Stochastic modelling and optimization with applications to actuarial models
This thesis is devoted to Ruin Theory which sometimes referred to the collective ruin theory. In Actuarial Science, one of the most important problems is to determine the finite time or infinite time ruin probability of the risk process in an insurance company. To treat a realistic economic situati...
| Main Author: | |
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
| Published: |
2012
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| Online Access: | https://eprints.nottingham.ac.uk/12702/ |
| _version_ | 1848791563056971776 |
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| author | Li, Mengdi |
| author_facet | Li, Mengdi |
| author_sort | Li, Mengdi |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This thesis is devoted to Ruin Theory which sometimes referred to the collective ruin theory. In Actuarial Science, one of the most important problems is to determine the finite time or infinite time ruin probability of the risk process in an insurance company.
To treat a realistic economic situation, the random interest factor should be taken into account. We first define the model with the interest rate and approximate the ruin probability for the model by the Brownian motion and develop several numerical methods to evaluate the ruin probability.
Then we construct several models which incorporate possible investment strategies. We estimate the parameters from the simulated data. Then we find the optimal investment strategy with a given upper bound on the ruin probability.
Finally we study the ruin probability for our class of models with the Heavy- Tailed claim size distribution. |
| first_indexed | 2025-11-14T18:30:30Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-12702 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:30:30Z |
| publishDate | 2012 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-127022025-02-28T11:20:53Z https://eprints.nottingham.ac.uk/12702/ Stochastic modelling and optimization with applications to actuarial models Li, Mengdi This thesis is devoted to Ruin Theory which sometimes referred to the collective ruin theory. In Actuarial Science, one of the most important problems is to determine the finite time or infinite time ruin probability of the risk process in an insurance company. To treat a realistic economic situation, the random interest factor should be taken into account. We first define the model with the interest rate and approximate the ruin probability for the model by the Brownian motion and develop several numerical methods to evaluate the ruin probability. Then we construct several models which incorporate possible investment strategies. We estimate the parameters from the simulated data. Then we find the optimal investment strategy with a given upper bound on the ruin probability. Finally we study the ruin probability for our class of models with the Heavy- Tailed claim size distribution. 2012-07-19 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/12702/1/resubmit_version_6_June-4.pdf Li, Mengdi (2012) Stochastic modelling and optimization with applications to actuarial models. PhD thesis, University of Nottingham. |
| spellingShingle | Li, Mengdi Stochastic modelling and optimization with applications to actuarial models |
| title | Stochastic modelling and optimization with applications to actuarial models |
| title_full | Stochastic modelling and optimization with applications to actuarial models |
| title_fullStr | Stochastic modelling and optimization with applications to actuarial models |
| title_full_unstemmed | Stochastic modelling and optimization with applications to actuarial models |
| title_short | Stochastic modelling and optimization with applications to actuarial models |
| title_sort | stochastic modelling and optimization with applications to actuarial models |
| url | https://eprints.nottingham.ac.uk/12702/ |