- Code STAT3035
- Unit Value 6 units
- Offered by Rsch Sch of Finance, Actuarial Studies & App Stats
- ANU College ANU College of Business and Economics
- Course subject Statistics
- Areas of interest Actuarial Studies, Statistics
This course introduces the theory of compound Poisson processes, with a particular emphasis on their application to insurance portfolios (though their applicability in other areas is also noted)
Topics include: Modelling loss distributions; Skewed parametric distribution families; Method of moments, method of percentiles and maximum likelihood estimation; Pearson goodness-of-fit testing for distribution assessment; Truncated and censored data, including applications to reinsurance and policy excess schemes; Random sums, convolutions and compound distributions, particularly for modeling aggregate claim distributions; Normal and gamma approximations to compound distributions; Compound Poisson process theory, including applications to insurance portfolio surplus processes; Ultimate and finite-time ruin probabilities; Adjustment coefficients and optimal reinsurance contracts.
Upon successful completion, students will have the knowledge and skills to:
- Estimating using skewed distributions with and without the presence of censoring and truncation
- Aggregation of random quantities through compound distribution theory
- Compound Poisson process theory including approximation of boundary crossing probabilities as applied to calculating risk for insurance portfolios
- Typical assessment may include, but is not restricted to: a mid-semester exam and a final exam (null) [LO null]
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Students are expected to commit at least 10 hours per week to completing the work in this course. This will include at least 3 contact hours per week and up to 7 hours of private study time.
Requisite and Incompatibility
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- Student Contribution Band:
- Unit value:
- 6 units
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