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

ISSN Print: 2162-2434
ISSN Online: 2162-2442
www.scirp.net/journal/jmf
E-mail: [email protected]

Citations

"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):

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[2]	A Forecasting Model Approach: Investigating Calendar Anomalies and Volatility Patterns in the Cryptocurrency Market
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[3]	Modelling Extreme Tail Risk of Bitcoin Returns Using the Generalised Pareto Distribution
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[4]	Intraday Risk Management of Cryptocurrency Returns During 2020–2021 Upsurge: A Conditional EVT Approach
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[5]	Assessing the Risk Characteristics of the Cryptocurrency Market: A GARCH-EVT-Copula Approach
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[6]	Efficacy of GARCH-EVT Model in Intraday Risk Management: Evidence from Severely Pandemic-affected Countries
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[7]	Averting Disaster: Leverage Limits for Single-Stock Leveraged ETFs
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[3]	Risk Management in the Area of Bitcoin Market Development: Example from the USA Risks, 2024 DOI:10.3390/risks12040067

[4]	Exploring Calendar Anomalies and Volatility Dynamics in Cryptocurrencies: A Comparative Analysis of Day-of-the-Week Effects before and during the COVID-19 Pandemic Journal of Risk and Financial Management, 2024 DOI:10.3390/jrfm17080351

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

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

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