Generalized method of moment estimation of multivariate multifractal models

Liu, Ruipeng and Lux, Thomas 2017, Generalized method of moment estimation of multivariate multifractal models, Economic Modelling, pp. 1-13, doi: 10.1016/j.econmod.2016.11.010.

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Title Generalized method of moment estimation of multivariate multifractal models
Author(s) Liu, RuipengORCID iD for Liu, Ruipeng
Lux, Thomas
Journal name Economic Modelling
Start page 1
End page 13
Total pages 13
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2017-01-06
ISSN 0264-9993
Keyword(s) Multivariate
Long memory
GMM estimation
Summary Multifractal processes have recently been introduced as a new tool for modeling the stylized facts of financial markets and have been found to consistently provide certain gains in performance over basic volatility models for a broad range of assets and for various risk management purposes. Due to computational constraints, multivariate extensions of the baseline univariate multifractal framework are, however, still very sparse so far. In this paper, we introduce a parsimoniously designed multivariate multifractal model, and we implement its estimation via a Generalized Methods of Moments (GMM) algorithm. Monte Carlo studies show that the performance of this GMM estimator for bivariate and trivariate models is similar to GMM estimation for univariate multifractal models. An empirical application shows that the multivariate multifractal model improves upon the volatility forecasts of multivariate GARCH over medium to long forecast horizons.
Notes In press
Language eng
DOI 10.1016/j.econmod.2016.11.010
Field of Research 1402 Applied Economics
1403 Econometrics
1502 Banking, Finance And Investment
Socio Economic Objective 970114 Expanding Knowledge in Economics
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016 Elsevier B.V.
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Document type: Journal Article
Collection: Department of Economics
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