FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT)
Year:2012 | Volume:3 | Issue:12|Papers Count:8

Portfolio selection problem is one of the important areas in financial decision making. Generally, in the portfolio selection problem the Decision Maker (DM) pays attention to several objectives, such as annual return, annual dividend and risk. Multi-objective programming techniques such as e-constraint, utility functions and goal programmings are used to select the best satisfying portfolio by the DM. In this paper, we assume that some of the input problem parameters such as return of stocks is random and normally distributed and probabilistic methods, chance constrained programming, are utilized alongside min-max goal programming and goal chance constrained Programming model is introduced as a deterministic transformation to multi-objective Stochastic portfolio selection model. To demonstrate The Proposed program, samples of 20 stocks from the Dow Jones Industrial Average are presented.

Standard finance theory is a prescriptive theory of what the investors should do, but behavioral finance is the study of the influence of psychology on the behavior of financial practitioners and the subsequent effect on markets. Kahneman and Tversky (1979, 1992) showed that four novel concepts (Loss Aversion, Asymmetric Risk Preferences, Mental Accounting, and Probability Weighting Function) in Cumulative Prospect Theory.In this research, concepts of behavioral finance are surveyed and the mathematical model of portfolio selection in framework of behavioral finance theories is presented. Historical data of TED PIX for 10 years has been used and separated to 2 parts of test and evaluation groups. The optimum weight for risky asset proposed by standard mean-variance and behavioral model based on returns with standard deviation and semi standard deviation for the first 7 years (test data) in the 3 months periods. After that, returns of 81 optimum portfolios in a three years evaluation period are calculated. Statistical results show that in Tehran Stock Exchange the research hypothesis, return of behavioral model is greater than return of standard mean-variance model, was rejected, but behavioral portfolio risk is significantly less than the standard model.

The primary aim of this paper is to determine the optimal capital structure using the indices of value-based performance assessment and Appling the data envelopment analysis for the companies listed in Tehran stock exchange which in this research has been segregated into 10 industries. In this paper in order to determine external variables in DEA model, first we have investigated the relationship between the financial leverage as capital structure and both economic value-added and market value-added as indices of value-based performance assessment. The results implied that there is a significant and inverse relationship between cited variables at 198 firms and 10 industries. Based on this significant relationship, the financial leverage or capital structure and both economic value-added and market value-added have been chosen in DEA model as internal and external variables respectively. In the next stage, Appling the BCC model which is one of the two models of DEA, the optimal capital structure for 198 companies has been determined.

One of way for specifying entry and exit time to exchange market is technical analysis.in this research profitability of some high usage technical analysis indexes has been studied. Therefore, the return of 13 trade rules, including kinds of moving averages as active investment strategy and return buy and hold method as passive investment strategy in five countries of Iran, Oman, Jordan, Kuwait, Turkey has been evaluated. To do statistical tests, bootstrap technique has been used. Results showed that in most cases technical analysis rules has been more profitable than buy and hold strategy and short-term technical analysis rules had more profitability and among studying countries, Kuwait with most numbers of technical analysis rules profitability, showed that has more potential in using technical analysis rules. and Jordan, Oman, Turkey placed in next ranks consecutively. Iran is in the last rank with the least numbers.

In recent years, there has been an increasing interest in the study of the nonlinear properties of macroeconomic and financial time series. In macroeconomics, the study of nonlinearity is based on an intuitive assumption that both the nature of the structural shocks hitting the economy and the dynamic properties of the economy might have changed. Using conventional econometric tests implies that the time series often contain unit roots and are due to the nonstationarity I(1). Some of these results contradict economic theories. Also, there is always an uncertainty about shifts in the persistence of a time series, such as shifts from stationarity I(0) to nonstationarity I(1) or vice versa. This thesis has attempted to investigate the nonlinear model and generalized stochastic unit root (GSTUR) using Bayesian analysis and MCMC numerical methods on the TEDPIX time series. Besides, a comparison between the nonlinear GSTUR model and the linear RW model can be achieved via the Bayes factors, which is not available in the classical framework.Using the NSE, RNE and CD, in this paper we investigate the MCMC algorithm and with sensitivity analysis on the prior parameters values, the sensitivity of results to changes in parameter values is investigated. Also the structural characteristics and parameters of distributions is checked and no significant Autocorrelated, with long lags, and the posterior data were fitted with the expected distributions, have been investigated. Implementation of the model with 48 models GSTUR, it was observed that the increase in p has little effect on improving the model. In all cases, the Models without the constant and regression not prefer to RW model, and compare the Bayes factor, the RW model is supported. But in all other types of GSTUR models class, these models are preferred to RW model. The results suggest that there is evidence of nonlinearity in TEDPIX time series and with a 99% probability it has a trend stationarity.

Data Envelopment Analysis (DEA) covers an extended range of mathematical optimization models to assess relative efficiency of a set of homogenous units with similar inputs and output. This model obtains a set of weights for input and output variables of decision-making units and then calculates relative efficiency of each unit. The present research aims at introducing Data Envelopment Analysis (DEA) technique and BCC Model in output oriented to calculate efficiency scores of manufacturing companies accepted in Tehran Stock Exchange based on financial reporting indices and rank them by Anderson-Peterson (A & P) Model. To this end, financial statements of 100 manufacturing companies accepted in Stock Exchange for period of 2004 to 2010 were analyzed.Efficiency indices including seven inputs and one output constitute the basis of the above technique. The results reveal that efficiency score of the companies accepted in Stock Exchange was calculated separately for the appointed period and the companies scored one in each period were considered as efficient companies and those scored below one were regarded inefficient. The results indicate high ability of DEA mathematical model in identifying efficient companies and ranking them based on the data reported according to their financial statements.

Many performance measures, such as the classical Sharpe ratio have difficulty in evaluating the performance of mutual funds whose return distributions are skewed. In this article, we examine the ability of the downside risk and the upside potential ratio (UPR) in evaluating the skewed return distributions. We have used a sample of the active mutual funds in the Tehran Stock Exchange (TSE) for the period of 22- dec - 2010 To 22- dec - 2011. In order to make a fair comparison between the Sharpe ratio and UPR, we assume that MAR in UPR plays the role of the risk-free rate in Sharpe ratio. We constructed a ranking based on both criteria, and we find a very high correlation between the Sharpe ratio and the UPR. This has seen to be the result of normal in the return distributions. Therefore, we prefer to use the UPR as an alternative to the Sharpe ratio, as it gives a more adequate evaluation of the forecasting skills.

This research aims to identify the dimensions of E-Service Quality of Stock Market in Iran ,and to develop a reliable and valid instrument to measure the quality of electronic services according to user's views based on the modified E-SQUAL and E-RecS-QUAL scales. The research model contains 8 main criteria and 41 sub criteria. For data gathering, library method and fieldwork were utilized and for analyzing data, factor analysis was applied.The results show that there are positive and meaningful relationships between efficiency, availability, fulfillment, security, training, responsibility, contact and law cases with electronic service quality in which, ranking of 41 sub criteria shows that "enables users to search what they need", "complete transaction quickly", "Protection of users personal information" are more powerful than others. Finally some suggestions were presented.