The Predictive Performance of Extreme Value Analysis Based-Models in Forecasting the Volatility of Cryptocurrencies

Journals Menu

Follow SCIRP

ISSN Print: 2162-2434
ISSN Online: 2162-2442
www.scirp.org/journal/jmf
E-mail: jmf@scirp.org

"The Predictive Performance of Extreme Value Analysis Based-Models in Forecasting the Volatility of Cryptocurrencies"
written by Cyprian Omari, Anthony Ngunyi,
published by Journal of Mathematical Finance, Vol.11 No.3, 2021

has been cited by the following article(s):

[1]	Assessing the Risk Characteristics of the Cryptocurrency Market: A GARCH-EVT-Copula Approach
	Journal of Risk and Financial Management, 2022

[2]	Efficacy of GARCH-EVT Model in Intraday Risk Management: Evidence from Severely Pandemic-affected Countries
	Global Business Review, 2022

[3]	Averting Disaster: Leverage Limits for Single-Stock Leveraged ETFs
	Journal of Mathematical Finance, 2022

[1]	Cryptocurrencies - Financial Technologies of the Future [Working Title] 2024 DOI:10.5772/intechopen.1003794

[2]	Intraday Risk Management of Cryptocurrency Returns During 2020–2021 Upsurge: A Conditional EVT Approach Business Perspectives and Research, 2023 DOI:10.1177/22785337221148878

[3]	Efficacy of GARCH-EVT Model in Intraday Risk Management: Evidence from Severely Pandemic-affected Countries Global Business Review, 2022 DOI:10.1177/09721509221104848

[4]	Assessing the Risk Characteristics of the Cryptocurrency Market: A GARCH-EVT-Copula Approach Journal of Risk and Financial Management, 2022 DOI:10.3390/jrfm15080346

Follow SCIRP