Abstract
P-thinned Gamma processes could be considered as a particular case of renewal processes which inter-renewal times are zero-inflated Gamma distributed. This paper considers also the difference between two, not obligatory identically distributed, processes which time intersections coincide in distribution with convolutions of zero-inflated Gamma distributed random variables. The idea comes from the Variance-Gamma model which is defined as Gamma time changed Wiener processes and is stochastically equivalent to a difference between two independent Gamma processes. The main properties and numerical characteristics of the resulting process are obtained. Simulation illustrates the theoretical results.
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Notes
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These measures of heavy-tailedness were introduced and partially investigated in Jordanova and Petkova [4].
References
Çinlar, E.: On a generalization of gamma processes. J. Appl. Probab. 17(2), 467–480 (1980)
Dickson, D.C.M., Waters, H.R.: Gamma processes and finite time survival probabilities. ASTIN Bull.: J. IAA 23(2), 259–272 (1993)
Dufresne, F., Gerber, H.U., Shiu, E.S.W.: Risk theory with the gamma process. ASTIN Bull.: J. IAA 21(2), 177–192 (1991)
Jordanova, P.K., Petkova, M.P.: Measuring heavy-tailedness of distributions. In: AIP Conference Proceedings, vol. 1910, no. 1, pp. 0600021–0600028 (2017)
Kapadia, C.H., Thomasson, R.L.: On estimating the parameter of a truncated geometric distribution by the method of moments. Ann. Inst. Stat. Math. 27(1), 269–272 (1975)
Kaishev, V.K., Dimitrova, D.S.: Dirichlet bridge sampling for the variance gamma process: pricing path-dependent options. Manag. Sci. 55(3), 483–496 (2009)
Kumar, A., Wylomanska, A., Poloczanski, R., Sundar, S.: Fractional Brownian motion time-changed by gamma and inverse gamma process. Phys. A: Stat. Mech. Appl. 468, 648–667 (2017)
Lawrance, A.J.: The innovation distribution of a gamma distributed autoregressive process. Scand. J. Stat. JSTOR 9, 234–236 (1982)
Lewis, P.A.W., McKenzie, E., Hugus, D.K.: Gamma processes. Stoch. Models 5(1), 1–30 (1989)
Madan, D.B., Seneta, E.: The variance gamma model for share market returns. J. Bus. 63, 511–524 (1990)
Madan, D.B., Carr, P.P., Chang, E.C.: The variance gamma process and option pricing. Rev. Financ. 2(1), 79–105 (1998)
R Development Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria
Seneta, E.: Fitting the variance-gamma model to financial data. J. Appl. Probab. 41(A), 177–187 (2004)
Spitzer, F.: Principles of Random Walk. Graduate Texts in Mathematics, vol. 34. Springer, New York (1976). https://doi.org/10.1007/978-1-4757-4229-9
Wolpert, R.L.: Stationary gamma processes (2016)
Acknowledgements
The authors were supported by the bilateral projects Bulgaria - Austria, 2016–2019, Feasible statistical modelling for extremes in ecology and finance, Contract number 01/8, 23/08/2017 and WTZ Project No. BG 09/2017.
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Jordanova, P., Stehlík, M. (2019). P-Thinned Gamma Process and Corresponding Random Walk. In: Dimov, I., Faragó, I., Vulkov, L. (eds) Finite Difference Methods. Theory and Applications. FDM 2018. Lecture Notes in Computer Science(), vol 11386. Springer, Cham. https://doi.org/10.1007/978-3-030-11539-5_33
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