ETC3510 - 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

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

Prerequisites

ETC1000

Prohibitions

ETC4351, MTH3251