Modelling conditional correlations in the volatility of Asian rubber spot and futures returns
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 of Bollerslev (1990) lie in the low to medium range. The results from the VARMA-GARCH model of Ling and McAleer (2003) and the VARMA-AGARCH model of McAleer et al. (2009) suggest the presence of volatility spillovers and asymmetric effects of positive and negative return shocks on conditional volatility. Finally, the DCC model of Engle (2002) 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.
|Keywords||Asian rubber prices, conditional correlations, futures returns, multivariate GARCH, spot returns, volatility spillovers|
|JEL||Time-Series Models; Dynamic Quantile Regressions (jel C22), Time-Series Models; Dynamic Quantile Regressions (jel C32), Financial Forecasting (jel G17), Financing Policy; Capital and Ownership Structure (jel G32), Agricultural Finance (jel Q14)|
|Publisher||Erasmus School of Economics (ESE)|
|Series||Econometric Institute Research Papers|
|Journal||Report / Econometric Institute, Erasmus University Rotterdam|
Khamkaew, T, Tansuchat, R, Chang, C-L, & McAleer, M.J. (2009). Modelling conditional correlations in the volatility of Asian rubber spot and futures returns (No. EI 2009-34). Report / Econometric Institute, Erasmus University Rotterdam (pp. 1–18). Erasmus School of Economics (ESE). Retrieved from http://hdl.handle.net/1765/17297