Forecasting Heavy-Tailed Densities with Positive Edgeworth and Gram-Charlier Expansions

被引:23
|
作者
Niguez, Trino-Manuel [1 ]
Perote, Javier [2 ]
机构
[1] Univ Westminster, Westminster Business Sch, Dept Econ & Quantitat Methods, London NW1 5LS, England
[2] Univ Salamanca, Dept Econ, Salamanca 37007, Spain
关键词
C16; C53; G12; TIME-SERIES; VOLATILITY; MODELS; RISK;
D O I
10.1111/j.1468-0084.2011.00663.x
中图分类号
F [经济];
学科分类号
02 ;
摘要
This article presents a new semi-nonparametric (SNP) density function, named Positive Edgeworth-Sargan (PES). We show that this distribution belongs to the family of (positive) Gram-Charlier (GC) densities and thus it preserves all the good properties of this type of SNP distributions but with a much simpler structure. The in- and out-of-sample performance of the PES is compared with symmetric and skewed GC distributions and other widely used densities in economics and finance. The results confirm the PES as a good alternative to approximate financial returns distribution, specially when skewness is not severe.
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页码:600 / 627
页数:28
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