Financial Econometrics

DIPARTIMENTO di ECONOMIA - DIEC
Scuola di Scienze Sociali
SCUOLA DI
SCI ENZE SOCI ALI
Financial Econometrics - Codice 85554
(laurea magistrale in Laurea Magistrale Economia e Istituzioni
Finanziarie ) - A.A. 2015/16
Docente
Malvina MARCHESE
e-mail:
…[email protected]
Anno di corso:2
Sem:2
Sede: genova
SSD: SECS-P/05
cfu 9
Ore lezione:72
Obiettivi formativi
The course provides a survey of the theory and application of time series models in financial
econometrics. Students are introduced to time series analysis of linear univariate and multivariate
covariance stationary models with short and long memory parameterization. The course then
employs linear time series knowledge to introduce students to time series financial econometrics
models, particularly discrete- time parametric ARCH models. The main objective of this course is
to develop the skills needed for modelling and forecasting assets volatilities and their comovements in financial markets. The course aims to provide students with a strong theoretical
understanding of volatility models and techniques for estimations, assessment and forecasting in
financial markets under a variety of degree of shock persistence. Theoretical lectures are
complemented by computer classes whose aim is to enable the students to develop computational
skills in MATLAB for empirical research
Programma/Contenuti
Topic I: LINEAR TIME SERIES ANALYSIS .
*Stochastic processes, covariance stationarity, strict stationarity, unit root processes, fractionally
integrated processes, Wold decomposition theorem.
*Introduction to spectral analysis: Fourier transforms,Spectrum of a time series process, rate of
decay of the spectrum for short and long memory processes.
*ARMA,ARIMA,ARFIMA univariate models: estimation and principles of forecasting.
*Unit root tests,long memory tests, cointegration,model diagnostic.
TOPIC II: UNIVARIATE GARCH MODELS.
*Stylized facts of asset returns
*ARCH model: identification and covariance stationarity conditions ,order identification,
estimation, evaluation
*GARCH model: identification and covariance stationarity conditions ,order identification,
estimation, evaluation and forecasting.
DIPARTIMENTO di ECONOMIA - DIEC
Scuola di Scienze Sociali
SCUOLA DI
SCI ENZE SOCI ALI
*Asymmetric GARCH models and leverage effects:EGARCH,QGARCH,GJGARCH,TGARCH:
identification and covariance stationarity conditions ,order identification, estimation, evaluation and
forecasting.
*Long memory in univariate GARCH models: testing for long memory in the time series domain,
forecasting in presence of long memory.
TOPIC III: MULTIVARIATE GARCH MODELS.
*Co-movements of financial returns: empirical and theoretical examples. Introduction to MGARCH
models and specific issues.
*VEC and BEKK models: dimensionality issues, conditions for positive definiteness, iterative
procedures for estimation.
*FACTOR MODELS
*CCC models: dimensionality issues, conditions for positive definiteness, iterative procedures for
estimation.
*NON PARAMETRIC models
*Testing in MGARCH models
TOPIC IV: APPLICATIONS
*Option pricing
*Asset allocation
*Value at risk
Eventuali propedeuticità e/o pre requisiti consigliati
No basic knowledge of time series econometrics is assumed.
No basic knowledge of Matlab is required.
A good knowledge of introductory econometrics with matrix algebra is strictly required (
Econometria I CLEC or equivalent ).
Good knowledge of probability theory and statistical inference is strictly required (Statistical
models exam, prof Lagazio)
Good background in calculus and basic linear algebra.
Risultati di apprendimento previsti
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Theoretical skills: Students should develop a sounded theoretical understanding of time
series processes with different degrees of memory persistence both in the time and in the
spectral domain. They should develop awareness in modelling linear time series and then
use this knowledge to appreciate the different volatility models in the literature and their
ability to reproduce stylized facts of assets returns. .……………………………..
Applied skills: ……Students must learn to apply their theoretical knowledge of time series
models to actual time series data, implementing model detection and diagnostic on data sets.
They should be able to test for unit roots, cointegration, long and short memory . They
should be able to write simple Matlab codes for forecasting of volatilities.
…………………………………………………….
Awareness: Students will develop awareness of financial econometrics models and by the
end of the course they should be able to employ such models also in the analysis
of commodity prices, such as oil prices, gas prices and energy commodity prices in general.
Communication skills:
Students will develop a good knowledge of econometric
DIPARTIMENTO di ECONOMIA - DIEC
Scuola di Scienze Sociali
SCUOLA DI
SCI ENZE SOCI ALI
terminology which will enable them to read most of the available literature on financial
econometrics .
Learning skills: Students will develop econometrics and statistical skills that will enable them to
analyze financial markets data sets, and to understand autonomously most complex models
available in the literature.
Modalità didattiche, obblighi, testi e modalità di accertamento.
Modalità didattiche Lectures, classes and computer classes.
Presente su Si ☒ No ☐
Aulaweb
Obblighi
Testi di studio Hamilton Time series econometrics
Franq Zaquoian Garch models
Lecture notes posted on Aulaweb
Modalità di Written exam on both theoretical models presented during the course and their
accertamento empirical implementations. Students are expected to show their ability to extend and
derive the theoretical results explained during the course. Moreover they are
requested to interpret regression output in Matlab and Gretl providing results on model
detection and diagnostic on data set.
Ripetizione Allowed as many time as the student wishes.
dell’esame
Informazioni aggiuntive per gli studenti non frequentanti
Modalità didattiche The students will be tested on the same contents above
Obblighi Students are requested to email the lecturer if they cannot attend lectures.
Testi di studio Hamilton Time series econometrics
Franq Zaquoian Garch models
Modalità di Esame
accertamento
☒ scritto ☐ orale ☐ altro:
Ripetizione Allowed as many time as the student wishes.
dell’esame
For foreign students
Course description
Methodology
Attendance
Textbook and
other
reccomended
resources
Assessment
Note
DIPARTIMENTO di ECONOMIA - DIEC
Scuola di Scienze Sociali
SCUOLA DI
SCI ENZE SOCI ALI
Si invitano tutti gli studenti a consultare periodicamente la pagina di questo insegnamento sul portale dell’elearning AulaWeb (raggiungibile dal sito di Ateneo o all’indirizzo: http://www.aulaweb.unige.it/). Tutte le
informazioni e i materiali relativi a questo insegnamento sono pubblicate esclusivamente in tale sito.