Quantitative Methods in Finance
The course deals with advanced quantitative methods for estimation and testing of financial relationships. This includes, but is not limited to; time series, panel data, ARCH and GARCH, Machine Learning, Artificial Intelligence.
Necessary technical background in mathematics will be given.
We will go through regression with time series data when variables are both stationary and non-stationary.
Methods for estimation and interpretation of econometric models that may include non-stationary variables make out one central theme. Both single equation methods and the system approach will be discussed, as well as statistical methods for estimating and determining the presence of one or more cointegrated relations among a set of economic time series.
The focus in this course is on modern quantitative applications in finance, for example how to create a portfolio using active investment strategies, and checking how, and if, its returns can be explained using time series and panel data methods.
To put our knowledge into context, we will also learn about ethics in financial markets. The topic of ethics is one of fundamental importance to the investment profession. Acting responsibly with high levels of integrity builds trust, upon which the investment profession is built. This part of the course is also covered by the CFA Level II syllabus.
KNOWLEDGE - The candidate...
- has an advanced understanding of the assumptions econometric time series models are based on;
- has an in-depth understanding of the econometric methods necessary for doing empirical analysis in financial economics;
- is able to use software to carry out econometric analysis of time series and panel data.
SKILLS - The candidate...
- will be able to conduct, interpret and critically deal with empirical studies in finance and related fields;
- will be able to identify the advantages and disadvantages of the various methods and techniques;
- will be able to understand the relationships between the theoretical concepts taught in finance class and their application in empirical studies;
COMPETENCE - The candidate...
- has the tools and knowledge necessary to define, design and carry out the necessary analysis and interpretations an academically rigorous research thesis needs.
- can convey extensive independent work and masters forms of expression in financial econometrics
The course combines traditional lectures with active learning methods.
The lectures present theories, models and methods through blackboard teaching and presentations.
To enhance students' practical understanding and application of the methods, emphasis is placed on problem-based learning where students work in groups with relevant case assignments. These assignments are based on real financial problems and are reviewed in plenary at the end of each teaching session.