- English
- FIN 3618
- 7.5 Credits
Introduction
Financial econometrics can be understood as the application of statistical techniques to data using the programming language R (which is widely used in the financial industry) to answer questions in finance. Therefore, financial econometrics can be used to test theories in finance. As such, it supports financial decision-making.
Course content
Introduction and mathematical foundations
- Steps involved in formulating an econometric model
- Functions
- Matrices
Statistical foundations and dealing with data
- Probability and probability distributions
- Descriptive statistics
- Types of data and data aggregation
- Simple returns vs. log returns
Review: The capital asset pricing model (CAPM)
- The assumptions underlying the CAPM
- Security market line
- Capital market line
- Sharpe ratio, Treynor ratio, Jensen's alpha
The classical linear regression model (CLRM)
- Simple regression
- The assumptions underlying the CLRM
- Properties of the OLS estimator
- Standard errors
- Statistical inference
- t-statistic
- p-value
Further development and analysis of the CLRM
- From univariate to multivariate regression
- Parameter estimation and standard errors in the multivariate regression framework
- Testing multiple hypotheses: the F-test
- R² and adjusted R²
CLRM assumptions and the diagnostic tests
- Assumption 1: Errors have zero mean
- Assumption 2: Errors have constant variance
- Assumption 3: Errors are linearly independent of each other
- Assumption 4: Errors are linearly independent of x-variables
- Assumption 5: Errors are normally distributed
- Multicollinearity
- Omitted variable bias
- Parameter stability tests
Disclaimer
This is an excerpt from the complete course description for the course. If you are an active student at BI, you can find the complete course descriptions with information on eg. learning goals, learning process, curriculum and exam at portal.bi.no. We reserve the right to make changes to this description.