STAT8002 Applied Time Series Analysis
| Offered By | School of Finance, Actuarial Studies & Appl Stats |
|---|---|
| Academic Career | Graduate Coursework |
| Course Subject | Statistics |
| Offered in | First Semester, 2010 and First Semester, 2011 |
| Unit Value | 6 units |
| Course Description |
This course considers statistical techniques to evaluate processes occurring through time. It introduces students to time series methods and the applications of these methods to different types of data in various contexts. Time series modelling techniques will be considered with reference to their use in forecasting where suitable. While linear models will be examined in some detail, extensions to non-linear models will also be considered. The latter part of the course will analyze some case studies. Coverage will begin with basic concepts on difference equations, which underlie all of the time-series methods employed in the rest of the course. Some basic rules of matrix algebra will also be reviewed, as they will be useful for the study of multiple time series models. We will then proceed with the traditional Box-Jenkins approach to time series analysis and then continue with dynamic modeling and regression approaches. Non-linear models such as conditionally heteroskedastic (time-varying variance) models will also be studied. In addition, recent developments such as cointegration analysis, error correction models, vector autoregression, and multivariate cointegration will also be covered, if time permits. We will learn not only how to construct these models but also how to use them in applied analysis. Heavy emphasis will be given to fundamental concepts and applied work. Since this is a course on applying time series techniques, different examples will be considered whenever appropriate. |
| Learning Outcomes |
By the end of the course, students should be able to: understand and apply the concept of stationarity to the analysis of time series data; use the Box-Jenkins approach to model time series data; run and interpret time series models involving time-varying volatility and/or trends; use vector autoregression to analyze data and apply techniques such as impulse response analysis to interpret results; analyze cointegrated data using an error correction model. |
| Indicative Assessment |
Two major assignments which will count for a minimum of 30% (and a maximum of 40%) of the final mark, with a final examination counting for a maximum of 70%. |
| Workload | 10 hrs / wk |
| Course Classification(s) | AdvancedAdvanced courses are designed for students having reached 'first degree' level of assumed knowledge, which provide a deep understanding of contemporary issues; or 'second degree' and higher levels of knowledge; or for transition to research training programs. |
| Areas of Interest | Actuarial Studies, Finance, and Statistics |
| Eligibility | At least an average of 65% (or equivalent) in the final two years of an Australian undergraduate degree with at least two years of university level statistical and mathematical study including calculus and linear algebra, as well as mathematical statistics and linear regression theory. |
| Prescribed Texts |
See Course Outline: http://ecocomm.anu.edu.au/courses/outline/STAT8002.pdf |
| Preliminary Reading |
See Course Outline: http://ecocomm.anu.edu.au/courses/outline/STAT8002.pdf
|
| Programs | Graduate Certificate in Actuarial Studies and Master of Applied Statistics |
| Other Information |
For further information please refer to http://ecocomm.anu.edu.au/courses/course.asp?code=STAT8002 |
| Academic Contact | Seehttp://ecocomm.anu.edu.au/courses/course.asp?code=STAT8002 |
The information published on the Study at ANU 2010 website applies to the 2010 academic year only. All information provided on this website replaces the information contained in the Study at ANU 2009 website.
