HMM in Dynamic HAC Models

SFB 649 Discussion Paper 2012-001

29 Pages Posted: 7 Jan 2017

See all articles by Wolfgang K. Härdle

Wolfgang K. Härdle

Humboldt University of Berlin - Institute for Statistics and Econometrics; Xiamen University - Wang Yanan Institute for Studies in Economics (WISE); Charles University; Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Ostap Okhrin

Humboldt University of Berlin - School of Business and Economics

Weining Wang

Humboldt University of Berlin

Date Written: January 2, 2012

Abstract

Understanding the dynamics of high dimensional non-normal dependency structure is a challenging task. This research aims at attacking this problem by building up a hidden Markov model (HMM) for Hierarchical Archimedean Copulae (HAC), where the HAC represent a wide class of models for high dimensional dependency, and HMM is a statistical technique to describe time varying dynamics. HMM applied to HAC provide flexible modeling for high dimensional non Gaussian time series. Consistency results for both parameters and HAC structures are established in an HMM framework. The model is calibrated to exchange rate data with a VaR application, where the model’s performance is compared with other dynamic models, and in the second application we simulate rainfall process.

Keywords: Hidden Markov model, Hierarchical Archimedean Copulae, Multivariate Distribution

JEL Classification: C13, C14, G50

Suggested Citation

Härdle, Wolfgang K. and Okhrin, Ostap and Wang, Weining, HMM in Dynamic HAC Models (January 2, 2012). SFB 649 Discussion Paper 2012-001. Available at SSRN: https://ssrn.com/abstract=2894223 or http://dx.doi.org/10.2139/ssrn.2894223

Wolfgang K. Härdle (Contact Author)

Humboldt University of Berlin - Institute for Statistics and Econometrics ( email )

Unter den Linden 6
Berlin, D-10099
Germany

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE) ( email )

A 307, Economics Building
Xiamen, Fujian 10246
China

Charles University ( email )

Celetná 13
Dept Math Physics
Praha 1, 116 36
Czech Republic

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Unter den Linden 6
Berlin, D-10099
Germany

Ostap Okhrin

Humboldt University of Berlin - School of Business and Economics ( email )

Unter den Linden 6
Berlin, AK Berlin 10099
Germany

Weining Wang

Humboldt University of Berlin ( email )

Unter den Linden 6
Berlin, AK Berlin 10099
Germany

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