Applied Econometrics - JEM116

• Title: Applied Econometrics
• Guaranteed by: Institute of Economic Studies (23-IES)
• Faculty: Faculty of Social Sciences
• Actual: from 2008 to 2008
• Semester: summer
• E-Credits: 5
• Examination process: summer s.:
• Hours per week, examination: summer s.:2/2, Ex [HT]
• Capacity: unknown / unknown (unknown)
• Min. number of students: unlimited
• 4EU+: no
• Virtual mobility / capacity: no
• State of the course: taught
• Language: English
• Teaching methods: full-time
• Additional information: http://ies.fsv.cuni.cz/index.php?module=sylab&action=sylab&id_sylab=140&lng=cs_CZ
• Note: course can be enrolled in outside the study plan; enabled for web enrollment
• Guarantor: prof. Roman Horváth, Ph.D.
• Class: Courses for incoming students
• Incompatibility : {Ekonomie(magisterské studium) specializace finance, finanční trhy a bankovnictví - povinné}, {Ekonomie(magisterské studium) specializace finance, finanční trhy a bankovnictví - povinně volitelné}, {Ekonomie(magisterské studium) specializace Evropská ekonomická integrace a hospodářská politika - povinné}, {Ekonomie(magisterské studium) specializace Evropská ekonomická integrace a hospodářská politika - povinně volitelné}

Annotation

English

The course concentrates on the practical use of econometric methods, reviewing the relevant methodology, its use, and possible alternative modeling approaches. The lectures are supplemented by computer classes, where students can gain hands-on experience in applied econometric analysis. During the course, we will especially focus on time series techniques applied to forecasting asset volatility, modeling inflation, exchange rate volatility, and other topics that you may regularly encounter in economic and financial literature. The course focuses on the following topics in econometrics: OLS, IV, ARIMA, GARCH, VAR, cointegration, filters, and limited dependent variables.

Last update: Horváth Roman, prof., Ph.D. (10.02.2023)

Literature

Selected recommended textbooks on applied econometrics:

Brooks, C.: Introductory Econometrics for Finance, Cambridge University Press.

Enders, W.: Applied Econometric Time Series, 2nd edition, 2003
Harris, R. and R. Sollis: "Applied Time Series Modelling and Foecasting", 2003
Stewart, K. G.: "Introduction to Applied Econometrics", 2005
Verbeek, M.: ?A Guide to Modern Econometrics?, 2nd edition, 2004
Kratzig, M. and H. Lutkepohl ,?Applied Time Series Econometrics?, 2004
Kocenda, E. and A. Cerny, "Elements of Time Series Econometrics: An Applied Approach", 2007, Karolinum Press

Last update: Horváth Roman, prof., Ph.D. (17.02.2021)

Teaching methods

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.

Last update: Kukačka Jiří, PhDr., Ph.D. (14.02.2023)

Syllabus

English

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

Last update: Horváth Roman, prof., Ph.D. (10.02.2023)

Czech

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 

Last update: Nechvátalová Lenka, Mgr. (24.02.2021)