Diversification in crude oil and commodities: a comparative analysis
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This paper is an humble attempt to add value to the existing literature by empirically testing the "time-varying" and "scale dependent" volatilities of and correlations of the sample commodities. Particularly, by incorporating scale dependence, it is able to identify unique portfolio diversification opportunities for different set of investors bearing different investment horizons or holding periods. In order to address the research objectives, we have applied the vector error-correction test and several recently introduced econometric techniques such as the Maximum Overlap Discrete Wavelet Transform (MODWT), Continuous Wavelet Transform (CWT) and Multivariate GARCH - Dynamic Conditional Correlation. The data used in this paper is the daily data of seven commodities (crude oil, gas, gold, silver, copper, soybean and corn) prices from 1 January 2007 until 31 December 2013. Our findings tend to suggest that there is a theoretical relationship between the sample commodities (as evidenced in the cointegration tests) and that the crude oil, gas, gold and copper variables are leading the other commodities (as evidenced in the Vector Error-Correction models).
Commodity , Maximum Overlap Discrete Wavelet Transform (MODWT) , Continuous Wavelet Transform (CWT) , MGARCH-DCC , Diversification , Causality
Abdullah, A. M., & Mohammed Masih, A. M. (2016). Diversification in crude oil and commodities: a comparative analysis. Asian Academy of Management Journal of Accounting and Finance, 12(1), 101-128.
Universiti Sains Malaysia (USM)