ESF:MPF_APFE Applied Financial Econometrics - Course Information
MPF_APFE Applied Financial Econometrics
Faculty of Economics and AdministrationAutumn 2024
- Extent and Intensity
- 2/2/0. 6 credit(s). Type of Completion: zk (examination).
In-person direct teaching - Teacher(s)
- Axel Alejandro Araneda Barahona, Ph.D. (lecturer)
Axel Alejandro Araneda Barahona, Ph.D. (seminar tutor) - Guaranteed by
- Axel Alejandro Araneda Barahona, Ph.D.
Department of Finance – Faculty of Economics and Administration
Contact Person: Iva Havlíčková
Supplier department: Department of Finance – Faculty of Economics and Administration - Timetable
- Fri 10:00–11:50 P106, except Fri 20. 9., except Fri 8. 11.
- Timetable of Seminar Groups:
- Prerequisites
- BPE_ZAEK Introduction to Econometrics || BPE_INEC Introduction to Econometrics
Students are expected to be familiar with basic concepts of Corporate finance, Statistics and Econometrics - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Business Management and Finance (programme ESF, B-BMF)
- Economics (programme ESF, N-EKONA)
- Finance (programme ESF, B-FIN)
- Finance (programme ESF, N-FIN)
- Corporate Finance, Accounting, and Taxes (programme ESF, N-FIN)
- Financial Markets, Institutions and Technologies (programme ESF, N-FIN)
- Mathematical and Statistical Methods in Economics (programme ESF, N-MSME)
- Course objectives
- The course offers an insight into key topics of financial econometrics. The objective of the course is to develop an understanding about ideas and methods used to study financial markets. Emphasis is given on understanding the limits to predictability of market returns, specifics of time-series models (AR, ARDL, MA, ARMA, ARIMA, Unit-Root method, ARCH, GARCH), specifics of market returns (Different distributional assumptions) and how they are used to estimate key financial market risk measures (Value-at-Risk, Expected Shortfall). Participants are introduced to the CAPM and Fama – French pricing models, their estimation and possible further extensions (additional factors). To consolidate these ideas, students are introduced to a design and proper evaluation of an asset allocation strategy (e.g. model selection, forecasting, forecast evaluation). The applied nature of the course leads to the development of skills necessary to perform financial econometrics tasks in the R environment.
- Learning outcomes
- After completing the course, the student should be able to: - study the behavior of financial time-series, - quantify key risk measures of risky assets, - design and evaluate asset allocation strategies.
- Syllabus
- Introduction to financial econometrics 1. Introduction to financial markets and topics in financial econometrics. 2. Predictability of market returns. Time-series econometrics 3. Time-series econometric models, AR (p), MA (p), ARMA (p, q), ARIMA (p, q). 4. Unit Root Tests and invertibility, Seasonal Unit Root Tests, Unit Root Tests with Structural Breaks. 5. ARDL models – estimation, autocorrelation tests, HAC standard errors, time-series based boostrapping methods ). 6. ARCH models – ARCH(1), AR-ARCH(1), GARCH models – GARCH(1,1), distributional assumptions, ARCH tests Market risk measures 7. Value-at-Risk models – historical, distributional, model based. VaR forecast evaluation. 8. Expected shortfall – historical, distributional, model based. ES forecast evaluation. Event studies 9. Market event study – design of a market event study. 10. News driven market movements, e.g. monetary policy news announcements. Asset pricing and allocation 11. Capital asset pricing model, Fama and French model. 12. Asset allocation studies I., granularity, asset based allocation.
- Literature
- recommended literature
- BERNARDI, M and Catania L AMP. The model confidence set package for R. International Journal of Computational Economics and Econometrics. 2018, vol. 8, No 2, p. 144-158. Available from: https://dx.doi.org/10.1504/IJCEE.2018.091037. info
- LEVENDIS, John D. Time Series Econometrics: Learning through replication. Springer, 2018. ISBN 3-319-98281-8. info
- CAMPBELL, J W and A W MacKinlay A C LO. The econometrics of financial markets. Princeton University press, 1997. ISBN 0-691-04301-9. info
- not specified
- LINTON, O. Financial econometrics: Models and Methods. Cambridge University Press, 2019. ISBN 978-1-316-63033-4. info
- Teaching methods
- Lecture notes, problem sets, and case studies are necessary for successful passing of the course. As they are required they will be available in the eLearning module for free.
- Assessment methods
- Grading is in accordance with the internal guidelines of the Faculty of Economics and Administration of Masaryk’s University and is based on every week assignments during seminars (50%), and final exam (50%). A total of 51% minimum is required to pass.
- Language of instruction
- English
- Further comments (probably available only in Czech)
- The course is taught annually.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/econ/autumn2024/MPF_APFE