Overview

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

Offerings

S1-01-CLAYTON-ON-CAMPUS
S2-01-CLAYTON-ON-CAMPUS

Contacts

Chief Examiner(s)

Dr Fima Klebaner

Notes

IMPORTANT NOTICE:
Scheduled teaching activities and/or workload information are subject to change in response to COVID-19, please check your Unit timetable and Unit Moodle site for more details.

Learning outcomes

On successful completion of this unit, you should be able to:
1.

understand the modern approach to evaluation of uncertain future payoffs

2.

understand the concepts of arbitrage and fair games and their relevance to finance and insurance

3.

understand the concepts of conditional expectation and martingales and their relation to pricing of financial derivatives

4.

understand 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

5.

use Ito's formula

6.

price options by using the Binomial and Black-Scholes models

7.

simulate the price process and obtain prices by simulation

8.

formulate discrete time Risk Model in Insurance and use it for control of probabilities of ruin.

Teaching approach

Active learning
Peer assisted learning

Assessment

1 - Within semester assessment
2 - Examination

Scheduled and non-scheduled teaching activities

Applied sessions
Lectures

Workload requirements

Workload