FINANCIAL RESEARCH
Year:2016 | Volume:18 | Issue:3 |Papers Count:12

The purpose of this study is to investigate the relationship between the quality of company's risk disclosure with information asymmetry under Firm-Riskiness, economic downturn and institutional Analysts in Tehran Stock Exchange To achieve this aim 100 firms were evaluated over the period of 2009-2014. To test the research hypothesis, random data pattern is used. The analysis of risk information disclosure in this study have been investigated by content analysis of the various sections of board of directors Performance Report. The role of the present study is based on the standard which was introduced by Linsley and Shrives (2006). The results of current study show that there is a significant negative relationship between quality of risk disclosure and information asymmetry (bid-ask spread and volume of transactions). Also level of firm-riskiness regarding to level of technology and existence of institutional Analysts in volume of transactions case had a significant impact on the relationship between quality of risk disclosure and information asymmetry. But in Tehran Stock Exchange, risk information disclosure in different Economic conditions has a same impact on information asymmetry.

In this paper we use robust optimization to solve asset allocation problem under uncertainty for return and covariance-variance parameters. Not taking uncertainty into account about input parameters in optimization problems can take optimal solutions away from optimum region or make them infeasible. For designing and defining the set of uncertainty for return and covariance-variance, we use the concept of estimated distance and bootstrap for predictions, respectively. Calculations of the sets of uncertainty are based on predications of ARMA and GARCH methods. In order to ensure that robust approach’ s results outperform the nonrobust approch’ results we use robust sharpe index with the help of pair comparison test during eight consecutive quarter periods. Finally, some numerical examples are given to illustrate the effectiveness of the proposed approach.

This paper investigates the relative performance of Value-at-Risk (VaR) and expected shortfall (ES) models using daily overall index data from TSE for a period of 8 years from 2008 to 2016. The main emphasis of the study has been given to Conditional Extreme Value Theory (CEVT) and to evaluate how well Conditional EVT model performs in modeling tails of distributions and in estimating and forecasting VaR and ES measures. We also compare them with parametric approaches. We have compared the accuracy of Conditional EVT approach to VaR and ES estimation with other competing models. We use Bernoulli coverage and Independence of violation tests for backtesting the VaR models and McNeil & Frey’ s Backtest and Model Confidence Set to assess the performance of the ES models. The best performing VaR and ES models is found to be the Conditional EVT. MCS function result for ES also shows that the Conditional EV with student's t standardized residuals, Conditional EV with normal standardized residuals and GARCH with student's t residuals models are respectively ranked first to third.

Value at risk is one of the most common risk measures which, considering its dependency on volatility return, uncertainty of volatility prediction models and existing bias in parameter prediction, is subject to bias. Also the broad usage of this measure has caused anxiety for investors about the estimation accuracy. So, according to the importance of this issue, this study compares precision of Markov Regime Switching GARCH and GARCH in VaR estimation of Tehran Stock Exchange index (TEDPIX) with constructing Bootstrap confidence interval and measures the possibility of rotation and movement of both high and low volatile regime on precision of value at risk estimation. The results show that Markov Regime Switching GARCH lead to more conservative value at risk estimation than GARCH model and it is more suitable for risk aversion investors.

Morkowitz model is one of the well-known models in portfolio selection problem. This paper presents an extended version of Markowitz mean semi variance portfolio selection model. The extended model considers sets of constraints including cardinality, bounds on holdings, sector capitalization, an entropy constraints. It also considers transaction costs. The problem model has a combinatorial structure. Due to the NP-hard characteristic of the resulting mathematical model, Harmony Search Meta-heuristic algorithm was used to solve the model. Since the proposed mathematical model is a multi-objective one, the Pareto solution approach was applied. To investigate the applicability of the proposed model, a data set of ten stocks from Tehran Stock Exchange, from March 2011 to December 2015, is used as a case study. The obtained efficient frontier indicates the applicability of the harmony algorithm in the optimization model. Research results show that the proposed model is efficiently is capable to consider the investment portfolio requirements quite well.

Up to now various methods have been used to predict stock prices and profits. According to financial volatility markets, the most important thing is which of the methods can be applied to predict the optimal decision to help managers and decision makers and business sectors. Most studies have been done up to now to predict the time series, autoregressive method known as Box-Jenkins has been used to predict the time series. While there are many time series with seasonal variations or cyclic which can not be adequately modeled by a polynomial. In this study, Holt-Winters method is used to predict non-stationary time series data for the profit sale of an intermediate product. The results show that the proposed method compared with classical methods and procedures S-filtered has a higher performance in forecasting future values.

The purpose of this study is offering a new model based on microstructure models in order to explain herd behavioral in the capital market of Iran. Using this approach and daily transaction data in one year period (235 trading days) and based on Cipriani & Guarino model, this study has done. This study uses Mokhaberat Company share data as statistic sample. The process of data has done by Matlab. Analyzing data by SPSS showed the evidence of herd behavioral for all trading days in this company. Also herd behavior in sale transactions is more than buying shares. In addition it is observed that herd behavioral is more than any time at the start minutes of transaction beginning.

Firms’ tax amounts represent cash outflows from firms to the governments. Cash flows which could be invested and create value for the firms. Therefore firms have been tried to restrict those cash outflows through implementing different tax policies. This research is about to develop and test a tax policy predictor model. Statistical model consist of 85 public firms listed on Tehran Stock Exchange (TSE). Structural equation modeling is the statistical instrument. Religion and trust in public sector are proxies for cultural values. Results indicate that cultural values affect firms’ tax policy while intermediating variables are in and have no impact when those intermediating variables are not included. Other findings show effects of capital structure on tax policy development by firms.

This study in first stage, describes the transaction costs imposed on credit institutions and the factors affecting them from the traditional model of transaction cost economics and also introduced the "relationship lending" as a variable that points to reduce the information asymmetry between the borrower and the credit institute. The impact of this variable using Ordered Multinomial Probit Model on the Williamson model will be examined. Credit institutes under this study have been collected as a random sample from banks in Tehran. These banks had been authorized by central bank of Iran till March 2012. The results shows that with the introduction of the independent variable "lending relationships" the final effect of the independent variables "investment in specific assets", "special collaterals", "degree of uncertainty for the credit institute" and "difficulty in measuring employee performance" on variable of transaction costs of lending will be reduced.