Dynamic distributions and changing copulas
AbstractA copula models the relationships between variables independently of their marginal distributions. When the variables are time series, the copula may change over time. A statistical framework is suggested for tracking these changes over time. When the marginal distribu- tions change, pre-filtering is necessary before constructing the indicator variables on which the tracking of the copula is based. This entails solving an even more basic problem, namely estimating time-varying quantiles. The methods are applied to the Hong Kong and Korean stock market indices. Some interesting movements are detected, particularly after the attack on the Hong Kong dollar in 1997.
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Bibliographic InfoPaper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0839.
Date of creation: Sep 2008
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Concordance; contagion; exponentially weighted moving average; quantiles; signal extraction; tail dependence.;
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-10-28 (All new papers)
- NEP-ECM-2008-10-28 (Econometrics)
- NEP-ETS-2008-10-28 (Econometric Time Series)
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