FIN538 Financial Econometrics
Spring 2019Autumn 2019
The goal of the course is to cover econometrics methods widely used in asset pricing and corporate finance with a particular emphasis on intuition and empirical applications.
- Introduction to R
- Basic Econometrics
- Ordinary Least Squares
- Maximum Likelihood
- Generalized Method of Moments
- Cross-section of stock returns (CAPM, multifactor models, Arbitrage Pricing Theory (APT))
- Black, Jensen and Scholes (1972) approach
- Fama MacBeth (1973) approach
- Principal Component Analysis
- Time series of stock returns (Efficient Market Hypothesis, volatility and correlation modelling, high-frequency data)
- Event studies
- ARCH/GARCH/DCC models
- High-frequency time-series
- Risk management
- Expected Shortfall
- Extreme Value Theory
- Panel data
- Instrumental variables
- Natural experiments
After completion of the course, the student's will be able to:
- Assess the common empirical research methods in finance
- Understand methods for testing asset pricing models
- Understand methods used corporate finance, time series analysis and choice theory.
- Implement the common empirical methods in finance using R.
- Replicate analysis in state-of-the art empirical finance papers.
- Will be able to conduct, interpret and critically deal with empirical studies in finance.
- Has the tools and knowledge necessary to define, design and deliver the results of empirical investigations as done in academic articles.
The course will consist of the combination of lectures and class student presentations.
Advanced master-level courses such as asset pricing, investment, corporate finance, and econometrics.
Credit reduction due to overlap
The course cannot be combined with ECS503 Advanced Econometrics.
Class participation (20%)
Individual presentation(s) of academic paper(s) (20%)
Four individual assignments (60%)
Grading scale A - F.
No textbook. The course is based on lecture slides and academic papers.
- ECTS Credits
- Teaching language
Autumn, offered autumn 2019.
Assistant Professor Darya Yuferova, Department of Finance, NHH