نشریه تحقیقات مالی
پیاپی 27 (بهار و تابستان 1388)

According to stock price excessive volatility in Tehran stock exchange, the price limit mechanism is utilized in order to making the price fluctuation narrow and based on the specific periods, the price limit has encountered some variations which price limit has been determined by try and error within these periods and in a short stage of time many modifications existed through the applications of the price limit practice; without considering its real effect on market and reaction of the investors to the variation of the price limit. In this study, the price limit modification from %2 to %3, happening on some effective variables in Tehran stock exchange, as the focal point, is mainly analyzed. To analyze the research data, descriptive and inferential statistics have been used. To test the hypotheses, we have used econometrics and statistics methods such as GARCH model and Multiple Linear Regression. Significance of models coefficients have been measured by P-Value at significant level equal to 5%. Statistical population in this research includes all of the listed companies in Tehran Stock Exchange within the time bracket from 1/7/1386 to 30/9/1387 in a daily approach. The conclusions of this study revealed that the price limit modification from %2 to %3 in Tehran stock exchange within the examined time period does not have significant effect on market volatility, market return and trade frequency, unlike the significant effect on increasing market trade size, decreasing turn-over velocity or decreasing liquidity. In other word, the conclusions are reasoning that for a certain one percent increase of the price limit in Tehran stock exchange there will be no significant effects on core variables in the market.

This research intends to investigate the relationship between financial information transparency and investor behavior in TSE, in order to provide safety trade and improve performance of the financial market in Iran. In last decade transparency of the financial market has been known as one of the most effective variables in determining investor strategy. This study examines perception of transparency among investors in TSE. In the study used by questionnaire and for analyzing the data, SPSS software and the test of correlation, Independent Sample Test and One-Way ANOVA have been used. Results showed that three dimensionsi.e. transparency of ownership structure, information disclosure and transparency of board structure effect on investor behavior, however investors give more attention to the information disclosure. Also investor’s perception of transparency dimension considering demographic variables is different.

The aim of this paper is to identify and analyses the influence of shareholder ownership identity on payout ratio for a panel of Iran firms from 2002 to 2008. We found that there is a significant positive correlation between institutional ownership and payout ratio. The relation between payout ratio and individual ownership is negative. The most finding of the study indicates that Iranian companies with highly concentrated ownership distribute more dividends. We show that there is a significantly positive correlation between the institutional ownership and the payout ratio. The relation between payout ratio and individual ownership is negative and the ownership concentration measured by the five largest shareholders affects positively on payout ratio.

This research analyze the resource and structure of cross-autocorrelation in returns and volatility of stocks that listed in the Tehran Stock Exchange during the period Farvardin 1382–Eisfand 1386, with employing the GARCH model. At the first, the results show that, in down(bear) market, return on high trading volume portfolio lead return on low trading volume portfolio, when controlled for firm size, but this is the case for short-term. Second, this study indicated volatility spillovers from low trading volume (small size) portfolio to high trading volume (big size) portfolio returns. These findings are just opposite of the results documented by Bartosz Gebka. Additionally, the empirical finding indicates that the speed adjustment of the returns portfolio to market- wide information is the same for up and down markets. These findings are contradictory with the results of Bartosz Gebka. He show that, in both up and down markets the speed of adjustment of low volume (small size) portfolio to common market-wide information is slower than the lagged high volume (big size) portfolio and this is the case for either short-term or long-term.

The research problem investigated in this paper is modeling volatility and analyzing risk and return’s relationship in Tehran Stock Exchange using GARCH-family models including GARCH(1,1), GARCH(2,2), EGARCH(1,1), PGARCH(1,1), TGARCH(1,1), GARCH(1,1)-M and CGARCH(1,1). Using the daily returns of Tehran Stock Exchange companies, we focused on two portfolios of all the companies during a 10-year-period and those liquid ones during a 5-year-period. In order to meet the distributional characteristics of the financial time series, we have used Normal, t-Student and GED distributional assumptions. The results of this survey and applied research show that first, the conditional volatility models best succeed in modeling characteristics of financial data including volatility clustering, long memory and leverage effects. Second, for both portfolios, increased risk will lead to a rise in the returns.

Today most of financial analyst believes that companies for creating value should have more return than cost of capital. This concept is operationalised by applying EVA an IR. As a result of changes created by Stewart in the RI concept, EVA has become a new tool of financial performance management. Stewart believes that for evaluating internal and external performance EVA should be used instead of income and cash flow from operation. Accordingly these research investigates the relation between depended variable including EVA and RI as the proxies of the economic evaluation model and future EPS. The research hypotheses were tested by using linear regression. The results show that future EPS has a significant relation with RI but not with the EVA there for only RI has predicting power.