Quantitative Methods in Finance

Aims of the course

The students will obtain the knowledge and skills for modern quantitative analysis in finance. They will be able to apply this knowledge to the investigation of economic processes, and also understand the econometric and multivariate methods, approaches, ideas, results and conclusions met in the majority of economic and business books and articles. The students will understand essential differences between time series, cross-section data and panel data, and the specific econometric problems met when working with these types of data. The students should get the skills for construction and development of multiple regression models. The considered methods and models will be mastered practically on real economic data bases with modern econometric software.

Key objectives and competences of the course are thus the following:
- To expand the knowledge of basic econometric models used in applied economic analysis, where a formal treatment of the models is complemented with empirical applications.
- To prepare the students to be able to use econometric methods and multivariate analysis for analysis at an advanced level.

Course syllabus

1. Introduction to quantitative methods in finance
2. Multiple regression model and the least squares estimator
3. Hypotheses testing
4. Prediction with multiple regression model
5. Model diagnostics in the classical linear regression model
6. Regression models with dummy explanatory variables
7. Distributed-lag regression models
8. Instrumental variables estimation
9. Time series modelling and forecasting
10. Principal component analysis
11. Exploratory factor analysis
12. Cluster analysis
13. Multiple discriminant analysis
14. Discrete choice models and the maximum likelihood estimator
15. Panel data analysis

Course director(s)

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