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Symmetric and asymmetric nonlinear causalities between oil prices and the U.S. economic sectors

Jinghua Wang () and Geoffrey Ngene ()
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Jinghua Wang: Pacific Lutheran University
Geoffrey Ngene: Mercer University

Review of Quantitative Finance and Accounting, 2018, vol. 51, issue 1, 199-218

Abstract: Abstract This study investigates the causal dynamics of the U.S. sector price changes and oil price changes using the symmetric nonlinear and asymmetric nonlinear causality tests. We find a unidirectional causality from each sector to the oil market using the Granger and MWald linear causality tests. However, the symmetric nonlinear and asymmetric nonlinear causality for negative price changes tests yield unidirectional causality from the oil to the sector price changes which sharply contrast the evidence using the linear models. We find bidirectional causality using the asymmetric nonlinear test for positive price changes, suggesting temporal, dual and nonlinear information flow during bull markets. Our results from the nonlinear and asymmetric causality tests remain robust after accounting for structural breaks. The empirical findings unravel nonlinear interactions between sector price and oil price changes as well as the importance of signs of changes in the interacting variables, implying oil returns may need to be priced when forecasting sector returns.

Keywords: Sectors; Oil prices; Causality; Symmetric; Asymmetric; Nonlinear (search for similar items in EconPapers)
JEL-codes: C22 C52 G10 G15 Q40 Q43 (search for similar items in EconPapers)
Date: 2018
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