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Modelling Conditional Correlations in the Volatility of Asian Rubber Spot and Futures Returns

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  • Chia-Lin Chang
  • Thanchanok Khamkaew
  • Michael McAleer

    ()
    (University of Canterbury)

  • Roengchai Tansuchat

Abstract

Asia is presently the most important market for the production and consumption of natural rubber. World prices of rubber are not only subject to changes in demand, but also to speculation regarding future markets. Japan and Singapore are the major futures markets for rubber, while Thailand is one of the world’s largest producers of rubber. As rubber prices are influenced by external markets, it is important to analyse the relationship between the relevant markets in Thailand, Japan and Singapore. The analysis is conducted using several alternative multivariate GARCH models. The empirical results indicate that the constant conditional correlations arising from the CCC model lie in the low to medium range. The results from the VARMA-GARCH model and the VARMA-AGARCH model suggest the presence of volatility spillovers and asymmetric effects of positive and negative return shocks on conditional volatility. Finally, the DCC model suggests that the conditional correlations can vary dramatically over time. In general, the dynamic conditional correlations in rubber spot and futures returns shocks can be independent or interdependent.

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File URL: http://www.econ.canterbury.ac.nz/RePEc/cbt/econwp/1038.pdf
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Bibliographic Info

Paper provided by University of Canterbury, Department of Economics and Finance in its series Working Papers in Economics with number 10/38.

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Length: 20 pages
Date of creation: 01 Jan 2010
Date of revision:
Handle: RePEc:cbt:econwp:10/38

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Keywords: Multivariate GARCH; volatility spillovers; conditional correlations; spot returns; futures returns;

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  1. Shiqing Ling & Michael McAleer, 2001. "Asymptotic Theory for a Vector ARMA-GARCH Model," ISER Discussion Paper 0549, Institute of Social and Economic Research, Osaka University.
  2. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-50, July.
  3. Nicholas Apergis & Anthony Rezitis, 2003. "Food price volatility and macroeconomic factor volatility: 'heat waves' or 'meteor showers'?," Applied Economics Letters, Taylor & Francis Journals, vol. 10(3), pages 155-160.
  4. Jae H. Kim & Hristos Doucouliagos, 2005. "Realized Volatility and Correlation in Grain Futures Markets: Testing for Spill-Over Effects," Monash Econometrics and Business Statistics Working Papers 22/05, Monash University, Department of Econometrics and Business Statistics.
  5. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(01), pages 232-261, February.
  6. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
  7. Michael McAleer & Suhejla Hoti & Felix Chan, 2009. "Structure and Asymptotic Theory for Multivariate Asymmetric Conditional Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 28(5), pages 422-440.
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Cited by:
  1. Chang, C-L. & McAleer, M.J. & Tansuchat, R., 2009. "Modelling conditional correlations for risk diversification in crude oil markets," Econometric Institute Research Papers EI 2009-11, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  2. Rabeh Khalfaoui & Mohammed Boutahar, 2012. "Portfolio Risk Evaluation An Approach Based on Dynamic Conditional Correlations Models and Wavelet Multi-Resolution Analysis," AMSE Working Papers 1208, Aix-Marseille School of Economics, Marseille, France.
  3. Yen-Hsien Lee, 2014. "An international analysis of REITs and stock portfolio management based on dynamic conditional correlation models," Financial Markets and Portfolio Management, Springer, vol. 28(2), pages 165-180, May.

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