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Nonlinear dependence and information spillover between electricity and fuel source markets: New evidence from a multi-scale analysis

Tongshui Xia, Qiang Ji () and Jiang-Bo Geng

Physica A: Statistical Mechanics and its Applications, 2020, vol. 537, issue C

Abstract: This study identifies nonlinear causality between electricity and fuel source returns based on a new multi-scale framework. The empirical results show that the causality direction between electricity and fuel returns behaves differently across time scales. Generally speaking, linear or nonlinear causality relationship between the electricity and gas markets exists for most time scales. The study also explores the magnitude of the feedback effects between electricity and fuel returns using the connectedness network. The results show that the degree of feedback effects between the electricity and fuel markets is relatively weak at the original data level. Across various time scales, there is positive but weak information spillover from the oil and uranium to electricity markets and reciprocal information spillover between the electricity and gas/coal markets at most time horizons. The information spillover from the gas to electricity returns is relatively strong.

Keywords: Electricity prices; Fuel prices; Ensemble empirical mode decomposition; Nonlinear causality test; Connectedness network (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1016/j.physa.2019.122298

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