Scheda insegnamento
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Docente Iliyan Georgiev
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Moduli Iliyan Georgiev (Modulo 1)
Giuseppe Cavaliere (Modulo 2)
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Crediti formativi 6
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SSD SECS-P/05
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Lingua di insegnamento Inglese
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Campus di Bologna
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Corso Laurea Magistrale in Economics (cod. 8408)
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Orario delle lezioni (Modulo 1) dal 16/02/2022 al 02/03/2022
Orario delle lezioni (Modulo 2) dal 03/03/2022 al 17/03/2022
SDGs
L'insegnamento contribuisce al perseguimento degli Obiettivi di Sviluppo Sostenibile dell'Agenda 2030 dell'ONU.
Anno Accademico 2021/2022
Conoscenze e abilità da conseguire
At the end of the course the student has acquired an advanced and comprehensive knowledge of the main, up-to-date econometric methods for the analysis of economic and financial time series data. In terms of inference techniques, emphasis is given to up-to-date bootstrap methods. In particular, she/he is able: - to analyze critically the application of advanced econometric models to economic time series data; - to implement and make use of proper (asymptotic and bootstrap) inference methods in dynamic environments.
Contenuti
Part I: Conditional volatility models: estimation, inference and applications
- Univariate GARCH processes: properties, estimation, diagnostics and inference.
- Applications to Value at Risk.
- Multivariate models of conditional variance: estimation, diagnostics and inference.
- Applications to optimal hedging.
Part II: Asymptotic and Bootstrap inference in time series
- Introduction to the bootstrap: iid, wild, fixed regressor, moving block, m out of n, permutation, subsampling
- Bootstrapping stationary time series
- Bootstrap inference in multivariate (VAR) models
- Non-stationary time series: bootstrapping unit root and cointegration tests
- Bootstrapping conditional volatility models and the parameter on the boundary problem
Testi/Bibliografia
Lütkepohl H. (2005). New Introduction to Multiple Time Series Analysis. Springer.
Gatarek L., Johansen S. (2015). PDF [https://www.eui.eu/Documents/DepartmentsCentres/Economics/Seminarsevents/Johansen.pdf]
Horowitz J. (2001). The bootstrap. In: Handbook of Econometrics, vol. V.
Lecture notes provided by the instructors
Metodi didattici
Lectures
Modalità di verifica e valutazione dell'apprendimento
Take home exam (possibly followed by an oral discussion, on discretion of the course instructors).
Passing numerical grades are intended to match the following qualitative description:
18-23: sufficient
24-27: good
28-30: very good
30 cum laude: excellent.
Strumenti a supporto della didattica
A dedicated page on virtuale.unibo.it
Orario di ricevimento
Consulta il sito web di Iliyan Georgiev
Consulta il sito web di Giuseppe Cavaliere
Alumni