Postgraduate Course: Advanced Time Series Econometrics (ECNM11049)
Course Outline
| School | School of Economics |
College | College of Humanities and Social Science |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This module explores further topics in time series econometrics, beyond Econometrics 2. Students will be introduced to various tools that are part of the basic econometric training of professional economists. The course is intended for students who want to be professional economists or who want to go on to PhD study. It also is very relevant to those planning to work or research in finance and/or macroeconomics.
The class covers two key topics, with a practical focus.
Modelling Volatility
Financial time series, particularly when captured at high frequencies, often exhibit volatility clustering. For example, the variance of stock returns can be high for extended periods and then low for extended periods. When this occurs, making the assumption that residuals are iid is unconvincing. Our modelling techniques need to be capable of capturing both periods of turbulence and tranquillity. One way to model volatility clustering is to allow the residual variance to depend upon its own history, so that a large realisation of the current period disturbance increases the conditional variance in subsequent periods. ARCH and GARCH modelling techniques have this property. We will look at this class of estimators and investigate their practical application.
Cointegation and Error-Correction Models
The concept of cointegration relates identifying equilibrium relationships among sets of non-stationary variables. The notion of equilibrium is best seen as a long-run concept, and has a clear interpretation in economics. Error correction models are a specific class of dynamic model in which short-run dynamic adjustment is influenced by deviation from equilibrium. Combining cointegration and error correction is intuitively appealing in that dynamics and the long-run are inherently linked. A key feature of a cointegrating relationship is that at least some of the variables involved must respond to deviation from equilibrium in a direction consistent with the system returning to equilibrium. We'll discuss these concepts and the modelling techniques that allow us to both test for cointegration and build and evaluate dynamic error correction models. We'll also look at some practical applications of the techniques. |
| Course description |
Not entered
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
Students MUST have passed:
Econometrics 1 (ECNM11043) AND
Econometrics 2 (ECNM11050)
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | Students should have taken and passed a course similar in content to Econometrics 1 ECNM11043 and Econometrics 2 ECNM11050 AND they must email sgpe@ed.ac.uk in advance to request permission. |
Information for Visiting Students
| Pre-requisites | Students should be registered for MSc Economics OR MSc Economics (Finance). All other students must email sgpe@ed.ac.uk in advance to request permission. |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2015/16, Available to all students (SV1)
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Quota: 22 |
| Course Start |
Block 4 (Sem 2) |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 18,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
78 )
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| Assessment (Further Info) |
Written Exam
100 %,
Coursework
0 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Formative assessment: students will have two opportunities to submit answers to a past exam question, by stated deadlines. Those who choose to submit on-time will be sent an indicative mark and written feedback.
Final Assessment: A two hour written exam and provides 100% of your final mark in this class. The exam paper will be sectionalised. You will be required to answer all questions in Section A and one question from a choice of three in Section B. Past papers are available.
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| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
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| Main Exam Diet S2 (April/May) | | 2:00 | |
Learning Outcomes
| This module explores further topics in time series econometrics, beyond Econometrics 2. Students will be introduced to various tools that are part of the basic econometric training of professional economists. The course is intended for students who want to be professional economists or who want to go on to PhD study. It also is very relevant to those planning to work or research in finance and/or macroeconomics.
|
Reading List
Enders: Applied Time Series Econometrics, Wiley.
Verbeek: A Guide to Modern Econometrics, Wiley.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Additional Class Delivery Information |
Lectures and tutorials will together take up 3 hours per week throughout the six week options block. |
| Keywords | Not entered |
Contacts
| Course organiser | Prof Jonathan Thomas
Tel: (0131 6)50 4515
Email: Jonathan.Thomas@ed.ac.uk |
Course secretary | Miss Sophie Bryan
Tel: (0131 6)51 1764
Email: Sophie.Bryan@ed.ac.uk |
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