The aim of this module is to give students an understanding of econometric time-series methodology. The module will build upon the materials of Basic Econometrics. Important extensions include volatility models of financial time-series, and multivariate (multiple equation) models such as vector error correction and related cointegrating error correction models.
A. specify and demonstrate the distributional characteristics of a range of time series models
B. estimate appropriate models of financial and economic time series for the purpose of forecasting and inference
C. apply univariate and multivariate model selection and evaluation methods
D. apply conditional heteroskedasticity, unit roots and cointegration in economic and financial time series analysis
The module will be delivered by a combination of lectures and tutorials. Lecturers will be designed to provide essential information and introduce students to the basic tools and concepts of time-series analysis. Tutorials will provide students with the opportunity to further develop their skills through the exploration of various theoretical and practical problems, illustrated via actual data sets and real world problems from economics and finance.