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Estimating dynamic copula dependence using intraday data

Estimating dynamic copula dependence using intraday data Abstract We estimate the dynamic daily dependence between assets by applying the Semiparametric Copula-Based Multivariate Dynamic (SCOMDY) model on intraday data. Using tick data of three stock returns of the period before and during the credit crisis, we find that our dependence estimator better captures the steep increase in dependence during the onset of the crisis as compared to other commonly used time-varying copula methods. Like other high-frequency estimators, we find that the dependence estimator exhibits long memory and forecast it using a HAR model. We show that for out-of-sample forecasts, our dependence estimator performs better than the constant estimator and other commonly used time-varying copula dependence estimators. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Studies in Nonlinear Dynamics & Econometrics de Gruyter

Estimating dynamic copula dependence using intraday data

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Publisher
de Gruyter
Copyright
Copyright © 2015 by the
ISSN
1081-1826
eISSN
1558-3708
DOI
10.1515/snde-2013-0123
Publisher site
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Abstract

Abstract We estimate the dynamic daily dependence between assets by applying the Semiparametric Copula-Based Multivariate Dynamic (SCOMDY) model on intraday data. Using tick data of three stock returns of the period before and during the credit crisis, we find that our dependence estimator better captures the steep increase in dependence during the onset of the crisis as compared to other commonly used time-varying copula methods. Like other high-frequency estimators, we find that the dependence estimator exhibits long memory and forecast it using a HAR model. We show that for out-of-sample forecasts, our dependence estimator performs better than the constant estimator and other commonly used time-varying copula dependence estimators.

Journal

Studies in Nonlinear Dynamics & Econometrics – de Gruyter

Published: Sep 1, 2015

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    Engle
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    Wiggins
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    Corsi
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    Øigard
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    Alexander
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    Barndorff
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    Wood
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    Barndorff
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    Patton
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    Martens
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    Corsi
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    Rodriguez
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    Drost
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    Barndorff
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    Harris
  • Modeling Tick - by - Tick Realized Correlations Data
    Audrino
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    Komunjer
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    Dias
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    Nelsen
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    Patton
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    Drost