Time
series: Analysis, Modelling and Forecasting
Level:
Intermediate
Course Length: 2-days
Overview: The course will show how economic and financial
time series can be modelled and analysed. The aim is to provide understanding
and insight into the methods used, as well as explaining the technical details.
However, the lectures will stress the concepts and the implications for applied
work, rather than the mathematical details. Statistical modelling will be
demonstrated using the STAMP package and participants will be given the
opportunity to use the package in class.
Topics Include:
|
Stationary vs.
Non Stationary time series |
Structural time
series models |
|
ARIMA models |
State Space
models and the Kalman Filter |
|
Unobserved
Components and signal extraction |
Seasonality,
Trends and Cycles |
Who should attend: The course is suitable for graduate
students, researchers in universities, and economists and statisticians working
in government, industry or the financial sector.
Prerequisites:
Participants are expected to have taken an introductory course in
econometrics or time series analysis. No previous
experience with STAMP is required. Work experience with econometrics would be
advantageous.
Prof. Andrew Harvey: Andrew
Harvey is Professor of Econometrics at the University of Cambridge with a
Fellowship at Corpus Christi College. He is also a Fellow of the Econometric
Society and a Fellow of the British Academy (FBA). Previously he was a Professor
of Econometrics at the London School of Economics. His research interests focus
on time-series econometrics, macro-econometrics, financial econometrics, state
space models, signal extraction, volatility, quantiles and copulas. Professor
Harvey is also one of the main developers of STAMP, an OxMetrics module for
structural time-series analysis and forecasting.
Further
information, including registration on will be available from