ETC5351 - Modelling in finance and insurance

Leader(s): Professor Fima Klebaner and Professor Don Poskitt

Offered

Clayton First semester 2009 (Day)

Synopsis

Mathematical definition of options and other financial derivatives, probability models, mathematical models of random processes, applications, numerical methods, Monte Carlo methods.

Objectives

The learning goals associated with this unit are to:

• develop an understanding of the modern approach to evaluation of uncertain future payoffs
• develop an understanding of the concepts of arbitrage and fair games and their relevance to finance and insurance
• develop an understanding of concept of conditional expectation and martingales and their relation to pricing of financial derivatives
• develop an understanding of the random processes such as Random Walk, Brownian Motion and Diffusions and be able to apply them for modelling real life processes and risk models
• obtain skills to use Ito's formula
• develop the skills to price options by using the Binomial and Black-Scholes models
• ability to simulate the price process and obtain prices by simulation
• ability to formulate discrete time Risk Model in Insurance and use it for control of probabilities of ruin.

Assessment

Within semester assessment: 40%
Examination: 60%

Contact hours

3 one-hour lectures and 1 one-hour tutorial/practice class per week