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This paper presents the partial results obtained at the doctoral work titled ADAPTIVE HYBRID SYSTEM FOR THE VALUE AT RISK ESTIMATION ON PORTFOLIOS, where different AI techniques are used. This expert system tries to predict the portfolio variability with two o more assets, where the ROI and the risk rate are vital to define the efficient frontier market proposed by Markowitz.
This paper presents the partial results obtained at the doctoral work titled ADAPTIVE HYBRID SYSTEM FOR THE VALUE AT RISK ESTIMATION ON PORTFOLIOS, where different AI techniques are used. This expert system tries to predict the portfolio variability with two o more assets, where the ROI and the risk rate are vital to define the efficient frontier market proposed by Markowitz.
In this paper, we propose M-CVaR portfolio selection model under nonlinear transaction costs and minimum trading volumes. We use a quadratic function to approximate origin transaction costs function, set genetic algorithms, and analyse the M-CVaR model by real financial data. A series of numerical experiments shows that the model is reasonable and the algorithm is efficient. Further, we give that...
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...
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