Citation
Ruza, Nadiah and Hussain, Saiful Izzuan and Masseran, Nurulkamal
(2025)
Tail risk analysis of cryptocurrencies: insights from Extreme Value Theory.
In:
Globalization, Inclusive Growth, and Sustainable Futures in Southeast Asia.
Universiti Putra Malaysia Press, MALAYSIA, pp. 1-25.
ISBN 9786297840512
Abstract
This study employed Extreme Value Theory (EVT) to identify high-risk investment opportunities in the volatile crptocuurency market. EVT provides a more accurate risk assessment than traditional methods as it focuses on the tail distribution. The daily outcomes of six major cryptocurrencies were used for the analysis (Bitcoin, Ethereum, Ethereum Classic, Litecoin, Monero and Ripple). The time frame extends from January 2017 to December 2019 and includes major changes. Returns are fitted to the generalized Pareto distribution (GPD) in conjunction with the extreme value distribution. The results show that Bitcoin has a relatively low downside risk compared to other cryptocurrencies. Ethereum and Litecoin have more stable return patterns, suggesting a safer profile, while Ripple and Monero have the highest tail risk. These findings are consistent with other studies looking at the diversification and safe-haven properties of certain cryptocurrencies and highlight the importance of Extreme Value Theory (EVT) in evaluating extreme negative risk. The study is highly relevant for investors, portfolio managers and regulators to minimize volatility and reduce systemic risk in digital asset markets.
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Additional Metadata
| Item Type: |
Book Section
|
| Subject: |
Economics |
| Subject: |
Finance |
| Subject: |
Statistics |
| Divisions: |
School of Business and Economics |
| Publisher: |
Universiti Putra Malaysia Press |
| Keywords: |
Bitcoin; Cryptocurrency; Extreme returns; Extreme value theory |
| Sustainable Development Goals (SDGs): |
SDG 8: Decent Work and Economic Growth, SDG 9: Industry, Innovation and Infrastructure, SDG 11: Sustainable Cities and Communities |
| Depositing User: |
Ms. Nur Aina Ahmad Mustafa
|
| Date Deposited: |
31 Jul 2026 07:33 |
| Last Modified: |
31 Jul 2026 07:33 |
| URI: |
http://psasir.upm.edu.my/id/eprint/127588 |
| Statistic Details: |
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