[Forum SIS] Short Course di Statistica - Qiwei Yao (London School of Economics and Political Sciences)

[Statlab- UNISA]

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Annuncio Short Course di Statistica

Dipartimento di Scienze Economiche e Statistiche - DiSES

Università degli Studi di Salerno

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Data evento: Venerdì 6 giugno 2014, ore 11:00 - Sala del Consiglio  

Qiwei Yao (London School of Economics and Political Sciences)

Short course on factor modelling for high-dimensional time series 

Il corso è organizzato nell'ambito delle Attività promosse dal PRIN "La
previsione economica e finanziaria: il ruolo dell’informazione e la capacità
di modellare il cambiamento"

Responsabile Scientifico nazionale: Tommaso Proietti.
Responsabile Scientifico locale: Michele La Rocca

ABSTRACT:

Following a brief survey on the factor models for multiple time series in
econometrics, we introduce a statistical approach from the viewpoint of
dimension reduction. Our method can handle nonstationary factors. However
under stationary settings, the inference is simple in the sense that both
the number of factors and the factor loadings are estimated in terms of an
engenanalysis for a non-negative definite matrix, and is therefore
applicable when the dimension of time series is in the order of a few
thousands. Asymptotic properties of the proposed method are investigated
under two settings: (i) the sample size goes to infinity while the dimension
of time series is fixed; and (ii) both the sample size and the dimension of
time series go to infinity together. In particular, our estimators for
zero-eigenvalues enjoy the faster convergence (or divergence) rates, which
makes the estimation for the number of factors easier.  Furthermore the
estimation for both  the number of factors and the factor loadings shows the
so-called "blessing of dimensionality" property.  A two-step procedure is
investigated when the factors are of different degrees of strength.
Numerical illustration with both simulated and real data is also reported.

Tutti gli interessati sono cordialmente invitati a partecipare.

 

Laboratorio di Ricerca e Formazione avanzata in Statistica (STATLAB)
<http://www.dises.unisa.it/centri_laboratori/statlab/index> 

Dipartimento di Scienze Economiche e Statistiche - DiSES
<http://www.dises.unisa.it/index>  

Università degli Studi di Salerno

Via Giovanni Paolo II, 132

84084 Fisciano SA

Tel. +39 089 96 3132

 



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