演讲题目：

1.EXPLAINING YOUNG MORTALITY

2.Multivariate Ruin Probabilities under Regular Variation Risks

3.Optimal Reinsurance and Partial Hedging

摘要：

1.Stochastic modeling of mortality rates focuses on fitting linear models to logarithmically adjusted mortality data from the middle orlate ages. Whilst this modeling enables insurers to project mortality rates and hence price mortality products it does not provide good fit for younger aged mortality. Mortality rates below the early 20’s are important to model as they give an insight into estimates of the cohort effect for more recent years of birth. It is also important given the cumulative nature of life expectancy to be able to forecast mortality improvements at all ages. When we attempt to fit existing models to a wider age range, 5-89, rather than 20-89 or 50-89, their weaknesses are revealed as the results are not satisfactory. The linear innovations in existing models are not flexible enough to capture the non-linear profile of mortality rates that we see at the lower ages. In this paper we modify an existing 4 factor model of mortality to enable better fitting to a wider age range, and using data from seven developed countries our empirical results show that the proposed model has a better fit to the actual data, is robust, and has good forecasting ability.

2.In this paper, we consider four common types of ruin probabilities for a discrete-time multivariate risk model, where the insurer is assumed to be exposed to a vector of net losses resulting from various lines of businesses over each period. By assuming a large initial capital for the risk model and a multivariate regularly varying distribution for the net loss vector, we establish some interesting asymptotic estimates for those ruin probabilities via the upper tail dependence function of the net loss vector. Our results insightfully characterize how the dependence structure among the net loss vector can aect the ruin probabilities in the asymptotic sense, and more importantly, from our main results, explicit asymptotic estimates for those ruin probabilities can be obtained by specifying a copula for the dependence structure among the net loss vector.

3. In actuarial science, the insurers often use reinsurance as one of the tools to control their risk, where the insurer will incur an additional cost in terms of reinsurance premium when it cedes part of its loss to a reinsurer. Obviously, the reinsurance premium depends on the size of the ceded loss, and therefore, from the perspective of the insurer, there is a tradeoff between the ceded loss and reinsurance premium budget and this leads to the problem of optimal reinsurance. Often, the problem is resolved through a minimization problem over a risk measure (such as VaR and CTE) of the insurer’s total risk exposure subject to a reinsurance premium budget. In finance, how to hedge a contingent claim is one of the central problems, and it is usually too costly to achieve a perfect hedging. A more practical and desirable strategy is to resort to the partial hedging, which leaves some scenarios to have a positive payout. Clearly, from the hedger’s angle, there is also a tradeoff between the hedged loss and hedging cost the hedger is willing to spend. In this talk, I will address the connection and difference between the optimal reinsurance and the optimal partial hedging

problems. This talk is based on joint work with Jianfa Cong and Ken Seng Tan.

演讲人：

1.YOUWEI LI （Queen's University Belfast - School of Management）

2.张奕教授（浙江大学）

3.Dr. Chengguo Wen (University of Waterloo)

报告时间：

1.2012年7月7日9:30-10:20

2.2012年7月7日10:20-11:10

3.2012年7月7日11:10-12:00

报告地点：中央财经大学中国精算研究院会议室

欢 迎 各 位 老 师 同 学 参 加！

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