Time Series and Financial Econometrics - ECON8200

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2022 to 2023
Spring Term 7 15 (7.5) Hans-Martin Krolzig checkmark-circle


The module offers a research-oriented introduction to contemporary time series and financial econometrics by linking econometric theory to empirical studies of the macro-economy and financial markets. It introduces models and methods used in central banks and research institutions for policy analysis and forecasting. It integrates empirical illustrations through the use of computer-based exercises with macroeconomic and financial data using appropriate software. We start with providing comprehensive treatment of univariate time series analysis and deal in details with the modelling and forecasting of stationary and nonstationary stochastic processes. We then proceed with specifying, estimating and testing a range of asset pricing models. Next, we addresses the analysis of returns predictability, both in the single regression framework and in the multivariate setting. Here we also provide careful modelling of volatility effects of the market data (e.g. by using asymmetric GARCH), and market interdependence.


Contact hours

Total contact hours: 30
Private study hours: 120
Total study hours: 150


Compulsory for the following courses:

• MSc Economics and Data Science
• Optional for MSc Economics, MSc Financial Economics

Method of assessment

Main assessment methods:

Project 30%
Examination 70%

**Please note that the exam in May/June 2023 will be Online (24 hour window)**

Reassessment: 100% exam

Indicative reading

The most up to date reading list for each module can be found on the university's reading list pages (https://kent.rl.talis.com/index.html).
Core reading
• Campbell, John, Lo, Andrew, and Craig MacKinlay. The econometrics of financial markets. 2nd Edition. Princeton University Press, 1997
• Enders, Walter. Applied Econometric Times Series. 4th Edition. Wiley, 2014.
• Hamilton, James. Time Series Analysis. Princeton University Press, 2014.
• Lütkepohl, Helmut. New Introduction to Multiple Time Series Analysis. Springer, 2006.

Recommended reading
• Franses, Philip, van Dijk, Dick and Anne Opschoor. Time Series Models for Business and
• Economic Forecasting. 2nd Edition. Cambridge University Press, 2016.
• Lo, Andrew. Adaptive Markets: Financial Evolution at the Speed of Thought. Princeton University Press, 2017.

This list will be augmented by the articles from such journals as American Economic Review, Econometrica, Journal of Applied Econometrics, Journal of Econometrics, Journal of Economic Perspectives, Journal of Political Economy, Quarterly Journal of Economics and Review of Economic Studies among others.

See the library reading list for this module (Canterbury)

Learning outcomes

On successfully completing the module you will be able to:
1. have comprehensive understanding of econometric techniques used with time series data
2. demonstrate critical assessment in reading and interpretation of empirical macroeconomic research
3. be practised in own modelling of economic series using advanced econometric theory
4. comprehensively understand the role of financial markets in modern economies
5. critically apply financial theories (including Efficient Market Hypothesis and Behavioural Finance)
6. have the ability to undertake complex empirical research using statistical software for time series analysis


  1. Credit level 7. Undergraduate or postgraduate masters level module.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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