فهرست مطالب ahmad nabizade

  In general, financial literacy is the ability to effectively understand and apply various financial skills, including budgeting for money management and investment, which leads to self-sufficiency in financial principles and ultimately leads to improved financial life. Accordingly, the main purpose of this study can be considered the effect of financial literacy on the intention to invest in the stock market by considering the tendencies and behavioral controls of investors and emphasizing ethical and subjective norms in the Tehran Stock Exchange.The statistical method used for the data analysis is the Structural Equation Model. According to the research questionnaire, the sample size of the research is 125 to 375, which 310 questionnaires were collected and analyzed. The results show that the financial literacy of the investors are meaningfully effective on the tendency of the investor in the stock market. Furthermore, the moral norms of the person also affect the intention of investment.: On the other hand, financial institutions and stock exchanges, considering the issues raised in this study, can consider the rational and irrational reaction of investors, based on financial literacy and emotions along with the source of risk, so that they can make recommendations and instructions

Measuring credit risk and estimating the likelihood of companies failing is one of the most important challenges in the credit sector. Structural and non-structural models are the two main frameworks for estimating default risk and credit risk. But each of these models has its strengths and weaknesses, and it seems that combining these two frameworks and providing a hybrid model can provide a more accurate prediction of companies' default risk. In the present study, a hybrid model has been used to measure the default risk of listed and over-the-counter companies in the period between 2007-2017, which has been transferred to the basic market according to the laws of the Iranian capital market. First, the Merton model (structural models) was used to measure the risk of default of these companies, and then the results of this model were compared with the Z-Altman model (from non-structural models). Then, by regression analysis of different financial ratios, significant variables were identified and Morton's and Z-Altman models were statistically and comparatively compared. The findings show that the hybrid model offers a more accurate prediction of the risk of default than structural and non-structural models. By entering the results of each of these two models into the hybrid model, the statistical power of the hybrid model increases. Therefore, using a combined model will help banks and credit institutions to provide resources to healthier companies with less risk.

Mutual funds, by having a net asset value near to 102,771 thousands billiard Rial by the end of 2019 plays an important role in Iran's capital market. One of the factors affecting performance of these funds is the activity level of its portfolio compare to index. The fund managers, despite the mutual funds expenses, have been always questioned if they had been able to outscore the market or not? In this research, the impacts of active management, expenses ratio, turnover ratio, size, fund flow ratio and individual investor share ratio on mutual fund performance are studied.

By using Fama – French five factors model and mutual funds monthly return, the value of alpha and R-Squared (R2) indicating the performance and passiveness of fund respectively, will be calculated. R2 value is always between zero and one. When R2 is close to one, it is indicating that fund’s performance is like market index and the portfolio is managed passively or the fund’s portfolio is a closet indexer. In other hand, when the value of R2 is near to zero, it shows that the fund’s portfolio is managed actively. Thus, the active management is proportional to (1 - R2) value. Finally by utilizing regression equation, the impact of mutual fund’s active management, expenses ratio, turnover ratio, size, fund flow ratio and individual investor share ratio on fund performance is investigated.

According to the results, there is a significant inverse relation between active management and mutual fund performance. Funds with larger size and higher expense ratio show improvement in performance, and increment of fund’s flow reduces its performance. In funds with weak performance, there is a reverse relation between turnover ratio and performance. Also, there is a significant direct relation between individual investor share and fund’s performance.

Active management did not result in performance improvement in Tehran Stock Exchange Market.

As banks’credit risk instability has a critical role on monetary and financial system, this study focuses on factors affecting both specific banking factors and macroeconomics factors on the credit risk of commercial banks in Iran. Based on Judgmental sampling method data of 9 independent and dependent variables was analyzed at the level of the commercial banks and the macroeconomics of the country by generalized method of moments (GMM) during the period from March 2009 to March 2016. The results show that the ratio of non-current facilities (NPL) of the past period, and the growth rate of GDP without oil with non-current facilities ratio (NPL) have a positive relationship with credit risk and bank's capital, the growth rate of oil revenue and credit growth, have a significant and negative relationship with credit risk. Also, bank size, inflation rate, and return on assets have a significant relationship with the credit risk criterion (NPL).

chooseing the optimal portfolio is an integral issue in investment. It is challenging to estimate the tock return rate because of the vague nature of future events. Hence, it is recommended to add diverdity to cover the related risks. According to Markowitz’s modern portfolio theory, assets return has normal distribution. But empirical evidences show that assets return distribution is not normal and we would consider higher moment and Entropy as diversification indexes in this paper. In this study, a new approach for polynomial idealistic programming which is basedon a mean-variance-skewness-kurtosis-entropy model is proposed and two measures of Shannon entropy and Gini-Simpson entropy are used. The results indicated that the proposed approach is well-suited, especially for portfolio models with higher moments. The findings showed that using entropy as a diversification index cannot cause any significant decrease in optimized values for other goals. Using Shannon entropy and Gini-Simpson entropy models can lead to an increase in return and Shannon entropy model can yield more diversification compared to Gini-Simpson entropy model.

Portfolio optimization is the one of most important problems in financial theory. Different strategies can be selected to manage the portfolio that include two kinds is called passive and active. Index tracking is one of most important passive approach. So, there are different models and algorithms to make index tracking portfolio. The aim of this research is analyze of down side beta in the index tracking portfolio. So, three models are presented. Then, to solve these models, evolutionary algorithms include genetic and deferential evolutionary algorithm is used. To show sufficiency of the models, Tehran stock exchange data are selected. Results show the model based down side beta with deferential evolutionary algorithm has higher efficiency Compared with two another models.

The purpose of this study is to provide an appropriate pricing model and also addressing the common deficiencies in other valuation models. To this goal, a sample of 82 companies is selected. (Financial companies, companies with fiscal year different from end of 29th of isfand, companies which their stocks were not traded in past 3 month and those which listed after 1389 are excluded). Then portfolios based on the third and fourth moments are formed by the sampled companies. We used three pricing models including CAPM, Fama- French 3 factor model and Carhart Model for each portfolio. Results show that estimating these models accounting third and fourth moment lead to increase of significance of these models. But the insignificance of the interception of difference between two portfolios showed that third and fourth moment premium are not priced which can be due to assuming homogeneous investment horizon for investors. For this, using wavelet analysis, we analyzed three portfolios with in two horizon levels including level 1 (2 to 4 month) and level 2 (4 to 8 month). Results interestingly showed the improvement in significance and also in R^2.
Using GPH estimator, we showed that there is long term memory in studied time series. In order to making these series stationary, we used recent method by calculating fractional data and again we estimated the models. Results showed that models estimation significantly improved for all three portfolios. But except CAPM for the two first portfolios, in other models the risk premium is not priced. Comparing fractional models with those obtained by wavelet models strongly indicates the superiority of the latter. Comparing all models, we concluded that best model for pricing, based on the third moment, is fama- French 3 factor model in level 2 daubeechies4 and by regarding the fourth moment, CAPM is optimal one for the level 2 symlts8.