Disentangling Systematic and Idiosyncratic Dynamics in Panels of Volatility Measures

59 Pages Posted: 31 May 2010 Last revised: 7 Oct 2014

See all articles by Matteo Barigozzi

Matteo Barigozzi

London School of Economics and Political Science; Université Libre de Bruxelles (ULB) - European Center for Advanced Research in Economics and Statistics (ECARES); University of Bologna

Christian T. Brownlees

Universitat Pompeu Fabra - Faculty of Economic and Business Sciences

Giampiero M. Gallo

Corte dei Conti - Italian Court of Audits; University of Bologna - Rimini Center for Economic Analysis (RCEA); CRENoS

David Veredas

Vlerick Business School

Date Written: January 29, 2014

Abstract

Realized volatilities observed across several assets show a common secular trend and some idiosyncratic pattern which we accommodate by extending the class of Multiplicative Error Models (MEMs). In our model, the common trend is estimated nonparametrically, while the idiosyncratic dynamics are assumed to follow univariate MEMs. Estimation theory based on seminonparametric methods is developed for this class of models for large cross-sections and large time dimensions. The methodology is illustrated using two panels of realized volatility measures between 2001 and 2008: the SPDR Sectoral Indices of the S&P500 and the constituents of the S&P100. Results show that the shape of the common volatility trend captures the overall level of risk in the market and that the idiosyncratic dynamics have an heterogeneous degree of persistence around the trend. Out-of-sample forecasting shows that the proposed methodology improves volatility prediction over several benchmark specifications.

Keywords: Vector Multiplicative Error Model, Seminonparametric Estimation, Volatility

JEL Classification: C32, C51, G01

Suggested Citation

Barigozzi, Matteo and Barigozzi, Matteo and Barigozzi, Matteo and Brownlees, Christian T. and Gallo, Giampiero M. and Veredas, David, Disentangling Systematic and Idiosyncratic Dynamics in Panels of Volatility Measures (January 29, 2014). Available at SSRN: https://ssrn.com/abstract=1618565 or http://dx.doi.org/10.2139/ssrn.1618565

Matteo Barigozzi

Université Libre de Bruxelles (ULB) - European Center for Advanced Research in Economics and Statistics (ECARES) ( email )

Ave. Franklin D Roosevelt, 50 - C.P. 114
Brussels, B-1050
Belgium

HOME PAGE: http://www.barigozzi.eu/research.html

London School of Economics and Political Science ( email )

Houghton Street
London, England WC2A 2AE
United Kingdom

University of Bologna ( email )

Piazza Scaravilli 2
Bologna, 40100
Italy

Christian T. Brownlees

Universitat Pompeu Fabra - Faculty of Economic and Business Sciences ( email )

Ramon Trias Fargas 25-27
Barcelona, 08005
Spain

HOME PAGE: http://econ.upf.edu/~cbrownlees/

Giampiero M. Gallo

Corte dei Conti - Italian Court of Audits ( email )

viale Mazzini
Roma, Roma 00195
Italy

University of Bologna - Rimini Center for Economic Analysis (RCEA) ( email )

Via Patara, 3
Rimini (RN), RN 47900
Italy

CRENoS ( email )

V. S. Ignazio 78
Cagliari, 09124
ITALY

David Veredas (Contact Author)

Vlerick Business School ( email )

Library
REEP 1
Gent, BE-9000
Belgium

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