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Regular version of the site
Bachelor 2024/2025

Times Series Econometrics

Type: Elective course (Economics)
Area of studies: Economics
Delivered by: School of Finance
When: 4 year, 1, 2 module
Mode of studies: offline
Open to: students of one campus
Instructors: Madina Karamysheva
Language: English
ECTS credits: 6
Contact hours: 58

Course Syllabus

Abstract

We first review the basics of time series econometrics. Then, in more details, we look at the VAR class of models, including VAR, VARX, VECM, GVAR, and its rather broad application to macroeconomics, including fiscal and monetary policy and some finance applications. After that, we cover ARCH, GARCH with its application to value at risk and contagion. Course Prerequesites: Linear Algebra, Probability Theory, Mathematical Analysis, Basic Econometrics.
Learning Objectives

Learning Objectives

  • The objective of this course is to provide the student with tools for empirical analysis of time series and to show how econometric models can be applied to empirical models in macroeconomics and finance.
Expected Learning Outcomes

Expected Learning Outcomes

  • Apply econometric models to empirical models in macroeconomics and finance
  • Understand the difference between various univariate models, be able to analyze the process and choose an appropriate model.
  • Detect unit roots, understand the difference between stationarity and non-stationarity
  • being able to condust forecasting with ARIMA models
  • Being able to apply various identification schemes to SVAR models, being able to understand how VAR are estimate, how to construct IRF and FEVD
  • Being able to apply obtained knowledge to real-life finance, economics problems
  • Being able to estimate variaous conditional volatility models and apply them to real-life finance problems
Course Contents

Course Contents

  • Introduction/reviewing of time series econometrics
  • Non-stationarity
  • ARIMA
  • Multivariate Time Series Models. VAR
  • VAR applications
  • Modeling the conditional variance (ARCH, GARCH, Multivariate GARCH)
Assessment Elements

Assessment Elements

  • non-blocking Quizzes
  • non-blocking Home assignments
  • non-blocking Big practical group project
  • non-blocking Midterm test
  • non-blocking Final test
Interim Assessment

Interim Assessment

  • 2024/2025 2nd module
    0.25 * Big practical group project + 0.25 * Final test + 0.2 * Home assignments + 0.25 * Midterm test + 0.025 * Quizzes + 0.025 * Quizzes
Bibliography

Bibliography

Recommended Core Bibliography

  • Applied econometric time series, Enders, W., 2004
  • James Douglas Hamilton. (2020). Time Series Analysis. Princeton University Press.

Recommended Additional Bibliography

  • Hamilton, J. D. . (DE-588)122825950, (DE-576)271889950. (1994). Time series analysis / James D. Hamilton. Princeton, NJ: Princeton Univ. Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.038453134

Authors

  • KARAMYSHEVA MADINA RINATOVNA