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.
Aine läbinud üliõpilane:
- oskab erinevate andmetüüpide korral valida sobivat ökonomeetrilist mudelit;
- hindab mudeli parameetreid, kasutades selleks sobivat tarkvara;
- teeb vajalikud testid ja interpreteerib nende tulemusi;
- võrdleb erinevaid mudeleid, kasutades selleks sobivalt valitud suurusi;
- interpreteerib ökonomeetrilise analüüsi tulemusi.
- oskab erinevate andmetüüpide korral valida sobivat ökonomeetrilist mudelit;
- hindab mudeli parameetreid, kasutades selleks sobivat tarkvara;
- teeb vajalikud testid ja interpreteerib nende tulemusi;
- võrdleb erinevaid mudeleid, kasutades selleks sobivalt valitud suurusi;
- interpreteerib ökonomeetrilise analüüsi tulemusi.
learning outcomes in the course in Eng.
After comleting this course the student:
- is able to formulate and estimate econometric models based on different data sets such as cross-sectional, time series and panel data and data with qualitative dependent variable;
- 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 formulate and estimate econometric models based on different data sets such as cross-sectional, time series and panel data and data with qualitative dependent variable;
- performs the necessary tests and interprets the results;
- compares different models using appropriate quantities;
- interprets outcomes of econometric analyses and draws appropriate conclusions.
brief description of the course in Estonian
Klassikaline lineaarne regressioonmudel. CAPM mudel ja beetakordaja. Juhuslikud protsessid. Finantsaegridade prognoosimine. Autoregressiivsed mudelid. Libiseva keskmise mudelid. ARMA. Vektor-autoregressiivsed mudelid. Pikaajaliste seoste modelleerimine. Statsionaarsus ja ühikjuure testid. Kointegratsioon. Volatiilsuse modelleerimine. ARCH, GARCH, EGARCH, TARCH mudelid. Suure sagedusega aegread. Paneelandmed. Kasutatakse vabavara Gretl
brief description of the course in English
Classical linear regression model. CAPM model. Random processes. Predicting financial returns. Autoregressive models. Moving average models. ARMA. Vector-autoregressive models. Modelling long-run relationship in finance. Stationarity and unit root testing. Cointegration. Modelling volatility. ARCH, GARCH, EGARCH, TARCH. High-frequency data. Panel data. Software: freeware Gretl
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
-
LECTURER SYLLABUS INFO
semester of studies
teaching lecturer / unit
language of instruction
Extended syllabus
2025/2026 spring