Likelihood-based risk estimation for variance-gamma models

DOI10.1007/s10260-017-0393-zzbMath1387.62108OpenAlexW2689453535MaRDI QIDQ1742843

Maria Michela Dickson, Marco Bee, Flavio Santi

Publication date: 12 April 2018

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: http://www.economia.unitn.it/alfresco/download/workspace/SpacesStore/75993e9b-9573-4a40-a2f7-c3b69e90499d/DEM2017_03.pdf

zbMATH Keywords

maximum likelihoodnumerical optimizationrisk estimationvariance-gamma distributionmulticycle EM algorithm

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70) Point estimation (62F10)

Related Items

Modeling right-skewed financial data streams: a likelihood inference based on the generalized Birnbaum-Saunders mixture model, VG_codes

Uses Software

• R
• ghyp
• fGarch
• QRM
• VarianceGamma
• Rugarch

Cites Work

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• The Variance Gamma Process and Option Pricing