The relationship between Bitcoin returns, volatility and volume: asymmetric GARCH modeling
Journal of Enterprise Information Management
ISSN: 1741-0398
Article publication date: 17 April 2020
Issue publication date: 24 November 2022
Abstract
Purpose
To show that when volume of trades is taken into consideration, Bitcoin does not seem as volatile as it claimed. Further, to study the relationship between Bitcoin trading volume, volatility and returns, and the asymmetry in response to economic information for the period from July 2010 to November 2017.
Design/methodology/approach
Comparison of Bitcoin price volatility with that of six currencies and gold. We repeat the analysis using returns divided by volume. We examine the relationship between volume, returns and volatility, and the asymmetry of the reaction of the volatility to economic news using asymmetric models (EGARCH) run for four meaningful distinct time periods/subsamples.
Findings
Positive and significant relationship between (1) volume and volatility after 2013 (year Bitcoin became popular) and (2) volume and returns before the Mt. Gox hack. During the euphoric period, starting at the beginning of 2013 until the Mt. Gox hack, unexpected increases in Bitcoin returns increased Bitcoin volatility more than unexpected, equally sized decreases (asymmetry).
Originality/value
We take into consideration the volume of trades to show that Bitcoin volatility seems high because of the low volume of trades. We study an extended time period, not covered by other studies. We divide our sample into four meaningful time periods based on important events in Bitcoin market history. This is important for a new market such as the Bitcoin market; the relationships under study are very important in markets where participants rely on technical analysis in the absence of reliable fundamental methodology to measure the intrinsic value of the asset.
Keywords
Citation
Sapuric, S., Kokkinaki, A. and Georgiou, I. (2022), "The relationship between Bitcoin returns, volatility and volume: asymmetric GARCH modeling", Journal of Enterprise Information Management, Vol. 35 No. 6, pp. 1506-1521. https://doi.org/10.1108/JEIM-10-2018-0228
Publisher
:Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited