JOURNAL OF ASSET MANAGEMENT AND FINANCING
Year:2017 | Volume:4 | Issue:4 (15) |Papers Count:7

The portfolio selection problem and optimizing it is an important issue in investment field. This process aims to create A portfolio that incur the minimum amount of risk to the investor in different levels of return. The existence of statistical uncertainty and noise in information, which is used in the process of optimization, would hamper the performance of optimized portfolios. The purpose of this article is to eliminate the noise of correlation coefficient matrix by using clustering method. In order to do so, two clustering methods, Single Linkage and Average Linkage, are applied, and the optimized portfolio based on the Tehran Stock Exchange information from March 2007 to March 2013 is obtained. The results show that such portfolio is more reliable and provides less risk to the capital owner. For analyzing the robustness of the results in a wide range of different investment horizons and numbers of assets, a Bootstrap analysis with resampling is performed and in most cases a significant improvement was observed.

Among the essential activities of banks to benefit their clients and themselves is the allocation of resources. One of the essential aspects of resource allocation is determining the optimal combination of payment facilities to various economic sectors. In this article, using the post-modern portfolio theory approach (the Mean-semi variance approach), the optimal portfolio of shared facilities of Iranian commercial banks is determined. The average monthly stock return of the companies operating in each sector (during 2008 to 2011) is used as the return rate of each sector. Results indicate that, in order to have minimum variance or the maximum risk aversion, participatory facilities should be allocated as follows: 33% to the industry sector and mining, 22% to the housing and building sector, and 29% to the agricultural sector. Also commercial and service sector are allocated 16% of the facilities which is relatively risky, so that with an increase in the risk acceptance of the banking system and at the expense of decreased share of facilities in the industrial, mining, and housing sector, the optimum share will increase to 26% and then decrease with further increase in risk acceptance rate.

In this research, a new model for valuation of financial contracts is designed by using guaranteed and participation rates. In the traditional methods, valuation of these contracts is determined with the use of minimum guaranteed rate of returns such as risk free rate. However, the proposed model is based on the valuation of these contracts by guaranteed and participation rates as well as the customer's risk tolerance and investment risk. In this model, first an asset allocation model is considered in order to model market elements such as certificate of deposit, bonds and stocks. Then, conditional value at risk, as a proper risk measure, is used to determine guaranteed and participation rates and fair valuation of the contracts. To improve the validity, the model is run for both the capital markets of Iran and the United States of America. The variables used in this study are interest rate of banks, bonds and stock index from 1998 to 2012 in Iran and from 1980 to 2012 in America.

This article investigates the relation between market competition and dividend policies. Using a sample of listed companies in the Tehran Stock Exchange in the period of 1387-1391, we find that firms in highly competitive industries prefer to pay more dividends. Research hypotheses are developed based on the outcome theory and substitution theory. In order to investigate the impact market competition on dividend policies. To test the hypothesis were used panel data regression model and logistic regression. Results indicate that there is a significant positive relation between dividends paid and market competition, return on assets and lifecycle. Also there is a significant negative relation between dividends paid and financial leverage. On the other hand, using the logit model, results indicate that there is a significant positive relationship between increase dividends paid and market competition. Results also demonstrate that there is a significant positive relation between omit dividends paid and return on assets and financial leverage. Also there is a significant negative relation between omitted dividends paid, market competition, growth opportunities and life cycle.

Asset and liability management is considered as the most important financial aspect of the long term strategic planning process. Accordingly, one can study different aspects of balance sheet with planning, directing and controlling different levels of assets, liabilities, and owner’s equity. Since the management of assets and liabilities is implemented under an uncertain environment, this research deals with the analysis of asset and liability management with the use of goal programming and fuzzy multi-objective group decision making approach and analyzes the deviations of the asset and liability management models by applying fuzzy terms.

This study is based on Mousavi and Setoudeh (2013) that simulates stock price behavior of national Iranian copper industrial companies in Iran stock exchange. This paper provides the possibility of analyzing stock price fluctuations and forecasting intrinsic stock price from internal and external viewpoints. For modeling stock behavior, some internal and external factors are identified and the relation between different variables is shown by causal diagrams using system dynamics approach. The financial variables are considered in three groups of pricing, price, and debt financing. Research model is simulated and analyzed by this approach and by using the Vensim DSS software. The overall results indicate that stock supply has important effect on stock price, and debt financing has positive impact on stock’s intrinsic value.

Although many studies have tried to construct a theoretical or empirical structure of relation among trading volume, stock return and return volatility in financial markets, there still is not a general consensus about it. This study discovers latent information in variables time series for 96 months (April 2007- March 2015). To do so, related time series decomposed by using the maximum overlap discrete wavelet transform and wavelet coefficients has calculated. Then the relation between the series is examined by Granger causality test. The main feature of this research is to investigate the relation between variables at different time intervals. The results show that during the 2007 to 2015, the relation between variables in different time intervals varies. As in some periods, the Granger causality test confirms the causal relation between time series, while in some other time periods it does not support the existence of such relation.