Empirical analysis of oil risk-minimizing portfolios: the DCC-GARCH-MODWT approach
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This paper strives to analyze hedging strategies between Brent oil and six other heterogeneous assets - American ten-year bonds, US dollars, gold, natural gas futures, corn futures, and Europe, Australasia and Far East exchange-traded funds (EAFE-ETFs) - observing five wavelet time horizons and considering three different risk metrics: variance, value-at-risk (VaR) and conditional value-at-risk (CVaR). We construct two-asset portfolios, whereby conditional variances and covariances are obtained via a bivariate rolling dynamic conditional correlation-generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model. Results indicate that gold is the best combination with Brent for minimum-variance investors, while the Brent-natural gas pair produces the worst minimum-variance results due to the very high unconditional variance of gas. As for VaR and CVaR results, we find that Brent with gold gives relatively good outcomes, but the portfolio with gas heavily outperforms the por...tfolio with gold when one views longer time horizons. This happens because the Brent-gas portfolio has very low skewness and kurtosis on longer time horizons compared with the unhedged portfolio, and these characteristics favor good VaR and CVaR results. These findings could help global portfolio managers and investors who seek various ways to diversify their Brent oil investments, who act on different time horizons, and who target different risk-minimizing goals.
Keywords:oil hedging / portfolio / risk-minimizing metrics / heterogeneous assets / wavelet / rolling DCC-GARCH model
Source:Journal of Risk, 2020, 22, 3, 65-91
- Incisive Media, London