6 points, SCA Band 3, 0.125 EFTSL
Postgraduate - Unit
Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.
- Second semester 2018 (On-campus)
Students must have passed one of the following:or , and at least one of: , , , , , , or or obtain permission.
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 use of econometric methods to estimate Value at Risk; the modelling of transactions data using trade duration models and transaction-based volatility models; continuous time processes and the application of econometric techniques to option pricing; and the use of generalised method of moments in financial models.
The learning goals associated with this unit are to:
- critically evaluate alternative methods of modelling asset return volatility
- explain the role of volatility modelling in the measurement of risk and in the pricing of financial derivatives
- describe the role of continuous time stochastic processes in the pricing of financial derivatives
- evaluate econometric models for high frequency data
- evaluate the use of generalised method of moments in financial models.
Within semester assessment: 40% + Examination: 60%
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.
See also Unit timetable information