Estimating and Forecasting Large Panels of Volatilities with Approximate Dynamic Factor Models
Veredas, David Luciani, Matteo
Veredas, David
Luciani, Matteo
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Publication Type
Journal article
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Supervisor
Publication Year
2015
Journal
Journal of Forecasting
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Publication Volume
34
Publication Issue
3
Publication Begin page
163
Publication End page
176
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Abstract
We introduce an approximate dynamic factor model for modeling and forecasting large panels of realized volatilities. Since the model is estimated by means of principal components and low-dimensional maximum likelihood, it does not suffer from the curse of dimensionality. We apply the model to a panel of 90 daily realized volatilities pertaining to S&P 100 from January 2001 to December 2008. Results show that our model is able to capture the stylized facts of panels of volatilities (comovements, clustering, long memory, dynamic volatility, skewness and heavy tails), and that it performs fairly well in forecasting, in particular in periods of turmoil, in which it outperforms standard univariate benchmarks. Copyright © 2015?John Wiley & Sons
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Accounting & Finance