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Risk Theory with the Generalized Inverse Gaussian Lévy Process

Published online by Cambridge University Press:  17 April 2015

Manuel Morales*
Affiliation:
Department of Mathematics and Statistics, York University, N520 Ross Building, 4700 Keele St., Toronto, Ontario M3J 1P3 – CANADA, E-mail: mmorales@yorku.ca, Phone: (416) 736 2100 ext 33768
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Abstract

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Dufresne et al. (1991) introduced a general risk model defined as the limit of compound Poisson processes. Such model is either a compound Poisson process itself or a strictly increasing Lévy process. Their construction is based on a non-negative non-increasing function Q that governs the jumps of the process. This function, it turns out, is the tail of the Lévy measure of the process. We discuss an illustration of their model using a generalized Inverse Gaussian (GIG) Lévy process. This increasing Lévy process has the gamma and the inverse Gaussian process as particular cases. Although mathematically more complex, the GIG Lévy process keeps some of the nice properties of the simpler gamma process.

Type
Articles
Copyright
Copyright © ASTIN Bulletin 2004

References

Abramowitz, M. and Stegun, I. (1970) Handbook of Mathematical Functions With Formulas, Graphs and Mathematical Tables. Google Scholar
Asmussen, S. (2000) Ruin Probabilities. Advanced Series on Statistical Science and Applied Probability. World Scientific. CrossRefGoogle Scholar
Barndorff-Nielsen, O.E. and Halgreen, C. (1977) Infinite Divisibility of the Hyperbolic and Generalized Inverse Gaussian Distributions. Zeitschrift für Wahrscheinlichkeitstheorie und verwandte Gebiete 38, 439455.CrossRefGoogle Scholar
Barndorff-Nielsen, O.E., Mikosh, T. and Resnick, S., editors (2001) Lévy Processes-Theory and Applications. Birkäuser.Google Scholar
Barndorff-Nielsen, O.E. and Shephard, N. (2001) Non Gaussian OU Based Models and Some of their Uses in Financial Economics. Journal of the Royal Statistical Society. B. 63. Bertoin, J. (1996) Lévy Processes. Cambridge Tracts in Mathematics. 121. Cambridge University Press.Google Scholar
Cai, J. and Garrido, J. (1998) Aging Properties and Bounds for Ruin Probabilities and Stop-loss Premiums. Insurance: Mathematics and Economics 23, 3343.Google Scholar
Chaubey, Y., Garrido, J. and Trudeau, S. (1998) On the Computation of Aggregate Claims Distributions: Some New Approximations. Insurance: Mathematics and Economics 23, 215230.Google Scholar
Dufresne, F. and Gerber, H.U. (1989) Three Methods to Calculate the Probability of Ruin. ASTIN Bulletin 19, 7190.CrossRefGoogle Scholar
Dufresne, F., Gerber, H.U. and Shiu, E.S.W. (1991) Risk Theory with the Gamma Process. ASTIN Bulletin 21(2), 177192.CrossRefGoogle Scholar
Feller, W. (1971) An Introduction to Probability Theory and Its Applications II. Wiley, New York. Google Scholar
Grandell, J. (1991) Aspects of Risk Theory. Springer Series in Statistics. Springer-Verlag. CrossRefGoogle Scholar
Jacod, J. and Shiryaev, A. (1987) Limit Theorems for Stochastic Processes. Springer-Verlag.CrossRefGoogle Scholar
Jørgensen, B. (1982) Statistical Properties of the Generalized Inverse Gaussian Distribution. Lecture Notes in Statistics. (9). Springer. CrossRefGoogle Scholar
Morales, M. (2003) Generalized Risk Processes and Lévy Modeling in Risk Theory. A Ph.D. thesis in the Department of Mathematics and Statistics. Concordia University. Montréal, Canada. Google Scholar
Morales, M. and Schoutens, W. (2003) A Risk Model Driven by Lévy Processes. Applied Stochastic Models in Business and Industry 19, 147167.CrossRefGoogle Scholar
Sato, K.I. (1999) Lévy Processes and Infinitely Divisible Distributions. Cambridge University Press. Google Scholar
Schoutens, W. (2003) Lévy Processes in Finance: Pricing Financial Derivatives, Wiley. CrossRefGoogle Scholar
Yang, H. and Zhang, L. (2001) Spectrally Negative Lévy Processes with Applications in Risk Theory. Advances in Applied Probability 33(1), 281291.Google Scholar