Courses & Units
Applied Quantitative Finance BEA653
May be taken as an elective in other postgraduate courses only with permission of the Master of Finance course coordinator.
Introduction
There are two main objectives in applied quantitative finance. First, is to understand how asset prices behave. Future asset prices are uncertain and, therefore, must be described by a probability distribution. This means that statistical and econometric methods can be applied to investigate price processes occurring over time. Usually one builds a model, which is a detailed description of how successive observations are determined. The second objective is to use our knowledge of asset pricing behaviour to reduce risk or make better decisions. The focus in this unit will be on practical applications rather than formal proofs of theorems, using computer based software (EViews) to investigate the different econometric techniques for estimation and inference.
Summary
| Unit name | Applied Quantitative Finance |
|---|---|
| Unit code | BEA653 |
| Credit points | 12.5 |
| College/School | College of Business & Economics Tasmanian School of Business and Economics |
| Discipline | Finance |
| Coordinator | Mr Vladimir Volkov |
| Delivered By | University of Tasmania |
| Level | Postgraduate |
Availability
This unit is currently unavailable.
Note
Please check that your computer meets the minimum System Requirements if you are attending via Distance/Off-Campus.
Units are offered in attending mode unless otherwise indicated (that is attendance is required at the campus identified). A unit identified as offered by distance, that is there is no requirement for attendance, is identified with a nominal enrolment campus. A unit offered to both attending students and by distance from the same campus is identified as having both modes of study.
* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).
Unit census dates currently displaying for 2023 are indicative and subject to change. Finalised census dates for 2023 will be available from the 1st October 2022. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
Learning Outcomes
- Define and explain the properties that characterise financial data and the techniques for analysing cross-sectional data.
- Analyse and model the short-run relationships in financial time series data.
- Analyse and model the long-run relationships among financial time series data
- Apply econometric modelling and interpret the results using financial data.
Fee Information
| Field of Education | Commencing Student Contribution 1,3 | Grandfathered Student Contribution 1,3 | Approved Pathway Course Student Contribution 2,3 | Domestic Full Fee 4 |
|---|---|---|---|---|
| not applicable |
1 Please refer to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on eligibility for FEE-HELP.
If you have any questions in relation to the fees, please contact UConnect or more information is available on StudyAssist.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
Requisites
Prerequisites
(BEA681 - Data and Business Decision Making OR BEA654 - Data and Business Decision Making OR BEA674 - Data and Business Decision Making)Teaching
| Assessment | Mid-Semester Test (Online) (20%)|Workshop Submissions (30%)|Final Exam (50%) |
|---|---|
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
You will need the following text: Brooks, C. (2014). Introductory Econometrics for Finance. Cambridge: Cambridge University Press. 3rd edn. Software: Eviews 8 or newer version. |
|---|---|
| Recommended | Martin, V. and Hurn, A., and Harris, D. (2012). Econometric modelling with time series: specification, estimation and testing. Cambridge: Cambridge University Press. Franses, P. H. & D.V. Dijk (2000), Nonlinear Time Series Models in Empirical Finance. Cambridge, Cambridge University Press. | Links | Booktopia textbook finder |
The University reserves the right to amend or remove courses and unit availabilities, as appropriate.