Modeling and forecasting the volatility of Tehran Exchange Dividend Price Index (TEDPIX) The present research, analyses the forecasting performance of a variety of conditional and non-conditional models of TEDPIX volatility at the daily frequencies performance criterion namely the root mean square error (RMSE). Under RMSE, results show MA250 and CGARCH models had better performance between non conditional and conditional models respectively. Results of combined models also show that non-conditional models have had better performance relative to conditional models. Further, result of Diebold- Mariano test shows that the forecasting performance of MA 250 is not statistically significant from that of CGARCH.

The aim of this research is the investigation the relationship between the capital structure and institutional ownership mid to the other effective factors on this relation in Tehran Stock Exchange. The others factors include the percentage of stock dividend, profitability, business risk, assets structure, liquidity, growth, and company size. The statistical population of the research is 117 listed companies in TSE based on 7 industrial groups during 1383-1388. To testify of the research hypotheses applied pooled regression models with fixed effects by econometric software Eviews 6. The findings indicate all factors except the percentage of institutional structure were the effective factors on the capital structure in the level of total companies. However, in chemical industry, the percentage of institutional structure, the percentage of stock dividend, business risk, liquidity, and company size; in food industry, assets structures, liquidity, and company size; in metal industry, the percentage of institutional structure, the percentage of stock dividend, business risk, assets structure, liquidity, and company size; in non-metallic mineral industry, liquidity; in tile industry, business risk, and liquidity, and in materials and pharmaceutical products industry, liquidity, and company size were effective on the capital structure.

Contrarian and momentum investing strategies are two techniques which are used in stock markets to enhance portfolio return. Contrarian investing strategy states that stocks which had better performances in the past should be sold and stocks that had poor performances should be bought. In practice, this strategy is used for a package of stocks and for portfolio formation. The main objective of this paper is to investigate the profitability of using Contrarian investing strategy in Tehran Stock Exchange (TSE). The sample period used is from the early 2002 until the late 2007 for 70 listed companies in TSE. The result of this paper shows that the average return on loser portfolio is statistically significant greater than winner portfolio for 12 and more months after portfolio formation.

In this paper disposition effect, selling winners and holding losers, in Tehran stock exchange (TSE) investment companies and its effect on these companies’ cash flows and performance using Odean model has been reviewed and investigated. Research findings show that the realized profit ratio is %19 higher than the realized loss ratio in all of investment companies in TSE. This mean there is a behavior based on disposition effect in these companies. Other research finding which has been done by Generalized least square (GLS) method shows that the behavior based on disposition effect of investment companies has, negative effect on their performance (risk-adjust return).furthermore the result of this research shows that between investment companies dispositional behavior and cash flows are direct and significant relation. The result of this research denotes that disposition behavior has negative and significant effect on high performance companies cash flows and makes a direct relation between low performance weak cash flows.

The Purpose of business entity is to maximize shareholders wealth by enhancing the firm’s value thus, getting expected returns are very important for them. Investors and creditors are going to find a precise scale for measuring overall performance of a firm as a whole to decide whether to invest in the firm, to continue with the firm or to exit from it. Economic Value Added (EVA) is an analytical tool for detecting of a true enterprise value of the firm. On the other hand EVA is a substitute for accounting profit as a scale for measuring overall performance. In this paper, we attempt to present a framework that shows how stock market liquidity and economic value added variables have effected on enterprise value, investigate the relation between them. In this framework, lower cost of capital and high EVA arise from improvement of performance and liquidity. The empirical analysis uses a panel data of 154 companies listed on the Tehran Stock Exchange from 1383 and 1388. Results show that there has been positive and significant relation between EVA and Liquidity. Also we find significant correlation between these variables and enterprise value that it shows these variables are interacting with each other.

Collateralized mortgage obligations are derivatives securities based on mortgage loans which issued in different maturities, interest rates and credit ratings. In Iran attention to decision authorities for the first time allowed Iran Melli bank and Maskan bank to issue this kind of securities. One of the main questions in issuing this kind of securities is maximizing the issuer profit by choosing optimum maturity, number and size of each trench. In this paper by using combination of dynamic programming approach and Monte Carlo simulation technique we maximize the profit of issuer by optimizing the maturity of mortgage backed securities (reduce in issuing cost). Considering 3 trenches and up to 8 years maturity with 12% average rate of pool of mortgages, the result of the model determines the maturity of 4, 8 and 3 years respectively for first, second and third trenches. Compared with the proposed 5-years and non-classified mortgages, dynamic programming model leads to rise 1.2% in profit of issuer.

In this paper, In order to optimize the portfolio consisting of selected industrial stocks of Petroleum products, automobiles and parts, electrical industry and extraction of minerals from Tehran Stock Exchange member, First, time – varying conditional covariance matrix has been estimated based on the following Multivariate GARCH models: Diagonal-Vech (1,1), CCC (1,1) and Diagonal -BEKK (1,1). Then the portfolio risk minimization problem has been solved according to the Markovitz theory and the optimal time-varying weights of the four selected industries have been specified. Optimization results indicate that based on all above models, more weight in the portfolio allocated to the industries that their volatility in stock returns is less than others. The optimal time-varying weights for industries that have increase in their output volatility, has fallen and vice versa if the output volatility over time has decreased, and the share has increased.