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Forecasting Heavy‐Tailed Densities with Positive Edgeworth and Gram‐Charlier Expansions *
Author(s) -
Ñíguez TrinoManuel,
Perote Javier
Publication year - 2012
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/j.1468-0084.2011.00663.x
Subject(s) - skewness , gram , mathematics , edgeworth series , nonparametric statistics , econometrics , statistics , distribution (mathematics) , sample (material) , probability density function , economics , statistical physics , physics , mathematical analysis , biology , thermodynamics , genetics , bacteria
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.