Statistical Methods in Finance and Economics
The course introduces basic economic and finance principles and emphasises the techniques for fundamental empirical research, interpretation of quantitative results and model evaluatrions in finance and economics. It emphasises the understanding of quantitative methods, model evaluations, and the techniques for empirical studies in finance, economics and business. The module starts with an introduction to general economic concepts, then it will cover the basics and extension of ordinary least sqyare methods, heteroskedasticity, autocorrelation, multicollinearity, model specifications, to selective advanced topics from simultaneous equation models, binary and discrete choice models, qualitative and limited dependent variable models, time series analysis, panel data models, and nonparametric analysis. Furthermore, students will gain hands-on experience formulating and estimating models, interpreting results and making forecasts.
By the end of the module you should be able to:
- Understand the nature of statistical inferential procedures involved in analysing economic data
- Formulate models to solve some empirical economic problems
- Apply appropriate statistical methods and techniques to understand relationships among variables
- Gain hands-on experience in using statistical computing program of SAS
- Understand the power and limitations of applied statistical analysis
- Perform and present research by using relevant data and statistical tools
44 hours of lectures
10 hours of back-up classes
Will be specified by the lecturer in the first week of term.