Good and bad self-excitation: Asymmetric self-exciting jumps in Bitcoin returns

Chuanhai Zhang, Zhengjun Zhang, Mengyu Xu and Zhe Peng

Economic Modelling, 2023, vol. 119, issue C

Abstract: Recent studies find jumps in cryptocurrencies such as Bitcoin, however, little is known about the behavior of self-exciting jump clustering. Using high frequency data, we investigate the characteristics of self-exciting jumps in Bitcoin returns. First, we find strong asymmetry in self-excitation, which is triggered, on average, more by bad (negative) jumps than good (positive) jumps. Second, when discriminating bear and bull markets, we find negative asymmetry in bear markets but no evidence of positive asymmetry in bull markets. Third, self-excitation has asymmetric aftershock effects, where aftershocks triggered by bad self-excitation are more persistent than aftershocks triggered by good self-excitation. The findings presented in this paper have important implications in risk management and asset pricing for Bitcoin.

Keywords: Bitcoin; Self-excitation; Asymmetric effects; Good jumps; bad jumps; High frequency data (search for similar items in EconPapers)
JEL-codes: C12 C14 C32 G14 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:119:y:2023:i:c:s0264999322003613

DOI: 10.1016/j.econmod.2022.106124

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