- Code STAT3035
- Unit Value 6 units
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:
- Perform estimation using skewed distributions with and without the presence of censoring and truncation;
- Aggregate random quantities through compound distribution theory; and,
- Use 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: exams, assignments, quizzes, presentations and other assessment as appropriate. (100) [LO 1,2,3]
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Students are expected to commit 130 hours of work in completing this course. This includes time spent in scheduled classes and self-directed study time.
Requisite and Incompatibility
Information about the prescribed textbook will be available via the Class Summary.
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
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- Unit value:
- 6 units
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