Financial econometrics

Teachers

Included in study programs

Teaching results

The aim of the course is to provide students with the basic to intermediate level of understanding of econometric methods, techniques and tools used in the area of economics and finance. The student should then be able to – Knowledge, Skills and Competencies
1. Read and understand the key concepts in modern finance literature/ research papers
2. Use techniques and tools of econometrics and be able to independently construct econometric models
3. Use econometric models to test hypotheses, to determine (causal) impact of selected variables in economics and to make forecasts
4. Use econometric software

Indicative content

1. Introduction. Fundamentals from probability theory. Econometric software basics.
2. Linear regression model with one explanatory variable. Statistical verification of the results of the linear regression model.
3. Linear regression model with several explanatory variables. Basic assumptions of the classical linear regression model. The problem of multicollinearity.
4. Specification of econometric model. How to treat outliers and deal with extreme observations. Dummy variables.
5. Time series models: classical decomposition of time series, stationarity and ARMA models, non-stationary time series, exponential smoothing, ARIMA models.
6. Cointegration and error correction model.
7. Models with limited dependent variable - probit and logit.

Support literature

Brooks, Ch.: Introductory Econometrics for Finance, 3rd Edition, Cambridge, 2014.

Requirements to complete the course

30% two tests during the semester using software, 10% activity during the semester, 60% exam

Student workload

Total study load (in hours):
Attendance at lectures 26 h, participation in seminars 26 h, preparation for seminars 26 h, preparation for tests during semester 26 h, preparation for the exam 52 h

Language whose command is required to complete the course

english

Date of approval: 11.03.2024

Date of the latest change: 27.01.2022