Iranian Journal of Finance
Volume:2 Issue: 1, Winter 2018

This study aims to present a model for predicting corporate default among Tehran Stock Exchange’s selected industries. To do this, corporate default drivers were identified and selected by referring to previous research findings and using experts’ opinions. These drivers were divided into five categories: accounting ratios, market variables, macroeconomic indicators, nonfinancial factors, and earnings quality measures. Structural equation modeling (SEM) technique was used to derive the prediction model. In this technique, corporate default drivers were used as latent independent variables, and their constituent factors were considered as observable indicators of the above variables. In addition, corporate default, as the latent dependent variable, was calculated by a measure based on the Black-Scholes-Merton (BSM) option pricing model. After implementing structural equation modeling (SEM) technique by use of Smart PLS software, a prediction model that contains influential drivers of corporate default was derived and presented for each of the selected industries.

In this research, we use jump beta and continuous beta as indicators of financial sector companies systematic risk and study their determinants in banking, insurance and investment industry. In result, the value of jump beta is higher than continuous beta. Jump beta of Banking industry and Investment industry is considerably lower than average. We found some negative and positive effects of firm characteristics on jump beta and continuous beta. In insurance companies, the supremacy of jump beta is influenced by firm characteristics. Size has positive effect on aggressiveness of both continuous and jump betas in investment companies. Current ratio has positive effect and debt ratio has negative effect on aggressiveness of insurance companies. Firm characteristic has some positive and negative effects on continuous industry beta deviation, but no effect on jumpy one. Inflation has negative effect on continuous beta but has no considerable effect on jump beta. Inversely, exchange rate has negative effect on jump beta but has no sensible effect on continuous beta. Influence of growth rate is strong positive for all industries of financial sector but weak positive for banking and insurance companies

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.

Classic finance believes that stock price changes are related to systematic changes in the company's intrinsic values. However, recent research shows that behavioral factors play a very important role in determining stock prices and returns of investors, one of these behavioral patterns is noise trading. The purpose of this study is to investigate the effect of unsystematic risk fluctuations on noise transactions. For this study, we use the random variance of the capital asset pricing model-disrupted unit as a measure of unsystematic risk fluctuations and for measuring noise trading We used a comparison of  company market value with industry companies the average market value. The research sample included 92 companies listed in the Tehran Stock Exchange during the period of 2011-2016.  The result of the test the hypothesis of the research showed that the relationship between unsystematic risk fluctuations and noise trading using is positive and significant and thus unsystematic risk fluctuations can be used as a criterion for detecting noise trading.

The study is to review the disclosure quality rank on income-smoothing and informativeness by means of four hypotheses. The timescale is between 2010 and 2016, and 149 TSE’s listed companies are studied. The first hypothesis examines the effect of higher disclosure quality rank on income informativeness. The result confirms that higher rank of disclosure quality improves income informativeness. The second hypothesis reviews the relationship between disclosure quality rank and income smoothing. The findings of this hypothesis indicate lower disclosure quality will increase income smoothing behavior. In the third hypothesis, the effect of income smoothing on informativeness is examined, which results in a statistical view that income smoothing has a sensible positive effect on informativeness. Finally, the effect of higher rank of disclosure quality on the informativeness of the smoothing listed companies in the fourth hypothesis. The findings indicate that income smoothing has a meaningful effect in strong disclosure quality companies.