فهرست مطالب shahin ramtinnia

In this paper, the evidence of contract theory regarding the effect of investment opportunities on financing policies is provided using 10125 data collected from 225 companies with non-financial nature and non-negative equity which were active from 2011 to 2015 in the firms list of the Tehran Stock Exchange. In order to achieve reliable results and avoid the consequences of limited periods of time, regression of the integrated data was used as the statistical model. The ratio of properties market to book value, the ratio of stock market to book value, the inverse ratio of price to income, and the criterion derived from factor analysis were used to quantify the concept of investment opportunities and their real options. Financing policy was extracted using the ratio of market value of debts to equities. The results showed that after controlling the effects of companies’ size and their profitability, a significant inverse relationship existed between investment opportunities and development and use of debt in the structure of capital of the surveyed companies. The obtained results are compatible with theoretical explanations in the theory of investment opportunities and contracts between stakeholders in the studied companies.

Portfolio selection, in order to maximize the profit from investment, is an important concern for minor and institutional investors.Therefore; efficient and secure optimization of financial assets is one of the most important new and modern, financial topics, trying to improve the portfolio performance using modern approaches of other sciences. Accordingly, this article aimed to optimize the index returns of top 10 companies of Tehran Stock Exchange from 2011 to 2015 using portfolio risk minimization approach with the maximum yield according to conditional value at risk and differential evolution algorithm(DE-CVaR) on a monthly basis. The results showed that differential evolution algorithm with the conditional value at risk approach, had better Sharpe and returns ratios by CVaR value compared to the random algorithm. The results of posttest with monthly approach also showed that DE-CVaR was better than random algorithm in terms of the criteria for selecting the optimal portfolio.

Among 37 methods to reduce transaction costs introduced by Cha (2007), we recursively choose the best method for next period's investment in each of three portfolio strategies: Mean-Variance Optimization, Mean-CVaR Optimization, and the equally-weighted market. We identify a few of the best methods and offer a framework by which additional methods can be considered. Within our framework, the best methods recapture a substantial amount of wealth and significantly improve risk-adjusted performance, both economically and statistically. We used prices and returns of the 10 most active firms of Tehran Stock Exchange market, from 1391 to 1394 on a monthly basis in this research. The transactions costs reduction methods will be applied on them and the best methods will be identified. Also, a framework will be offered for comparison and investigation of new methods.

Increasing the profits and reducing the risks have always been of the most important issues of concern to the investors in the financial markets. In recent years, many solutions and proposals have been suggested in respect to the frequency of portfolio optimization issue, with the highest return and the lowest possible risk. One of the most prominent suggestions is the Markowitz Model which is mostly known as the Modern Portfolio Theory. On the other hand, the TLBO algorithm which has been presented in 2010 is one of the most efficient meta-heuristic methods to solve the optimization problem. In this study, we are attempting to solve the portfolio optimization problem, according to the framework of the model introduced by Markowitz and using TLBO algorithm. For this purpose, the data related to the returns of 20 companies listed in TSE during the period 2012-2016 were collected. It is worth mentioning that four criteria including variance, mean absolute deviation, semi-variance and conditional value at risk (CvaR) were used in order to measure the risk level in this investigation.

The portfolio optimization has become one of the most important issues for the companies operating in the capital market. When the real-world conditions and restrictions, including cardinality constraint are considered in portfolio optimization, the problem is not easily solvable. Therefore using the meta-heuristic methods will be considered. Regarding this fact, the main purpose of this paper is to solve portfolio optimization problem by using an entirely new and emerging meta-heuristic algorithm that called symbiotic organisms search, while considering the limitations of the real world in the formation of portfolio. This algorithm is inspired by the symbiotic relationship in diverse ecosystems that exist in nature, and introduced in 2014. Finally, the model used in this study has been solved with real data and the results have been analyzed. The results of this paper demonstrate that the symbiotic organism search has been successful in portfolio optimization and has been able to properly interact with the actual limitations of the market.