FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT)
Year:2013 | Volume:4 | Issue:16|Papers Count:8

As a principle, the performance of each organization should be measured as far as possible. There is a direct relationship between the presence or non presence of an efficient performance assessment system and the life and death of an organization. As such, lack of performance assessment system have been considered as organizational disease. Without measurement there will be no basis for performance evaluation. what cannot be measured cannot be administered.The present study deals with the efficiency of I.A.U, s large branches and the effect of benefit ratios on them. In order to evaluate the efficiency of higher education systems, one of the modeles, mathematical model of operation research entitled Data envelopment analysis (DEA) have been used. In order to apply this model concretely, financial performance of 70branches of I.A.U have been studied in the time span (1388-1390). Financial Performance of these branches by variables of operational expenditures and net worth, net profit and net operational cash flow which are of high theoretical back ground have been analyzed under the title of two inputs and two out puts and then results have been assessed by optimizing GAMZ saft ware and combinational method.The most efficient and the least efficient branch have been recognized. By a number of benefits financial ratios including ROE, ROA, OCF, LN T.A, their effect on efficiency have been studied with multi –variables regression. The results indicate that all calculated benefit ratios except net profit ratio to net worth have significant relation with efficiency.

A short memory process that encounters occasional structural breaks in mean can show a slower rate of decay in the autocorrelation function and other properties of fractional integrated I (d) processes. In the present study, this is discussed by long-term memory's semi-parametric and parametric tests and diagnosis and determine the time breakpoints by OLS tests based on CUSUM, SupF and Bai and Perron (1998, 2003). The result indicates that there are simultaneously long memory and time breakpoints in TEPIX series. Therefore, for a correct deduced about the market memory, statistical proporties and long-term memory tests was checked in pre and post periods of time breakpoints. Results is supported the approximately same statistical properties and existence of long memory in all divided partitions. Moreover, to ensure the long-term memory is unaffected by the structural breaks, Smith' (2005) modified GPH test was used. Resulting in, modified GPH estimator has supported the unaffected of long-term memory from breakpoints. Finally, it can be claimed that the TEPIX memory is long and actual. Therefore, this evidence shows a true long memory not due to structural break.

Is known so in order to stopping Iran's activities in nuclear energy colonial governments many sources were used. one of the tools are sanction against Iran. Recently European governments and American were to seriously review and discussion is sanctioned by the central Bank of Iran. About the management of such decision the research the possible effects banking sanctions looked history of research and also according to the comments intelligent identified and with using method fuzzy DEMATEL important cases and their deep has identified and has prioritized. Results Obtained Shows Seven factors are Effective and eight operating are reception. Respectively of damages effective are: Exchange rate, problem to open credit, creation problem to get resources currency, difficulty to trips of business, increase risk to resources of bank, increased cost and talking time and transactions and reduction public trust to banking system. The end with target applied to research and empowerment management deal with factors of effective are ways were presented.

Quantifying the uncertainty is one of the most important subject in financial issues, so nowadays in each financial and investment activity risk assessment and management is required. One of the key concepts in financial risk management is value at risk. In recent years, many methods presents for value at risk forecasting that Achieves to different results due to differences in assumptions. In this study we present the Monte-Carlo simulation based on random walk process for value at risk forecasting. Then this method used for value at risk forecasting by Tehran Stock Exchange (TSE) data and the results compared with historical simulation and variance-covariance methods. The results show, especially in the high confidence level, Monte Carlo simulation is a reliable and more competent method for value at risk forecasting.

One of the prediction models of shares expected return is one-factor Capital Asset Pricing Model (CAPM). Due to shortcomings of this model, other models such as Fama French and Carhart were proposed.Main purpose of this research is study the effect of financial data on the return of shares portfolio and the prediction power of Carhart model. To do this research, statistical society of Tehran Stock Exchange during the period 2007 to 2011 has been used which after screening, 150 remaining companies formed the basis for data collection.For this research three hypotheses were designed and tested using multi-variable time series regression and pair-test, these tests showed that growth stocks have more stock return.Also for add more reliability, the returns obtained with Carhart compared with real information. This comparison showed this information has no significant difference with real information.

Intellectual capital is known as a real capital and one of the most important assets of organizations. The purpose of this study was to evaluate the performance of Artificial Neural Networks in predicting intellectual capital efficiency in Accepted Companies in Tehran Stock Exchange. First, by using DEA Model and considering the value added coefficient variable of intellectual capital as a model input, and three variables including stock return, return on assets and return on equity as a model output variables, Intellectual capital efficiency of selected companies between 1385 to 1389 were investigated. At next step, multilayer Perceptron Neural Network Approach is used to predicting intellectual capital efficiency in companies. The results showed that Artificial Neural Network Model have high accuracy in predicting intellectual capital efficiency of accepted companies in Tehran Stock Exchange.

CANSLIM methods is a way to analysis available share in capital market as a combination and shares analysis of both methods of fundamental and technical. The aim of the present study is ranking the CANSLIM's indicators (include: percentage changes in quarterly Earning Per Share, percentage changes on Annual Earning Per Share, changes of management and new high prices «during a period of high prices for new experiences», free float, Leader or Demand, Institutional Sponsorship and total index changes) at the population studied level was the Tehran share exchanges. In this study needed data was collected with reference to available database software, financial statement of companies and analysis technical software, therefore review of using a multi-criteria decision-making methods like (SAW-TOPSIS) to share ranking with the CANSILM characteristics discussed and finally performance of ranking (based on yields), due to the index with negative values in problem and no solution with Entropy techniques, model has been developed so that it can accept negative values in weight.

Individual investors do not make decisions about how a fund's assets should be invested. They simply choose which fund to invest in based on its return, risk, fees and other factors. Among the factors considered in selecting investment Funds, performance of the fund is the most important one. So investors are looking for a tool in order to evaluate the performance of investment funds. The purpose of this study is comparing a new nonparametric model which also involves fund costs, with Sharpe model and two other modern models named Omega and Sortino. Therefore, the two hypotheses were defined and data related to the fund costs and the net present value of 22 stock funds and 19 fixed income funds were collected during 1391. The results using DEA show that there are significant differences between the nonparametric model, Sharp, Sortino and Omega models. At the end, by using nonparametric model, funds performance is measured and Fund performance evaluation results show that the performance of fixed-income funds have a higher of stock funds. Finally, the cost analysis was also performed for each of the funds.