City Research Online

Moment-matching approximations for stochastic sums in non-Gaussian Ornstein-Uhlenbeck models

Brignone, R., Kyriakou, I. ORCID: 0000-0001-9592-596X & Fusai, G. ORCID: 0000-0001-9215-2586 (2020). Moment-matching approximations for stochastic sums in non-Gaussian Ornstein-Uhlenbeck models. Insurance: Mathematics and Economics, 96, pp. 232-247. doi: 10.1016/j.insmatheco.2020.12.002

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
SWORD Depositor:
[thumbnail of main.ime.v3.pdf]
Preview
Text - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (1MB) | Preview

Export

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Downloads

Downloads per month over past year

View more statistics

Actions (login required)

Admin Login Admin Login