Overview

This unit introduces students to a range of advanced, current techniques used in analysing financial data. Topics covered include the analysis of the time series and distributional features of financial data; the use of stochastic volatility and realised volatility models to capture time-varying volatility, including long memory in volatility; the … For more content click the Read More button below.

Offerings

S2-01-CLAYTON-ON-CAMPUS

Contacts

Chief Examiner(s)

Professor Jiti Gao

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.

critically evaluate alternative methods of modelling asset return volatility

2.

explain the role of volatility modelling in the measurement of risk and in the pricing of financial derivatives

3.

describe the role of continuous time stochastic processes in the pricing of financial derivatives

4.

evaluate econometric models for high frequency data

5.

evaluate the use of generalised method of moments in financial models.

Teaching approach

Active learning

Assessment

1 - Within semester assessment
2 - Examination

Scheduled and non-scheduled teaching activities

Workshops

Workload requirements

Workload

Learning resources

Required resources