Abstract

In this paper, we recall actuarial and financial applications of sums of dependent random variables that follow a non-Gaussian mean-reverting process and contemplate distribution approximations. Our work complements previous related studies restricted to lognormal random variables; we revisit previous approximations and suggest new ones. We then derive moment-based distribution approximations for random sums attuned to Asian option pricing and computation of risk measures of random annuities. Various numerical experiments highlight the speed-accuracy benefits of the proposed methods.

Publication Type:	Article
Additional Information:	© 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Publisher Keywords:	Mean reversion, non-Gaussian processes, moment-matching, Asian option valuation, stochastic annuities
Subjects:	H Social Sciences > HF Commerce Q Science > QA Mathematics
Departments:	Bayes Business School > Actuarial Science & Insurance

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