Moment-matching approximations for stochastic sums in non-Gaussian Ornstein-Uhlenbeck models
    
    Brignone, R., Kyriakou, I.  ORCID: 0000-0001-9592-596X & Fusai, G.
ORCID: 0000-0001-9592-596X & Fusai, G.  ORCID: 0000-0001-9215-2586  (2021).
    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
ORCID: 0000-0001-9215-2586  (2021).
    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 > Faculty of Actuarial Science & Insurance | 
| SWORD Depositor: | 
Available under License Creative Commons Attribution Non-commercial No Derivatives.
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