Undergraduate - UnitETC3420 - Bayesian modelling and risk analysis

This unit entry is for students who completed this unit in 2014 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

print version

6 points, SCA Band 3, 0.125 EFTSL

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered, or view unit timetables.

Level	Undergraduate
Faculty	Faculty of Business and Economics
Organisational Unit	Department of Econometrics and Business Statistics
Offered	Clayton Second semester 2014 (Day)
Coordinator(s)	Dr Mike Callan

Synopsis

To provide a further grounding in mathematical and statistical techniques of particular relevance to insurance and financial work.

Outcomes

The learning goals associated with this unit are to:

explain the concepts of decision theory and apply them
calculate probabilities and moments of loss distributions both with and without limits and risk-sharing arrangements
construct risk models involving frequency and severity distributions and calculate the moment generating function and the moments for the risk models both with and without simple reinsurance arrangements
explain the concept of ruin for a risk model
explain the fundamental concepts of Bayesian statistics and use these concepts to calculate Bayesian estimators
describe the fundamental concepts of risk rating and apply them to simple experience rating systems
describe and apply techniques for analysing a delay (or run-off) triangle and projecting the ultimate position
explain the fundamental concepts of a generalised linear model (GLM), and describe how a GLM may apply
define and apply the main concepts underlying the analysis of time series models
explain the concepts of 'Monte Carlo' simulation using a series of pseudo-random numbers.