ETF5930 · Financial econometrics

Overview

This unit covers statistics econometrics tools to analyse and model the key characteristics of empirical distributions of asset returns, model and estimate the simple capital asset pricing model and its extensions, and test for various financial market hypotheses. It includes modelling, estimating and analysing time series properties of stationary and non-stationary financial data, and modelling and estimating simple and multivariate long-run relationships among financial variables. It also includes modelling and estimation of ARCH/GARCH volatilities, single-factor and multiple-factor capital asset pricing models. You will be requested to work through a number of questions and projects with a broad range of financial data sets.

Offerings

Assessment

The Handbook lists an examination for this unit.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. describe, interpret and critically analyse financial data
2. apply the simple and multivariate models and theory to model the relationship among financial variables, interpret the results, and conduct reliable statistical inference
3. test for stationary behaviour of financial time series
4. model the long-run relationships among financial time series
5. model and forecast the time-varying volatility of returns on financial assets
6. be proficient at econometric modelling of financial data using R software in the RStudio integrated development environment.

Workload

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. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.

Student experience, not official rules. Nothing here changes what the Handbook says.