درخت حوزه‌های تخصصی

The growing expansion of financing through the capital market and the introduction of guidelines for the establishment of credit rating agencies require the development of appropriate credit rating models for financial instruments, on the other hand, the capital financing market framework is centered around sukuk bond. According to the SEO, in the case of credit rating agencies, Sukuk rating will also be required. On the basis of the above, the present study attempted to develop a credit rating model for Ijareh Sukuk as the most important and most advanced tool in financing the capital market, on the one hand, the problems with issuing a Ijareh Sukuk, including the mandatory existence of the guarantor, and, on the other hand, the transparency of the market will provide financing and accelerate the financing process through this market. In the present study, after studying the theoretical foundations, including the rules and instructions issued by the supervisory authority of the capital market, theoretical and scientific principles regarding the rating of securities and institutions procedures in the field of credit rating  Ijareh Sukuk, the basic The model of credit rating is then developed, then the dimensions, components and indexes of the model have been subjected to expert opinion using the Delphi research method. Finally, based on the received comments, the final framework of the Ijareh Sukuk rating system was developed on Iran's capital market.

Value at Risk (VaR) plays a central role in risk management. There are several approaches for the estimation of VaR, such as historical simulation, the variance-covariance and the Monte Carlo approaches. This work presents portfolio VaR using an approach combining Copula functions, Extreme Value Theory (EVT) and GARCH-GJR models. We investigate the interactions between Tehran Stock Exchange Price Index (TEPIX) and Composite NASDAQ Index. We first use an asymmetric GARCH model and an EVT method to model the marginal distributions of each log returns series and then use Copula functions (Gaussian, Student’s t, Clayton, Gumbel and Frank) to link the marginal distributions together into a multivariate distribution. The portfolio VaR is then estimated. To check the goodness of fit of the approach, Backtesting methods are used. The empirical results show that, compared with traditional methods, the copula model captures the value more successfully.

In this research, we use a pair trading strategy to make a profit in an emerging market. This is a statistical arbitrage strategy used for similar assets with dissimilar valuations. In the present study, smooth transition heteroskedastic models are used with the second-order logistic function for producing thresholds as trading entry and exit signals. For generating upper and lower bounds, we apply the rolling window approach and one-step-ahead quantile forecasting. Markov chain Monte Carlo sampling method is used for optimizing the parameters. Also, passive strategy in the out-of-sample period is used to compare the profits. The population consists of 36 daily stock returns in Tehran Stock Exchange. Then, we select ten pairs from these stocks and use Minimum Square Distance method, and five pairs from one industrial sector. Finally, we see strategy1 and 2 have positive returns in the out-of-sample period, and they produce higher returns than passive strategy.

The evaluation of corporate social responsibility has gained significance over the past decade due to the importance of natural and environmental resources. Many studies have been conducted on corporate social responsibility and the presented related models, which add to the importance of this report. However, in addition to its significance, many researchers also believe that corporate social responsibility evaluation models lack the necessary efficiency due to different interpretations, lack of transparency, and abuse of some companies in order to deceive and commit fraud. Therefore, the aim of this research is to present a model to evaluate corporate social responsibility using value added, which can be a suitable criterion in evaluating the social responsibility of commercial entities. In the present study, first, a model was developed based on corporate social responsibility, and then, to test the model, social value added of Nano motor oil was studied as a case study. In this study, data was analyzed through pairwise comparison. The findings of the study conducted on the social value added of Nano motor-oil indicate economic efficiency of 40%, product social efficiency of 8%, and depicts a 38-times increase in social value added compared with its economic added value. Thus, Nano-engine oil producing companies are located on the corporate social responsible category and the corporate social responsibility in this product is on the third level (strong) that indicates the product’s efficiency in the community and can be a suitable incentive for all business organizations to pay more attention to their products’ environmental and social impacts.

foreign investments have always been welcome and policy makers always do their best in order to attract more and more capital into their area; But a question which gave rise to a series of studies is that is FDI always beneficial for the recipient and does it under all circumstances help the growth in the host economy? In order to answer this question, we first examined whether or not FDI, by itself, has any significant impact on growth and the results proved that FDI affects growth positively in our full sample. We then show that FDI’s effect on growth is different in developed and non-developed countries. A surprising finding in our study is that in developed countries foreign flows of investment do not affect economic growth where this effect in non-developed countries is relatively high and significant. Three different stock market indicators (market capitalization, value traded and turnover ratio) are then introduced and it is tested whether the differences in FDI’s impact in developed and non-developed countries is due to their stock-market-related financial absorptive capacities. Our key contribution in this paper, along with our other novel findings, is that we introduce cut-off levels for these three indicators which successfully split our sample into one sub-sample in which FDI strongly affects growth and one in which FDI’s effect on growth diminishes.     

This study was conducted for designing and explaining the convergence-based financial services marketing model in Tehran Stock Exchange. This study was mixed (qualitative-quantitative), and in the qualitative phase, a group of experts in the field of financial services marketing and senior managers of asset management companies were selected and unstructured interview was done for modelling based on ground theory. In the quantitative phase, customers of asset management companies were considered as the statistical population and 500 statistical samples were selected and questioned by questionnaires and 26 hypotheses derived from the initial model were tested. All hypotheses were confirmed but the effect of risk-taking and history of financial services providers on convergence of trends and indexes were rejected. There was also no relationship between history and requirements. Also, conditions and economic fluctuations governing the society and history of financial services providers did not have a significant effect on adherence to requirements of stock exchange.   Finally, the results led to the design of convergence-based financial services marketing model in Tehran Stock Exchange (based on the structure of the paradigm model). Comparing the model of the present study with previous models in the field of financial services marketing, an important and innovative point is the attention of asset manager companies to convergence in the financial markets, which was identified as one of the effective strategies for promoting perceived value and customer loyalty and its effect was also proved. Paying attention to the concept of convergence and contagion between markets and paying attention to parallel markets to get more returns is a significant factor in attracting financial services customers.

Identifying the causal relations between trading volume and stock returns and between trading volume and return volatility plays a vital role in identifying profitable investment opportunities. In this study, the Granger causality test was conducted to analyze the causal relationships between the mentioned variables in Tehran Stock Exchange. Consequently, the Vector Auto Regression (VAR) model was employed to determine the conditional mean equations of returns and volume. Moreover, the bivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model was used to model the conditional variance equation, stating the relationship between volume and return volatility. According to the results, no bilateral causal relationship can be ascertained between returns, volume, and return volatility. In other words, return and return volatility could barely predict volume; therefore, volume cannot be the Granger causality of the other two variables. However, stock returns were found to have an important role in determining the volume. Likewise, return volatility can be used to predict volume accurately. In fact, stock returns and the return volatility were both the Granger causalities of the volume.

Investment is an essential factor in a country’s economic development. Meanwhile, return and risk have been effective factors in investment. Today, many financial economists have accepted Risk or Beta as a standard tool for assessing the risk involved in certain actions. This paper has been conducted to find a way to obtain the risk of industries in different timescales included in the short-term and long-term. The statistical population includes a daily index of selected industries (including banks and the food, and car industries) from 2009 to 2014. The present study has measured the risk in different timescales using the wavelet analysis, and consequently, the risk time series have been expressed using a State- Space model. The direct relation between the risk of the selected industries and the market have been eventuated in which, an increase in return of the market would lead to an increase in return of industries and this has also been proven when there is a reduction in return.  

This article investigates the financial convergence between Iran, OPEC & the Shanghai Organization trade groups, of which Iran is a member.  The analysis covers the period of 2005 to 2017.In order to examine the convergence dynamics of these financial markets; we have employed the Philips and Sul (2007) methodology, which uses a nonlinear time-varying factor model. This paper provides a comprehensive picture of the financial systems within Iran and its convergence clubs by testing the convergence of their money market with domestic credit to private sector by banks (% of GDP), deposit and lending interest rate, real interest rate, and capital market with Stocks traded, total value (% of GDP). The empirical findings show that money and stock markets of OPEC and the Shanghai group do not form a homogenous convergence club. Results show that Iran has convergence with some countries in OPEC and the Shanghai group in money and stock markets, which can be explained by their similar economic indicators in both markets. Furthermore, the convergence speed between Iran and the Shanghai countries is higher than that of Iran and OPEC countries, which proves that joint trade agreements are stronger reasons for convergence than the oil factor. Iran should implement further structural reforms in order to achieve greater financial convergence with its joined groups.