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Disentangling systematic and idiosyncratic dynamics in panels of volatility measures
Barigozzi, Matteo Brownlees, Christian Gallo, Giampiero Veredas, David
Barigozzi, Matteo
Brownlees, Christian
Gallo, Giampiero
Veredas, David
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Publication Type
Journal article with impact factor
Editor
Supervisor
Publication Year
2014
Journal
Journal of Econometrics
Book
Publication Volume
182
Publication Issue
2
Publication Begin page
364
Publication End page
384
Publication Number of pages
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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 a heterogeneous degree of persistence around the trend. Out-of-sample forecasting shows that the proposed methodology improves volatility prediction over several benchmark specifications.
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Keywords
Accounting & Finance