Fitting a Pareto-Normal-Pareto distribution to the residuals of financial data

SummaryThe Pareto-Normal-Pareto (PNP) distribution assumes that, for log returns of financial series, the innovations are normally distributed between two threshold values with Pareto tails below and above the respective thresholds. These threshold values can be estimated by maximum likelihood estim...

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Bibliographic Details
Published in:	Computational statistics Vol. 18; no. 3-4; pp. 477 - 491
Main Authors:	Ellis, Suria, Steyn, Faans, Venter, Hennie
Format:	Journal Article
Language:	English
Published:	Heidelberg Springer Nature B.V 01-09-2003
Subjects:	Computer simulation Economic models Fittings Mathematical analysis Maximum likelihood estimates Maximum likelihood estimation Monte Carlo methods Monte Carlo simulation Pareto optimality Statistics Stock exchanges Thresholds
Online Access:	Get full text
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Summary:	SummaryThe Pareto-Normal-Pareto (PNP) distribution assumes that, for log returns of financial series, the innovations are normally distributed between two threshold values with Pareto tails below and above the respective thresholds. These threshold values can be estimated by maximum likelihood estimation (MLE). Monte Carlo simulations of normal, as well as heavy tailed error distributions, are used to compare the methods using this distribution with other methods to calculate Value-at-Risk (VaR) and Expected Shortfall (ESf). It is also applied to South African stock exchange data.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0943-4062 1613-9658
DOI:	10.1007/BF03354611