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Good vs. Bad Volatility in Major Cryptocurrencies: The Dichotomy and Drivers of Connectedness

SYSNO ASEP	0577571
Document Type	V - Research Report
R&D Document Type	The record was not marked in the RIV
Title	Good vs. Bad Volatility in Major Cryptocurrencies: The Dichotomy and Drivers of Connectedness
Author(s)	Šíla, Jan (UTIA-B) Kočenda, Evžen (UTIA-B)_ORCID Kukačka, Jiří (UTIA-B)_{RID, ORCID} Krištoufek, Ladislav (UTIA-B)_{RID, ORCID}
Number of authors	4
Issue data	IES UK: IES UK, 2023
Series	IES Working Papers
Series number	24/2023
Number of pages	28 s.
Publication form	Online - E
Language	eng - English
Country	CZ - Czech Republic
Keywords	Volatility ; Dynamic connectedness ; Asymmetric effects ; Cryptocurrency
Subject RIV	AH - Economics
OECD category	Finance
R&D Projects	GA23-06606S GA ČR - Czech Science Foundation (CSF)
Institutional support	UTIA-B - RVO:67985556
Annotation	Cryptocurrencies exhibit unique statistical and dynamic properties compared to those of traditional financial assets, making the study of their volatility crucial for portfolio managers and traders. We investigate the volatility connectedness dynamics of a representative set of eight major crypto assets. Methodologically, we decompose the measured volatility into positive and negative components and employ the time-varying parameters vector autoregression (TVP-VAR) framework to show distinct dynamics associated with market booms and downturns. The results suggest that crypto connectedness reflects important events and exhibits more variable and cyclical dynamics than those of traditional financial markets. Periods of extremely high or low connectedness are clearly linked to specific events in the crypto market and macroeconomic or monetary history. Furthermore, existing asymmetry from good and bad volatility indicates that information about market downturns spills over substantially faster than news about comparable market surges. Overall, the connectedness dynamics are predominantly driven by fundamental crypto factors, while the asymmetry measure also depends on macro factors such as the VIX index and the expected inflation.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2024

Number of the records: 1