José Vicente Segura

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This paper presents two fuzzy portfolio selection models where the objective is to minimize the downside risk constrained so that a given expected return should be achieved. We assume that the rates of returns on securities are approximated as LR-fuzzy numbers of the same shape, and that the expected return and risk are evaluated by interval-valued means.(More)
Exponential procedures are widely used as forecasting techniques for inventory control and business planning. A number of modifications to the generalized exponential smoothing (Holt–Winters) approach to forecasting univariate time series is presented, which have been adapted into a tool for decision support systems. This methodology unifies the phases of(More)
In this paper we present a fuzzy ranking procedure for the portfolio selection problem. The uncertainty on the returns of each portfolio is approximated by means of a trapezoidal fuzzy number. The expected return and risk of the portfolio are then characteristics of that fuzzy number. A rank index that accounts for both expected return and risk is defined,(More)
In this paper, we carry out the numerical study of a fuzzy portfolio selection model where the objective is to minimize the downside risk and the rates of returns on securities are approximated by means of LR-fuzzy numbers of trapezoidal form. Data from 96 securities over 195 month are used to compare the selected portfolios with a simple utility function(More)
In this paper we present the results obtained by applying our automatic forecasting support system, named SIOPRED, over a data set of time series in a Forecasting Blind Competition. In order to apply our procedure for providing point forecasts it has been necessary to develop an interactive strategy for the choice of the suitable length of the seasonal(More)
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