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Using fuzzy random variables, a dynamic portfolio model with uncertainty is mentioned for object system. In this approach, the random property is numerated by stochastic expectation and the fuzzy property is also numerated by weights and mean functions. A value-at-risk is introduced to assess the risk of unfavorable paths in investment. Using dynamic programming and mathematical programming, the optimal...
Tracking Efficient (TE) method is applied in forming portfolio that has a similarity with the market index (represented here by LQ45 Stock Index). In forming a portfolio, TE uses historical data in certain period of time. Parameter ß is used as stock relative measure to market index and it shows stock level of return towards the market index. By choosing an appropriate ß, the portfolio will has high...
The rapid development of the world economy, various investment activities more frequently, how to measure whether the activities of an investment profits? So people began to explore how an investment portfolio in order to gain maximum benefit. Modern portfolio theory is about investment behavior under conditions of uncertainty theory of income, in 1959, Markowitz presents a normative model on portfolio...
Traditional VaR method has many defects in measuring portfolio risk, this paper modifies BDSS model and gets revised BDSS model -- La-VaR model based on relative price. For fitting the sequences of the rate of return and relative price, this paper adopts Gaussian-kernel function with good smoothness and Copula-kernel model to portray marginal distribution and correlation structure. Afterwards sequence...
As the amount of asset is decreased, this paper gives the characteristic of the efficient frontier under the sense of CVaR risk measurement, examines the economic implications and compares with the Mean-Variance boundary. We find that when CVaR is used as risk measurement, investors will become more stable, which is useful to risk decentralization and controlling.
The potential of machine learning to automate and control nonlinear, complex systems is well established. These same techniques have always presented potential for use in the investment arena, specifically for the managing of equity portfolios. In this paper, the opportunity for such exploitation is investigated through analysis of potential simple trading strategies that can then be meshed together...
Entropy can be as a measurement of the uncertainty and entropy optimization models can help investors to make decisions in the imperfect securities market. In this paper, the transaction costs will be added to the entropy optimization models including Mean-Entropy model and Mean-Cross-Entropy model, which make the models more rational and objective. The empirical study is done in twenty stocks of...
Stock market fluctuation is very challenging to investors. They have to make important decision regarding dollar and cent in uncertain environment. Therefore the study has introduced a model to present the uncertainty in stock returns. The model was derived by incorporating the MV model and the VBS fuzzy model. Using fuzzy approach, the study introduced an extended MV model. To investigate the effectiveness...
An improved model for portfolio selection based on particle swarm optimization with escape velocity (EVPSO) algorithm is proposed. Firstly, the predilection coefficient is introduced to the model to make the investor choose the invest project according to their preference and find the balance between the invest income and risk conveniently. Secondly, the EVPSO algorithm is applied to the model to...
We focus on the optimal portfolio selection problem where the objective function is expressed by mean Conditional value-at-risk (mean-CVaR). In general, since the density function of underlying risk factors is not available, and then the calculation of CVaR is rather difficult and can not derive the optimal solution. Therefore, we propose the mean-CVaR portfolio optimization model to deal with the...
Within the mean-variance model of Markowitz portfolio framework, we propose a betterment portfolio optimize model, the optimize model take the risk value as the tools of risk measurement and use the risk adjustment return as the optimization function, at the same time solve portfolio by simulated annealing genetic algorithm and validate the model's validity in reality by empirical study. The model...
This paper structured a joint distribution function between the assets rate of return by the adoption of the generalized ARCH and the generalized Pareto distribution model and the relevant structure function. Comparison of corelation hypothesis between different marginal distributions and assets rate of return was made to show the impact on portfolio selection performance. Empirical research shows...
It is well known fact that organizations diversifies and increase their product line locally and globally. In developing new products, project managers prefer to undertake related projects. As the projects are interdependent and inter related, there is a risk related interdependency. Information Systems(I.S) project selection decision is influenced by a number of factors like long-term plans, profit...
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