Cryptocurrency trading and downside risk

Simple item page
dc.contributor.authorIqbal, Farhat
dc.contributor.authorZahid, Mamoona
dc.contributor.authorKoutmos, Dimitrios
dc.date.accessioned2023-09-07T17:35:19Z
dc.date.available2023-09-07T17:35:19Z
dc.date.issued2023-07-06
dc.description.abstractSince the debut of cryptocurrencies, particularly Bitcoin, in 2009, cryptocurrency trading has grown in popularity among investors. Relative to other conventional asset classes, cryptocurrencies exhibit high volatility and, consequently, downside risk. While the prospects of high returns are alluring for investors and speculators, the downside risks are important to consider and model. As a result, the profitability of crypto market operations depends on the predictability of price volatility. Predictive models that can successfully explain volatility help to reduce downside risk. In this paper, we investigate the value-at-risk (VaR) forecasts using a variety of volatility models, including conditional autoregressive VaR (CAViaR) and dynamic quantile range (DQR) models, as well as GARCH-type and generalized autoregressive score (GAS) models. We apply these models to five of some of the largest market capitalization cryptocurrencies (Bitcoin, Ethereum, Ripple, Litecoin, and Steller, respectively). The forecasts are evaluated using various backtesting and model confidence set (MCS) techniques. To create the best VaR forecast model, a weighted aggregative technique is used. The findings demonstrate that the quantile-based models using a weighted average method have the best ability to anticipate the negative risks of cryptocurrencies.en_US
dc.description.sponsorshipThis research received no external funding.en_US
dc.identifier.citationIqbal, Farhat, Mamoona Zahid, and Dimitrios Koutmos. 2023. Cryptocurrency Trading and Downside Risk. Risks 11: 122. https://doi.org/10.3390/risks 11070122en_US
dc.identifier.doihttps://doi.org/10.3390/risks11070122
dc.identifier.urihttps://hdl.handle.net/1969.6/97352
dc.language.isoen_USen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectcryptocurrenciesen_US
dc.subjectdownside risken_US
dc.subjectVaR modelsen_US
dc.subjectweighted aggregative approachen_US
dc.titleCryptocurrency trading and downside risken_US
dc.typeArticleen_US

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
Cryptocurrency Trading and Downside Risk.pdf
Size:
996.81 KB
Format:
Adobe Portable Document Format
Description:
Download

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.72 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

COB Faculty Works