- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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1 Online-Ressource.
- Language
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Englisch
- Bibliographic citation
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Predicting volatility of bitcoin returns with ARCH, GARCH and EGARCH models ; volume:9 ; number:1 ; day:15 ; month:9 ; year:2023 ; pages:1-8 ; date:12.2023
Future Business Journal / Future University in Egypt ; 9, Heft 1 (15.9.2023), 1-8, 12.2023
- Classification
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Wirtschaft
- Creator
- Contributor
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SpringerLink (Online service)
- DOI
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10.1186/s43093-023-00255-8
- URN
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urn:nbn:de:101:1-2024020907582925471295
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:23 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Yildirim, Hakan
- Bekun, Festus Victor
- SpringerLink (Online service)
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What Drives Bitcoin Volatility?
Volatility forecasting accuracy for Bitcoin
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Is bitcoin a safe haven for Indian investors? A GARCH volatility analysis
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What Drives Bitcoin Volatility?
Volatility forecasting accuracy for Bitcoin
Return and volatility spillovers in equity markets: An investigation using various GARCH methodologies
Stochastic volatility and GARCH: Do squared end-of-day returns provide similar information?
Über funktionale ARCH- und GARCH-Zeitreihen
Support vector regression based GARCH model with application to forecasting volatility of financial returns
Support Vector Regression Based GARCH Model withApplication to Forecasting Volatility of Financial Returns
Bitcoin return volatility forecasting: A comparative study between GARCH and RNN
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Bitcoin, gold and the dollar: A GARCH volatility analysis
Is bitcoin a safe haven for Indian investors? A GARCH volatility analysis
FloGARCH: Realizing long memory and asymmetries in returns volatility
What Drives Bitcoin Volatility?
Volatility forecasting accuracy for Bitcoin
Return and volatility spillovers in equity markets: An investigation using various GARCH methodologies
Stochastic volatility and GARCH: Do squared end-of-day returns provide similar information?
Über funktionale ARCH- und GARCH-Zeitreihen
Support vector regression based GARCH model with application to forecasting volatility of financial returns