Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.10300 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866915155262046208 |
|---|---|
| author | Goudenège, Ludovic Molent, Andrea Zanette, Antonino |
| author_facet | Goudenège, Ludovic Molent, Andrea Zanette, Antonino |
| contents | In this paper, we propose a novel methodology for pricing equity-indexed annuities featuring cliquet-style payoff structures and early surrender risk, using advanced financial modeling techniques. Specifically, the market is modeled by an equity index that follows an uncertain volatility framework, while the dynamics of the interest rate are captured by the Hull-White model. Due to the inherent complexity of the market dynamics under consideration, we develop a numerical algorithm that employs a tree-based framework to discretize both the interest rate and the underlying equity index, enhanced with local volatility optimization. The proposed algorithm is compared with a machine learning-based algorithm. Extensive numerical experiments demonstrate its high effectiveness. Furthermore, the numerical framework is employed to analyze key features of the insurance contract, including the delineation of the optimal exercise region when early surrender risk is incorporated. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_10300 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Robust Pricing of Equity-Indexed Annuities under Uncertain Volatility and Stochastic Interest Rate Goudenège, Ludovic Molent, Andrea Zanette, Antonino Pricing of Securities In this paper, we propose a novel methodology for pricing equity-indexed annuities featuring cliquet-style payoff structures and early surrender risk, using advanced financial modeling techniques. Specifically, the market is modeled by an equity index that follows an uncertain volatility framework, while the dynamics of the interest rate are captured by the Hull-White model. Due to the inherent complexity of the market dynamics under consideration, we develop a numerical algorithm that employs a tree-based framework to discretize both the interest rate and the underlying equity index, enhanced with local volatility optimization. The proposed algorithm is compared with a machine learning-based algorithm. Extensive numerical experiments demonstrate its high effectiveness. Furthermore, the numerical framework is employed to analyze key features of the insurance contract, including the delineation of the optimal exercise region when early surrender risk is incorporated. |
| title | Robust Pricing of Equity-Indexed Annuities under Uncertain Volatility and Stochastic Interest Rate |
| topic | Pricing of Securities |
| url | https://arxiv.org/abs/2502.10300 |