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Entropy 2016, 18(5), 170;

Forecasting Energy Value at Risk Using Multiscale Dependence Based Methodology

School of Business, Hunan University of Science and Technology, Xiangtan 411201, China
School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China
School of Economics and Management, Shanghai Maritime University, Shanghai 201306, China
Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
International Business School, Shaanxi Normal University, Xi’an 710119, China
Author to whom correspondence should be addressed.
Academic Editors: J.A. Tenreiro Machado and António M. Lopes
Received: 6 February 2016 / Revised: 19 April 2016 / Accepted: 20 April 2016 / Published: 4 May 2016
(This article belongs to the Special Issue Computational Complexity)
View Full-Text   |   Download PDF [492 KB, uploaded 4 May 2016]   |  


In this paper, we propose a multiscale dependence-based methodology to analyze the dependence structure and to estimate the downside portfolio risk measures in the energy markets. More specifically, under this methodology, we formulate a new bivariate Empirical Mode Decomposition (EMD) copula based approach to analyze and model the multiscale dependence structure in the energy markets. The proposed model constructs the Copula-based dependence structure formulation in the Bivariate Empirical Mode Decomposition (BEMD)-based multiscale domain. Results from the empirical studies using the typical Australian electricity daily prices show that there exists a multiscale dependence structure between different regional markets across different scales. The proposed model taking into account the multiscale dependence structure demonstrates statistically significantly-improved performance in terms of accuracy and reliability measures. View Full-Text
Keywords: energy markets; portfolio value at risk; copula GARCH model; Bivariate Empirical Mode Decomposition (BEMD); entropy energy markets; portfolio value at risk; copula GARCH model; Bivariate Empirical Mode Decomposition (BEMD); entropy

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He, K.; Zha, R.; Chen, Y.; Lai, K.K. Forecasting Energy Value at Risk Using Multiscale Dependence Based Methodology. Entropy 2016, 18, 170.

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