Dynamic Correlation and Risk Contagion Between “Black” Futures in China: A Multi-scale Variational Mode Decomposition Approach

[1]  He Nie,et al.  Co-movement of ASEAN stock markets: New evidence from wavelet and VMD-based copula tests , 2017 .

[2]  Ying Fan,et al.  The relationship between regional natural gas markets and crude oil markets from a multi-scale nonlinear Granger causality perspective , 2017 .

[3]  Rabeh Khalfaoui.  Oil–gold time varying nexus: A time–frequency analysis , 2018, Physica A: Statistical Mechanics and its Applications.

[4]  S. Raza,et al.  Electricity and growth nexus dynamics in Singapore : Fresh insights based on wavelet approach , 2017 .

[5]  Guangxi Cao,et al.  Detrended cross-correlation analysis approach for assessing asymmetric multifractal detrended cross-correlations and their application to the Chinese financial market , 2014 .

[6]  Xu Wang,et al.  The dependence structure in volatility between Shanghai and Shenzhen stock market in China: A copula-MEM approach , 2016 .

[7]  J. Beckmann,et al.  Volatility transmission in agricultural futures markets , 2014 .

[8]  Hangyong Lee,et al.  Testing for risk spillover between stock market and foreign exchange market in Korea , 2009 .

[9]  N. Antonakakis,et al.  Dynamic spillover effects in futures markets: UK and US evidence , 2014 .

[10]  Matteo Manera,et al.  Modelling Dynamic Conditional Correlations in Wti Oil Forward and Futures Returns , 2004 .

[11]  Paul H. Kupiec,et al.  Techniques for Verifying the Accuracy of Risk Measurement Models , 1995 .

[12]  Rudra Prosad Roy,et al.  Financial contagion and volatility spillover: An exploration into Indian commodity derivative market , 2017 .

[13]  R. Engle.  Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation , 1982 .

[14]  M. McAleer,et al.  Conditional Correlations and Volatility Spillovers between Crude Oil and Stock Index Returns , 2010 .

[15]  Heni Boubaker,et al.  A wavelet analysis of mean and volatility spillovers between oil and BRICS stock markets , 2017 .

[16]  Limin Du,et al.  Extreme risk spillovers between crude oil and stock markets , 2015 .

[17]  Yongmiao Hong,et al.  An empirical study on information spillover effects between the Chinese copper futures market and spot market , 2008 .

[18]  Andrea Ugolini,et al.  Wavelet-based test of co-movement and causality between oil and renewable energy stock prices , 2017 .

[19]  T. Bollerslev,et al.  Generalized autoregressive conditional heteroskedasticity , 1986 .

[20]  Guangxi Cao,et al.  Comparative analysis of grey detrended fluctuation analysis methods based on empirical research on China’s interest rate market , 2018, Physica A: Statistical Mechanics and its Applications.

[21]  Shian-Chang Huang,et al.  Wavelet-based multi-resolution GARCH model for financial spillover effects , 2011, Math. Comput. Simul..

[22]  W. Fuller,et al.  Distribution of the Estimators for Autoregressive Time Series with a Unit Root , 1979 .

[23]  François Benhmad.  Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach , 2012 .

[24]  Rania Jammazi,et al.  Time-varying causality between crude oil and stock markets: What can we learn from a multiscale perspective? , 2017 .

[25]  Zha Jin-shui.  The Extreme Risk Spillover Effect between International and Domestic Oil Markets , 2007 .

[26]  R. Engle.  Dynamic Conditional Correlation , 2002 .

[27]  Ling Tang,et al.  Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach , 2015 .

[28]  Mara Madaleno,et al.  Wavelet dynamics for oil-stock world interactions , 2014 .

[29]  M. T. M. Garcia,et al.  Risk contagion in the north-western and southern European stock markets , 2013 .

[30]  C. Green,et al.  Asymmetries, causality and correlation between FTSE100 spot and futures: A DCC-TGARCH-M analysis , 2012 .

[31]  Shiyun Li,et al.  Volatility Spillovers in the CSI300 Futures and Spot Markets in China: Empirical Study Based on Discrete Wavelet Transform and VAR-BEKK-bivariate GARCH Model , 2015, ITQM.

[32]  Changqing Luo,et al.  An Empirical Study on the Correlation Structure of Credit Spreads based on the Dynamic and Pair Copula Functions , 2016 .

[33]  Boqiang Lin,et al.  Promoting energy conservation in China's metallurgy industry , 2017 .

[34]  Safwan Mohd Nor,et al.  Interdependence and contagion among industry-level US credit markets: An application of wavelet and VMD based copula approaches , 2017 .

[35]  Shouyang Wang,et al.  Granger Causality in Risk and Detection of Extreme Risk Spillover Between Financial Markets , 2009 .

[36]  Bing Zhang,et al.  Recent hikes in oil-equity market correlations: Transitory or permanent? , 2016 .

[37]  S. Thorp,et al.  Financialization, Crisis and Commodity Correlation Dynamics , 2013 .

[38]  Théo Naccache,et al.  Oil price cycles and wavelets , 2011 .

[39]  Gilney Figueira Zebende,et al.  Oil and US dollar exchange rate dependence: A detrended cross-correlation approach , 2014 .

[40]  Lukas Vacha,et al.  Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis , 2012, 1201.4776.

[41]  Mohamed Boutahar,et al.  Analyzing volatility spillovers and hedging between oil and stock markets: Evidence from wavelet analysis , 2015 .

[42]  François Benhmad,et al.  Dynamic cyclical comovements between oil prices and US GDP: A wavelet perspective , 2013 .

[43]  D. Afanasyev,et al.  Fine structure of the price-demand relationship in the electricity market: multi-scale correlation analysis , 2015 .

[44]  Xueyong Liu,et al.  The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH–BEKK model , 2017 .

[45]  Yi-Ming Wei,et al.  Spillover effect of US dollar exchange rate on oil prices , 2008 .

[46]  Chaker Aloui,et al.  Sectoral energy consumption by source and output in the U.S.: New evidence from wavelet-based approach , 2018 .

[47]  Haizhong An,et al.  How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective , 2015 .

[48]  Sajid Ali,et al.  Interdependence between Greece and other European stock markets: A comparison of wavelet and VMD copula, and the portfolio implications , 2016 .

[49]  Ling-Yun He,et al.  Nonlinear bivariate dependency of price–volume relationships in agricultural commodity futures markets: A perspective from Multifractal Detrended Cross-Correlation Analysis , 2011 .

[50]  Boqiang Lin,et al.  Analysis of carbon emissions reduction of China's metallurgical industry , 2018 .

[51]  Dominique Zosso,et al.  Variational Mode Decomposition , 2014, IEEE Transactions on Signal Processing.

[52]  A. Rubia,et al.  Granger causality and systemic risk , 2015 .

[53]  Ling-Yun He,et al.  A new approach to quantify power-law cross-correlation and its application to commodity markets , 2011 .

[54]  Yudong Wang,et al.  The relationships between petroleum and stock returns: An asymmetric dynamic equi-correlation approach , 2016 .

[55]  H. Stanley,et al.  Extreme risk spillover effects in world gold markets and the global financial crisis , 2016 .

[56]  S. Hammoudeh,et al.  Oil and foreign exchange market tail dependence and risk spillovers for MENA, emerging and developed countries: VMD decomposition based copulas , 2017 .

[57]  Jian Zhou,et al.  Extreme risk spillover among international REIT markets , 2013 .

[58]  A generalized VECM/VAR-DCC/ADCC framework and its application in the Black-Litterman model: Illustrated with a China portfolio , 2018 .

[59]  S. Raza,et al.  Do commodities effectively hedge real estate risk? A multi-scale asymmetric DCC approach , 2018, Resources Policy.

[60]  R. Jammazi.  Oil shock transmission to stock market returns: Wavelet-multivariate Markov switching GARCH approach , 2012 .

[61]  Ling-Yun He,et al.  Multifractal Detrended Cross-Correlation Analysis of agricultural futures markets , 2011 .

[62]  Yongmiao Hong.  A test for volatility spillover with application to exchange rates , 2001 .