FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT)
Year:2017 | Volume:8 | Issue:32 |Papers Count:14

The aim of this study is to propose a new method for portfolio optimization based on financial ratios. In this method, cross efficiency scores are produced from financial ratios, using Data Envelopment Analysis.Mathematical interpretation of these cross efficiency scores that allocates several score to each company is efficiency of company in probably future situations. Efficiency scores calculated based on proper financial ratios can be considered as financial strength. Thus cross efficiency scores produced from financial ratios, can be considered as potential financial strength. As future is not clear, potential financial strength can be presented in expectation and risk indices that are mean and variance of cross efficiencies. Fraction of expectation to risk for potential financial strengths can be used as a criterion for pairwise comparison of companies. Eigenvector associated with the biggest eigenvalue of pairwise comparison matrix reflects relative importance weights of companies. This paper proposes relative importance weights of companies as a basis for portfolio optimization. Based on sharp index Performance of proposed method is acceptable and better than marker portfolio and portfolio of one similar method.

Tehran Stock Exchange has not lived and somewhat inefficient. Mechanisms and rules governing this market is still not implemented in such a way that the quality of data and information provided by member companies to deliver optimal. and suffered not because of pricing errors. Probably the most attention of users of financial statements, the income statement is focused on the lowest row. In the eyes of most, profit accounting tool for making logical decisions In general indicates that measures the quality of earnings on excess stock returns based on Fama and French three-factor model, taking into account the trend of stock prices of listed companies on Tehran Stock Exchange, is impressive.In this study of four indicators to measure earnings quality, earnings stability, predictability of earnings, accruals quality and smoothing was used as the four hypothesis that the effect of these measures on additional efficiency gains from the difference between the real Return expected return achieved was measured and the results of the test showed that the hypothesis were accepted theories, the literature cited in the literature and theoretical framework also matched.

On all stock exchange of the world famous considerably derivatives are traded. Options are a patent for its owner, the most important are derivatives. The best economic tool management risk, the use of the option contract. It is obvious that at the conclusion of each contract, determining the price is the main element, Thus providing fair prices for securities is very important. In this study, the option pricing under fractional Black-Scholes is survived.The fractional Black-Scholes is based on fractional Brownian motion with hurst parameter. The Hurst exponent be associated with fractal dimension and self-similary as an indicator of long-term memory is used in the process of stock prices. The aim to provide a pricing formula for European options with transaction costs is an approximate answer fractional pricing equation with transaction costs by way of variational iteration method is checked. The transaction costs contain fixed costs, a cost proportional to the volume traded and a cost proportional to the value traded. Expected, the price of the European option decreases as the Hurst exponent increases.To achieve this goal, we estimate (Hurst parameter time series), on the real data to the desired result, the option price reduction reached. Comparing results show that the actual prices by fractional black-scholes model, is closer to the actual results.

The purpose of the portfolio management is the portfolio selection, the portfolio that acts as guidance to investors in order to achieve to maximum efficiency. In this study for portfolio selection, particle swarm optimization and Markowitz model are used and a comparison was made between them. Introducing the model to select a portfolio for investors who can make the right choice with evaluation of that model is of our objectives in this study. For this purpose, literature and various studies are verified and a set of measures with regard to the purpose of the research was collected. Among the companies listed on the Tehran Stock Exchange, 65 companies were selected as sample for the period 2009 to 2013 and were analyzed as a statistical sample. To analyze the data, first the data is collected and categorized in software EXCEL and after doing calculations were analyzed using MATLAB software. The results of this research showed that the particle swarm optimization has a fewer errors in the selection of optimal portfolio compared with Markowitz model. The most important suggestion for future research is to compare the particle swarm optimization with other models of optimization such as, colonial competition, meta-heuristic, arbitrage model and etc.

The several heuristic algorithms have been proposed for portfolio selection. One of these algorithms is based on spin glasses that have local searching and parallel processing properties. Because of the spin glass algorithms are actually based on Monte Carlo simulation such as simulated annealing (SA) and have low convergence speed against other method, yet composing with other methods such as Learning Automata (LA) and genetic algorithms have been considered. In this paper, one of the composing methods based on SA and Exteremal Optimization (EO) has been proposed, this algorithm select and change the low order spins with higher probability and take the state of all spins into the better situation. After a sufficient number of steps, the system reaches a highly correlated that almost all species have reached fitness above a certain threshold. This co-evolutionary activity gives rise to chain reactions and every fluctuation that rearrange major parts of the system, potentially making any configuration accessible. Therefore any fluctuations allow escaping from local minima and efficiently explore the configuration space. The experimental results show this method is powerful paradigm for finding ground state of spin glass and better than other methods such as SA and LA for solving portfolio selection problem.

Predicting future prices and consequently higher returns in financial markets has been one of the most important issues. In this study, the design of intelligent systems to buy and sell based on a complex model of support vector machine algorithm and theory of trend channel been discussed. To achieve the aim of this object, this study was performed in four main steps. In the first phase, range or limits of trend channel at different time intervals were extracted and these limits in the second phase of the experiment was predicted by the algorithm and Support Vector Machine. In the second phase in the range of channel which been predicted in period of experiment, sales strategy was defined and implemented. And in the third stage, returns from system designed with efficiency resulting from the use of buy and hold strategies were compared. In all selection criteria as a sample, Intelligent system performance based on the model of combined sales and support vector machine algorithm and theory of trend channel was better than the performance of buy and hold strategy

Portfolio selection is one of the most important issues of investment in the research using operational research techniques and taking into account the criteria, we extract the appropriate portfolio in Tehran Stock Exchange. Accordingly, on the basis of financial criteria in portfolio choice literature and experts to identify and prioritize using fuzzy metrics to gain weight. Then, using multi-criteria decision-making methods copras as a new method, stocks ranked. According to the results of three Mobarakeh Steel Company, propulsion and cement north respectively ranked first, second and third. Rank schemes are also used to compare the results of TOPSIS technique has also been used. According to the results of copras, Mobarakeh Steel Company first position and based on results of topsis, Machin Sazi Arak have achieved the first rank.

One of key aspects of foreign reserves management in central banks is to determine appropriate currency portfolio of foreign exchange reserves. In this study, optimal currency composition of four major reserve currency (including dollar, euro, pound and yen) in currency portfolio of the central bank of Iran analyzed. For this purpose, post modern portfolio approach and quarterly data during 2011 to 2014 used and efficient frontier of the central bank extracted as well. The results indicate that maximum share of dollar, euro and yen in the strategic currency reserves portfolio of the central bank is respectively 35, 29 and 48 percent. Accordingly, if share of the currencies in the currency portfolio was more than these figures, the value of reserves is reduced. Furthermore, pound is a risky currency, so the central bank to hold the currency, mainly should act based on his transaction needs.

In recent years, financial markets have faced with high volatility so that the unreliability caused by this, has made investors to be concerned. Therefore, volatility modeling and prediction is taken into consideration in various researches and practical issues. In this regard, access to high frequency data creates a new field in volatility modeling and return prediction of financial assets. In this Thesis using high frequency data, the volatility modeling has been performed by HAR-RV family models, and the effect of adding jump component to volatility prediction efficiency of index is studied in Tehran Securities Exchange. The results of modeling and prediction suggest that the forecast error is decreased by adding jump component into model, and also the separation of jump and continuous components of realized volatility is effective on performance improvement.

The main aim of the present study is to examine the effect of financial leverage on operating liquidity in listed companies of Tehran Stock Exchange. Statistical population of the present study is consisted of companies listed on Tehran Stock Exchange during the time period of 2008 to 2014 and sample volume is equal to 118 companies by using screening method and after the elimination of outlaying observations. In this study, financial leverage was taken as independent variable in order to study its effect on current ratio, cash flow conversion cycle margin of the operational cash flow and return on assets. In this study, in which panel data with fixed and random effects were used, results obtained from firm data analysis by using multivariate regression at 95% confidence level indicated that financial leverage has a direct effect on return on assets. It was also indicated that financial leverage has a reverse effect on current ratio and cash flow conversion cycle. In addition financial leverage did not affect on the margin of the operational cash flow.

Risk forecasting for future periods plays an important role in making the right decisions of managers and financial activists to invest in companies and institutions. On the other hand wrong decisions of commercial managers can have undesirable consequences for their organizations. Therefore the most important issues for investors is forecasting risk in future periods. The importance of this issue was caused us to forecast Value at Risk (VaR) in one step ahead by using the exponential smoothing family for two normal and t-student distributions with confidence levels of 95%, 97. 5% and also 99% in this research. Previously the classic method is commonly used to forecast future periods of VaR, but in this research the family of exponential smoothing models is used, which process data by considering trend and doing so online monitoring. In order to validate the model, the proposed model has been compared with the classic method by using backtesting. The results confirms the more accurate forecasting of proposed method in normal distribution with confidence levels of 97. 5%, and 99% and also in t-student distribution with confidence levels of 97. 5%, 99%.

this study, using gold coins spot price returns, in the period from 2008 to 2016, estimates IME gold coin futures contracts Initial margin, by Value at Risk and ConditionalValue at Risk (CVAR) approaches. It use variance-covariance modeles, based on normal and T-student distributions, general pareto distribution and adaptive GPD models fore estimating initial margin requerment for futures contracts open positions. Fore VaR moles backtesting, it applies Christoffersen conditonal coverage liklihood ratio(LRcc) test and lopez and Blanco-Ihle loss functions. MAE and RMSE loss functions have been used for Conditional Value at Risk (CVAR) models Evalution. The paper finds that all models have been underperforming in low confidence level and Variance-covariance models based on T-student Distribution and adaptive GPD has outperformed the other models that support the fat tailed nature of gold coin spot price data historical distribution.

In finance, optimal portfolio selection, play's a crucial role for investor’ s decisions. In practical cases the problem of optimal portfolio selection has some challenges. In a cases stocks are affected by various uncertain factors therefore, it is impossible to simulate all of them properly. In this study, previous investigation about select and optimization of portfolio has been illustrated. For this purpose, credibility theory for calculating statistics moments such as Expected value, semi-skewness have been used. Also, the value at risk and Uncertainty is used for modeling in fuzzy Environment. For solving the model Matlab software run for solving Non-dominated sorting genetic algorithm "NSGA-II". And as result some of optimal pareto-front solutions have been obtained which were listed as optimal solution. To conclude Random portfolios has been created in order to compare with defined portfolios. the result indicate, defined models has more level of Satisfactory goals rather than Random portfolios.

Current study, has explores the VAR and ES in the Tehran Stock Exchange (TSE) by using the Extreme Value Theory (block maxima and GPD). Earlier estimates of the preliminary findings of the analysis that uses statistics, Empirical Distribution Function, Mean Excess Function and QQ plot, Pareto and heavy-tailed behavior were found data. To estimate the optimal threshold value, we have Mean Excess Function and hill plot applied. To estimate the optimal threshold value, Mean Excess Function and Hill plot use the statistics mentioned for the positive and negative returns, the threshold value for GPD models are about. /75 And. /60 have provided. Comparing the estimated residual value model classic extreme (monthly, quarterly, six month and one year) and the GPD, concluded the optimal performance GPD calculated on the value of extreme block which is highly sensitive to the choice of the period. Finally, to estimate VAR and ES, we GPD model demonstrated that a better performance was applied. The results showed that VAR and ES should not be the dominant financial risk management. In other words, dependence on individual risk scale for ignoring the problem will create portfolio risk information. So to contain the missing information by VAR and ES, it is essential that the various aspects of the distribution of losses / profits look like heavy-tailed.