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Abstract

This 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.



Item Type: MPRA Paper -

Institution: Maxwell Institute for Mathematical Sciences, Heriot-Watt University-

Original Title: A local dynamic conditional correlation model-

Language: English-

Keywords: Local and conditional correlations; multivariate nonparametric ARCH; multivariate kernel regression; multivariate k-NN method-

Subjects: G - Financial Economics > G0 - GeneralG - Financial Economics > G1 - General Financial MarketsC - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models-





Author: Feng, Yuanhua

Source: https://mpra.ub.uni-muenchen.de/1592/







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