A local dynamic conditional correlation model
AbstractThis paper introduces the idea that the variances or correlations in financial returns may all change conditionally and slowly over time. A multi-step local dynamic conditional correlation model is proposed for simultaneously modelling these components. In particular, the local and conditional correlations are jointly estimated by multivariate kernel regression. A multivariate k-NN method with variable bandwidths is developed to solve the curse of dimension problem. Asymptotic properties of the estimators are discussed in detail. Practical performance of the model is illustrated by applications to foreign exchange rates.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 1592.
Date of creation: 2006
Date of revision:
Local and conditional correlations; multivariate nonparametric ARCH; multivariate kernel regression; multivariate k-NN method;
Find related papers by JEL classification:
- G0 - Financial Economics - - General
- G1 - Financial Economics - - General Financial Markets
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-02-10 (All new papers)
- NEP-ECM-2007-02-10 (Econometrics)
- NEP-ETS-2007-02-10 (Econometric Time Series)
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