3 research outputs found

    Forecasting the density of asset returns

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    In this paper we introduce a transformation of the Edgeworth-Sargan series expansion of the Gaussian distribution, that we call Positive Edgeworth-Sargan (PES). The main advantage of this new density is that it is well defined for all values in the parameter space, as well as it integrates up to one. We include an illustrative empirical application to compare its performance with other distributions, including the Gaussian and the Student's t, to forecast the full density of daily exchange-rate returns by using graphical procedures. Our results show that the proposed function outperforms the other two models for density forecasting, then providing more reliable value-at-risk forecasts.Density forecasting, Edgeworth-Sargan distribution, probability integral transformations, P-value plots, VaR

    Forecasting the density of asset returns

    Get PDF
    In this paper we introduce a transformation of the Edgeworth-Sargan series expansion of the Gaussian distribution, that we call Positive Edgeworth-Sargan (PES). The main advantage of this new density is that it is well defined for all values in the parameter space, as well as it integrates up to one. We include an illustrative empirical application to compare its performance with other distributions, including the Gaussian and the Studentā€™s t, to forecast the full density of daily exchange-rate returns by using graphical procedures. Our results show that the proposed function outperforms the other two models for density forecasting, then providing more reliable value-at-risk forecasts

    Higher-order moments in the theory of diversification and portfolio composition

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    This paper revisits the corner solution in classical portfolio choice theory in which risk-averse agents would all be optimally plungers rather than diversifiers. We examine the effect of higher-order moments of two-, three- and four-parameter density functions on the investor's decision to diversify in an expected utility framework. The empirical analysis provides estimates of four parametric and two semi-nonparametric densities for the S&P500 and concluded that allocation of all wealth in the risky asset would not have been optimal
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