individual and institutional investors in the Tehran Stock Exchange, which 385 individual investors and 100 institutional investors were selected by available sampling method, and the questionnaires were provided to them. In order to analyze the data obtained from the questionnaire, polynomial logistic regression models was used and the results showed that the behavioral biases of individual and institutional investors had different effects on their investment decisions at the levels of resistance and support, and behavioral bias among individual investors has also been more predictive of their investment decisions. The results also showed that the behavioral biases of short-sightedness, excessive optimism and one-dimensional analysis were the same between the two groups of investors.

Through the grid matrix model, stock of companies can be classified according to different characteristics in a matrix then formed portfolios. In this research, using the data of 156 companies listed in Tehran Stock Exchange during the period of 2011-2017 and through the grid matrix model based on throughput accounting’ criteria as the proposed model, the formed portfolios and their performance with the traditional grid matrix model and market portfolio were compared. The results of the research show that the proposed model portfolios have a higher performance than the traditional grid matrix model based on Sharp, Sortino, upside potential and Omega criteria, and the portfolios of companies with high system performance, in addition to the above criteria, also had higher performance than traditional grid matrix model based Jensen's criteria. Also, the performance of these portfolios in terms of upside potential and omega criteria is higher than market portfolio, and the performance of companies with low system performance has a stronger correlation with market portfolios

In this study, we first calculate and estimate the efficiency of all banks listed in the Iranian Stock Exchange in the period 2012-2012. This estimation is made using the model of Eegner et al. (1977). Then, using the three-stage model presented by Shrews & Dahl (1992), Kay Van & Eisenberg (1997) and Altonbass et al (2007), using the Simultaneous Equation Path Analysis method to investigate the relationship between productivity, risk and We have capitalized and calculated the direct and indirect impact of these variables and their impact on each other. The results show that the model used is appropriate and there is a significant relationship between these three variables. The data obtained from this analysis, based on the adjusted coefficient of determination obtained from the research model, show that the impact of productivity and banking risk on capital is greater. Keywords: Banking Productivity, Banking Risk, Capital, Route Analysis

The capital market is one of the financial markets that in a dynamic economy can pave the way for long-term economic growth.Futures contracts that derive their values from an underlying asset, are included these financial instruments.To enter the futures market, the investor needs to anticipate future trends to cover his risk. For this purpose, the appropriate random differential equation has been selected to model the prediction of future coin contracts in the present study. Thus, after providing the necessary explanations about the necessity of using random models and as a result of new principles called random accounts, to introduce the most important stochastic differential equation in financial sciences including geometric Brownian, geometric Brownian with jump term, Heston and the explained model are discussed. Then, the appropriate model is selected, with a practical approach and based on the ability of each model to predict the price of futures contracts by assembling the Monte Carlo. The results of the fitness criteria regarding the predictive power indicate the superiority of the model explained in these contracts.