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    Disentangling systematic and idiosyncratic dynamics in panels of volatility measures

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    Publication type
    Journal article with impact factor
    Author
    Barigozzi, Matteo
    Brownlees, Christian
    Gallo, Giampiero
    Veredas, David
    Publication Year
    2014
    Journal
    Journal of Econometrics
    Publication Volume
    182
    Publication Issue
    2
    Publication Begin page
    364
    Publication End page
    384
    
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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.
    Keyword
    Accounting & Finance
    Knowledge Domain/Industry
    Accounting & Finance
    DOI
    10.1016/j.jeconom.2014.05.017
    URI
    http://hdl.handle.net/20.500.12127/5220
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.jeconom.2014.05.017
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