STAT8036 Credibility Theory

Offered By	School of Finance, Actuarial Studies & Appl Stats
Academic Career	Graduate Coursework
Course Subject	Statistics
Offered in	Second Semester, 2011 and Second Semester, 2012
Unit Value	6 units
Course Description	This course covers the fundamental concepts of: Bayesian statistics, including estimation, prediction, hypothesis testing, and decision theory; time series analysis, including estimation and prediction based on ARIMA models; credibility theory, including limited fluctuation credibility theory and the Buhlmann-Straub model; several run-off techniques for estimating an outstanding claims reserve; and Monte Carlo techniques, including the inverse transformation method, the polar method, and Monte Carlo integration.
Learning Outcomes	Upon successful completion of the requirements for this course, students will be able to: Explain the fundamental concepts of Bayesian statistics and use these concepts to calculate Bayesian estimators (including credibility estimators). Define and apply the main concepts underlying the analysis of time series models. Describe and apply techniques for analysing a delay (or run-off) triangle and projecting the ultimate position. Explain and apply the concepts of “Monte Carlo” simulation using a series of pseudo-random numbers.
Indicative Assessment	Mid-Semester Examination (30%) Final Examination (70%) Details about assessment may change during the first two weeks of semester. Please ensure that you check with your lecturer or tutor about any changes. Changes to the assessment schedule will be posted to the Wattle site.
Workload	Students taking this course are expected to commit at least 10 hours a week to completing the work. This will include: 3 hours a week: lectures 1 hour a week: tutorials 6 hours a week: reading, and exam/tutorial preparation
Course Classification(s)	AdvancedAdvanced courses are designed for students having reached 'first degree' level of assumed knowledge, which provide a deep understanding of contemporary issues; or 'second degree' and higher levels of knowledge; or for transition to research training programs. and SpecialistSpecialist courses are designed for students having reached 'first degree' level of assumed knowledge, which provide for the acquisition of specialist skills; or 'second degree' and higher level of knowledge; or for transition to research training programs; or knowledge associated with professional accreditation.
Areas of Interest	Actuarial Studies
Eligibility	At least an average of 65% (or equivalent) in the final two years of an Australian undergraduate degree with at least two years of university level statistical and mathematical study including calculus and linear algebra, as well as mathematical statistics and linear regression theory.
Prescribed Texts	None.
Technology Requirements	No computing is required for this course. However, you will need a scientific calculator.
Programs	Graduate Certificate in Actuarial Studies, Graduate Certificate in Actuarial Studies, Master of Actuarial Statistics, Master of Actuarial Studies, Master of Applied Statistics, Master of Applied Statistics, Master of Actuarial Statistics, and Master of Actuarial Studies
Other Information	This course, together with STAT3035 (Risk Theory), constitutes Subject CT6 of the Institute of Actuaries of Australia. To get an exemption from the Institute, you need to get an average of at least 60% for these two courses.
Academic Contact	Dr Borek Puza

The information published on the Study at ANU 2011 website applies to the 2011 academic year only. All information provided on this website replaces the information contained in the Study at ANU 2010 website.