Artikel
Performance analysis of gold- and fiat-backed cryptocurrencies: Risk-based choice for a portfolio
This study aims to investigate the performance and behavior of fiat- and gold-backed cryptocurrencies to support stakeholders through the preparation of a portfolio from 1 January 2021 to 30 June 2022. Moreover, while searching for a hedge or a diversifier to construct a less risky portfolio with handsome returns, the prices of fiat-backed cryptocurrencies report high fluctuation during the sample period. ARIMA-EGARCH models have been employed to examine the volatile behavior of these cryptocurrencies. The empirical results are mixed as Bitcoin has been highly volatile during the economic recession. Due to its volatility, investors seek a safe haven. Ripple, on the other hand, shows low risk compared to Bitcoin. The results further reveal that PAX gold is more volatile than PM gold, while Bitcoin, being a highly traded cryptocurrency, is significantly correlated to other cryptocurrencies. The implications of this research showing the volatility of gold- and fiat-backed cryptocurrencies are equally important to stakeholders, such as investors, and policymakers.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 16 ; Year: 2023 ; Issue: 2 ; Pages: 1-15
- Klassifikation
-
Management
- Thema
-
ARIMA-EGARCH model
fiat-backed cryptocurrencies
gold-backed cryptocurrencies
volatility
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Irfan, Muhammad
Rehman, Mubeen Abdur
Nawazish, Sarah
Yu, Hao
- Ereignis
-
Veröffentlichung
- (wer)
-
MDPI
- (wo)
-
Basel
- (wann)
-
2023
- DOI
-
doi:10.3390/jrfm16020099
- Handle
- Letzte Aktualisierung
- 10.03.2025, 11:44 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft.
Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Irfan, Muhammad
- Rehman, Mubeen Abdur
- Nawazish, Sarah
- Yu, Hao
- MDPI
Entstanden
- 2023
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