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.
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 |
Available under License Creative Commons Attribution Non-commercial No Derivatives.
Download (1MB) | Preview
Export
Downloads
Downloads per month over past year
Metadata
MetadataActions (login required)
Admin Login