Conditional dependence among oil, gold and U.S. dollar exchange rates: a copula-GARCH approach. (English) Zbl 1479.91423
Sriboonchitta, Songsak (ed.) et al., Behavioral predictive modeling in economics. Cham: Springer. Stud. Comput. Intell. 897, 203-218 (2021).
Summary: This paper investigates the dependence structure among nominal crude oil (WTI), gold, and specific U.S. dollar against four major currencies (euro, British pound, Japanese yen and Canadian dollar) on a daily basis over the last decade. In order to capture the tail dependence between commodity market and USD exchange rates, we apply both bivariate zero tail and tail copulas, combined with the AR-GARCH marginal distribution for gold, oil and exchange rates daily returns. The primary findings are as follows. Firstly, based on the concordance and correlation coefficient, we find that there is a positive correlation between gold and crude oil prices, and a negative dependence between gold and currencies as well as oil and currencies. Secondly, the crude oil price can be viewed as a short term indicator in the exchange rates movement; the crude oil price also can be viewed as a short term descend indicator of gold price, while the gold price is an short term rise indicator of oil price. Thirdly, small degree of conditional extreme tail dependence for all considered pairs are observed. Our results provide useful information in portfolio diversification, asset allocation and risk management for investors and researchers.
For the entire collection see [Zbl 1470.91007].
For the entire collection see [Zbl 1470.91007].
MSC:
| 91G30 | Interest rates, asset pricing, etc. (stochastic models) |
| 62M10 | Time series, auto-correlation, regression, etc. in statistics (GARCH) |
| 62H05 | Characterization and structure theory for multivariate probability distributions; copulas |
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