Courses & Units

Applied Quantitative Finance BEA653

Hobart

Note:

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
Available as student elective? No
Delivered By Delivered wholly by the provider
Level Postgraduate

Availability

Location Study period Attendance options Available to
Hobart Semester 2 On-Campus Off-Campus International International Domestic Domestic

Key

On-campus
Off-Campus
International students
Domestic students
Note

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Key Dates

Study Period Start date Census date WW date End date
Semester 2 12/7/2021 10/8/2021 30/8/2021 17/10/2021

* 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 (see withdrawal dates explained for more information).

Unit census dates currently displaying for 2021 are indicative and subject to change. Finalised census dates for 2021 will be available from the 1st October 2020. Note census date cutoff is 11.59pm AEST (AEDT during October to March).

About Census Dates

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.
Field of Education Commencing Student Contribution 1 Grandfathered Student Contribution 1 Approved Pathway Course Student Contribution 2 Domestic Full Fee
010103 $493.00 $493.00 not applicable $2,702.00
  • Available as a Commonwealth Supported Place
  • HECS-HELP is available on this unit, depending on your eligibility3
  • FEE-HELP is available on this unit, depending on your eligibility4

1 Please refer here more information on student contribution amounts.
2 Information on eligibility and Approved Pathway courses can be found here
3 Please refer here for eligibility for HECS-HELP
4 Please refer here for 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 this page 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

AssessmentTest or quiz (30%)|Test or quiz (20%)|Examination - invigilated (externally - Exams Office) (50%)
TimetableView 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.

LinksBooktopia textbook finder

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