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.
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.
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
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type of assessment in English
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independent study in Estonian
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independent study in English
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study literature
Brooks, C. "Introductory Econometrics for Finance"
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):