Financial Econometrics
BASIC DATA
course listing
A - main register
course code
MEM5240
course title in Estonian
Finantsökonomeetria
course title in English
Financial Econometrics
course volume CP
-
ECTS credits
6.00
to be declared
yes
fully online course
not
assessment form
Examination
teaching semester
autumn - spring
language of instruction
Estonian
English
Study programmes that contain the course
code of the study programme version
course compulsory
yes
Structural units teaching the course
ME - Department of Economics and Finance
Timetable link
Version:
VERSION SPECIFIC DATA
course aims in Estonian
Õppeaine eesmärk on tutvustada finantsaegridade analüüsimiseks kasutatavaid ökonomeetrilisi meetodeid.
course aims in English
The aim of the course is to introduce econometric methods used to analyse financial time-series.
learning outcomes in the course in Est.
Õppeaine läbinud üliõpilane:
- oskab erinevate andmetüüpide korral valida sobivat ökonomeetrilist mudelit;
- viib läbi mudeli parameetrite hindamist, kasutades selleks sobivat tarkvara;
- viib läbi vajalikud testid ja interpreteerib nende tulemusi;
- võrdleb erinevaid mudeleid, kasutades selleks sobivalt valitud suurusi;
- interpreteerib ökonomeetrilise analüüsi tulemusi;
- annab kaasõppijate ökonomeetrilistele projektidele argumenteeritud ja arengut toetavat tagasisidet.
- oskab erinevate andmetüüpide korral valida sobivat ökonomeetrilist mudelit;
- viib läbi mudeli parameetrite hindamist, kasutades selleks sobivat tarkvara;
- viib läbi vajalikud testid ja interpreteerib nende tulemusi;
- võrdleb erinevaid mudeleid, kasutades selleks sobivalt valitud suurusi;
- interpreteerib ökonomeetrilise analüüsi tulemusi;
- annab kaasõppijate ökonomeetrilistele projektidele argumenteeritud ja arengut toetavat tagasisidet.
learning outcomes in the course in Eng.
After completing the course, the student:
- is able to select an appropriate econometric model for different types of data;
- performs model parameter estimation using appropriate software;
- performs the necessary tests and interprets the results;
- compares different models using appropriate quantities;
- interprets outcomes of econometric analyses and draws appropriate conclusions;
- is able to provide well-argued, constructive feedback on peers’ econometric projects.
- is able to select an appropriate econometric model for different types of data;
- performs model parameter estimation using appropriate software;
- performs the necessary tests and interprets the results;
- compares different models using appropriate quantities;
- interprets outcomes of econometric analyses and draws appropriate conclusions;
- is able to provide well-argued, constructive feedback on peers’ econometric projects.
brief description of the course in Estonian
Aegridade ARIMA, SARIMA ja XARIMA mudelid ning prognoosimine. VAR mudelid, Grangeri kausaalsus ning impulssreaktsiooni-funktsioon. Aegridade spektraalanalüüs. Mittestatsionaarsed aegread, ühikjuure testimine, struktuursed muutused. Kointegratsioon, Johanseni kointegratsiooni test, veaparandusmudelid ECM ja VECM. Volatiilsuse modelleerimine: ARCH, GARCH, EGARCH, GJR mudelid. Mitmemõõtmeline volatiilsuse modelleerimine: MGARCH, DVECH ja tingliku korrelatsiooniga MGARCH mudelid. Juhtumi analüüs. CAPM mudeli testimine. Eksogeensus ja intrumenttunnused. Paneelandmed. Ühikjuure testimine paneelandmete korral. Tõenäosusmudelid. Kasutatakse tarkvara Stata.
brief description of the course in English
Time series models ARIMA, SARIMA, XARIMA, and forecasting. VAR models, Granger causality and impulse response function. Time series spectral analysis. Non-stationary time-series, unit root testing, structural breaks. Cointegration, Johansen test, error correction models ECM and VECM. Modelling volatility: ARCH, GARCH, EGARCH, GJR. Multivariate volatility modelling: MGARCH, DVECH and conditional correlation models. Event study. Testing CAPM model. Exogeneity and instruments. Panel data models and unit-root tests. Probability models. Software: Stata.
type of assessment in Estonian
-
type of assessment in English
-
independent study in Estonian
-
independent study in English
-
study literature
Brooks, C. "Introductory Econometrics for Finance"
Tsay, R. S. "Analysis of Financial Time series"
Wang, P. "Financial Econometrics"
Tsay, R. S. "Analysis of Financial Time series"
Wang, P. "Financial Econometrics"
study forms and load
daytime study: weekly hours
4.0
session-based study work load (in a semester):
lectures
2.0
lectures
-
practices
0.0
practices
-
exercises
2.0
exercises
-
lecturer in charge
-
type (CBL/PBL)
not specified
LECTURER SYLLABUS INFO
semester of studies
teaching lecturer / unit
language of instruction
Extended syllabus
2025/2026 spring