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Poslední úprava: prof. Roman Horváth, Ph.D. (10.02.2023)
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Poslední úprava: prof. Roman Horváth, Ph.D. (10.02.2023)
Students will learn the basics of time series econometrics with an emphasis on how to apply these methods. |
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Poslední úprava: prof. Roman Horváth, Ph.D. (02.04.2024)
Grading - in line with the Dean's decree 17/2018. Exam at the end of the semester (80% weight) Term paper (20% weight) Exam dates: 29.5. 14:00 room 206 11.6. 17:00 room 206
Please register for the exam using the SIS. The details regarding the term paper are available in Lecture 1.pdf and in separate pdf files posted (during the semester) in the SIS. |
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Poslední úprava: prof. Roman Horváth, Ph.D. (17.02.2021)
Selected recommended textbooks on applied econometrics: Brooks, C.: Introductory Econometrics for Finance, Cambridge University Press.
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Poslední úprava: PhDr. Jiří Kukačka, Ph.D. (14.02.2023)
Lectures accompanied by seminars in computer room 016. The software R will be used during the seminars, and materials will be processed in the interactive Jupyter Notebook .ypinb format (freeware, available on all computers in 016). If you want to work on your computer, ensure in advance Jupyter is properly connected to the R kernel. If you are new to R and have not used Jupyter so far, study the Intro_to_jupyter+R.zip in Files and review the recorded introductory lectures on R basics, Data structures, Data input, and Basic data management from Data Analysis in R and/or the first recorded lectures from Data Science with R. |
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Poslední úprava: prof. Roman Horváth, Ph.D. (10.02.2023)
Grading - in line with the Dean's decree 17/2018. Exam at the end of semester (60% weight) Term paper (40% weight) The details regarding the research proposal and term paper are available in Lecture 1.pdf and in separate pdf files posted (during the semester) in the SIS. |
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Poslední úprava: Mgr. Lenka Nechvátalová (24.02.2021)
Link to join the lectures and seminars (Microsoft teams): https://teams.microsoft.com/l/meetup-join/19%3a59d6db0790594a7781750871c6c259b7%40thread.tacv2/1614082938348?context=%7b%22Tid%22%3a%22e09276da-f934-4086-bf08-8816a20414a2%22%2c%22Oid%22%3a%2290413cdc-137d-4c39-a5d1-2f6fb3119fb1%22%7d
Code to join MS teams class: d7t0t2x
1. Introduction 2. OLS and basics 3. Introduction to Time Series 4. ARIMA Modeling 5. GARCH (2 lectures) 6. Introduction to Cointegration 7. Vector Autoregression 8. TSLS, IV 9. Non-linear time series models 10. Limited dependent variable models in finance 11. Time series filters 12. Networks 13. Guest lecture |