ORCID
Jules Clement Mba 0000-0001-6462-6385
Jenipher Mutale 0009-0009-1605-324X
Ehounou Serge Eloge Florentin Angaman 0009-0009-1605-324X
Keywords
estimator, lead-lag effect, volatility point change, quasi-maximum likelihood
Abstract
This study investigates the lead-lag relationships and volatility dynamics among four major cryptocurrencies – Bitcoin, Ethereum, Solana, and Polygon – during the turbulent year of 2022. We address three primary research questions: (1) To what extent do lead-lag relationships exist among major cryptocurrencies, and how do they challenge or support the notion of market efficiency in the crypto space? (2) How do volatility change points in different cryptocurrencies relate to each other and to major market events? (3) How can the identification of lead‑lag relationships and volatility change points inform cryptocurrency investment strategies and risk management practices? Using a continuous-time lead-lag estimator and a non-parametric volatility change point detection method, we analysed daily price data for the year 2022. Our findings reveal complex lead-lag dynamics, with Polygon unexpectedly emerging as a leading indicator despite its smaller market capitalisation. This challenges the conventional assumption that larger cryptocurrencies like Bitcoin consistently lead market movements, indicating potential inefficiencies in information transmission within the crypto market. The volatility change point analysis identifies varying frequencies of volatility shifts across the cryptocurrencies, with Polygon experiencing the most frequent changes (7) and Bitcoin the least (3). We observe both clustering of volatility change points around significant market events and variations reflecting the unique characteristics of each cryptocurrency. Our results suggest that while the cryptocurrency market shows a high degree of interconnectedness, it also exhibits nuanced dynamics that could be exploited for more effective hedging strategies and improved risk assessment. The study highlights the rapid evolution of the cryptocurrency ecosystem, where technological factors and market-specific events can significantly influence price dynamics and volatility patterns. This research contributes to the growing body of literature on cryptocurrency market behaviour, offering insights into the complex dynamics of this emerging asset class during a period of significant market stress. Our findings have implications for investors, regulators, and researchers seeking to understand and navigate the rapidly evolving cryptocurrency landscape.
Acknowledgments
Funding
The cost of editing selected articles published in the Journal of Banking and Financial Economics in the 2022– 2024 is covered by funding under the program “Development of Scientific Journals” of the Ministry of Education and Science under agreement No. RCN/SN/0321/2021/1. Task title: “Verification and correction of scientific articles and their abstracts”. Funding value: 21 197,00 PLN; The task consists of professional editing of articles published in English.
Declaration of Conflicting Interests
The author declared no potential conflicts of interest with respect to the research, authorship, and publication of the article.
Declaration About the Scope of AI Utilisation
The authors did not use an AI tool in the preparation of the article.
Recommended Citation
Mba, J. C., Mutale, J., & Angaman, E. (2024). Lead-lag and Volatility Point Change Estimations for Cryptocurrencies. Journal of Banking and Financial Economics, 2024(1), 54-76. https://doi.org/10.7172/2353-6845.jbfe.2024.1.5
First Page
54
Last Page
76
Page Count
23
Received Date
05.12.2023
Revised Date
03.09.2024
Accept Date
16.09.2024
Online Available Date
05.11.2024
DOI
10.7172/2353-6845.jbfe.2024.1.5
JEL Code
G15, C22, C58, E44
Publisher
University of Warsaw