Double-conditional smoothing of high-frequency volatility surface in a spatial multiplicative component GARCH with random effects
AbstractThis paper introduces a spatial framework for high-frequency returns and a faster double-conditional smoothing algorithm to carry out bivariate kernel estimation of the volatility surface. A spatial multiplicative component GARCH with random effects is proposed to deal with multiplicative random effects found from the data. It is shown that the probabilistic properties of the stochastic part and the asymptotic properties of the kernel volatility surface estimator are all strongly affected by the multiplicative random effects. Data example shows that the volatility surface before, during and after the 2008 financial crisis forms a volatility saddle.
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Bibliographic InfoPaper provided by University of Paderborn, CIE Center for International Economics in its series Working Papers with number 65.
Length: 28 pages
Date of creation: Aug 2013
Date of revision:
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Web page: http://www.uni-paderborn.de/fakultaeten/wiwi/department4/cie/
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Spatial multiplicative component GARCH; high-frequency returns; double-conditional smoothing; multiplicative random effect; volatility arch; volatility saddle.;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-09-06 (All new papers)
- NEP-ECM-2013-09-06 (Econometrics)
- NEP-ETS-2013-09-06 (Econometric Time Series)
- NEP-MST-2013-09-06 (Market Microstructure)
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