Forecasting the Density of Asset Returns
affiliation not provided to SSRN
Universidad Rey Juan Carlos - Department Economia; University of Salamanca
LSE STICERD Research Paper No. EM479
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.
Number of Pages in PDF File: 30
JEL Classification: C16, C53, G12
Date posted: July 21, 2008
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