ETC3420 - Bayesian modelling and risk analysis
6 points, SCA Band 3, 0.125 EFTSL
Undergraduate Faculty of Business and Economics
Leader(s): Professor Don Poskitt
Offered
Clayton Second semester 2009 (Day)
Synopsis
To provide a further grounding in mathematical and statistical techniques of particular relevance to insurance and financial work.
Objectives
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.
Assessment
Within semester assessment: 30%
Examination (3 hours): 70%
Contact hours
Two 1-hour lectures and one 2-hour tutorial per week
Prerequisites
13 October 2017
16 December 2019