Testing for Nonlinear Granger Causality Between Bitcoin Market and Crude Oil Market

Fang Wang () and Menggang Li ()
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Fang Wang: Beijing Laboratory of National Economic Security Early-warning Engineering Beijing Jiaotong University
Menggang Li: Beijing Laboratory of National Economic Security Early-warning Engineering Beijing Jiaotong University

A chapter in IEIS 2023, 2024, pp 36-45 from Springer

Abstract: Abstract This paper investigates the causality between bitcoin market and WTI crude oil market through multi-scale analysis and causality testing. The complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method is employed to decompose the two price series at different time-scales. In causality testing, a nonlinear Granger causality test is formulated to investigate the relationship among each pair of matched components. And we also divide the information components of different series into high-frequency components, low-frequency components and long-term trend according to the Fine-to-coarse reconstruction. In the end, a set of hypothetical scenarios are created and a statistical test for causality is performed.

Keywords: time-scale analysis; CEEMDAN; nonlinear Granger causality test; bitcoin market; WTI crude oil market (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-981-97-4137-3_4

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DOI: 10.1007/978-981-97-4137-3_4

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