This course builds on MSING065 and MSING066 and aims to deliver an overview of the state-of- the art econometric methods used by researchers and practitioners in the empirical analysis of financial data.
The main focus of the course is on time series methods, i.e., the analysis of data measured over time and at different frequencies, with the goal of building models explaining the dynamic evolution of economic and financial data over time. Important applications will focus on risk management and on forecasting.
After taking the course, a student will be able to:
- Know how to select the appropriate model, for, e.g., forecasting economic and financial variable or for modelling volatility
- Know how to test the fit of models fit or the accuracy of forecasts
- Understand how to deal with data that exhibits trends, persistence and structural breaks
- Learn ways to model dependence among economic/financial variables
Students will also have an opportunity to practice the implementation of some of the techniques using software such as STATA.
- Regression with dependent data;
- ARMA models
- Volatility modelling
- Structural change testing
- Modelling trends
- Unit root testing
- Multivariate models
- Impulse-response analysis
- Forecasting and forecast evaluation
Unseen Examination (2 hours) 80%
Group Coursework 20%
Coursework consists of four problem sets (each weighted 5%) for which students can work in groups of up to 3 people.
There is no required textbook. A reference textbooks that might be useful for parts of the course is Analysis of Financial Time Series, by Ruey Tsay, Wiley 2010