Cargando…
Volatility Dynamics of Non-Linear Volatile Time Series and Analysis of Information Flow: Evidence from Cryptocurrency Data
This paper aims to empirically examine long memory and bi-directional information flow between estimated volatilities of highly volatile time series datasets of five cryptocurrencies. We propose the employment of Garman and Klass (GK), Parkinson’s, Rogers and Satchell (RS), and Garman and Klass-Yang...
Autores principales: | Sheraz, Muhammad, Dedu, Silvia, Preda, Vasile |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9601717/ https://www.ncbi.nlm.nih.gov/pubmed/37420430 http://dx.doi.org/10.3390/e24101410 |
Ejemplares similares
-
Cryptocurrency volatility markets
por: Woebbeking, Fabian
Publicado: (2021) -
The impact of volatility on the functionality of cryptocurrencies
por: Altamirano Vásquez, Margarita, et al.
Publicado: (2020) -
COVID-19 and cryptocurrency volatility: Evidence from asymmetric modelling
por: Apergis, Nicholas
Publicado: (2022) -
Volatility Interdependence Between Cryptocurrencies, Equity, and Bond Markets
por: Harb, Etienne, et al.
Publicado: (2022) -
Investigating the relationship between volatilities of cryptocurrencies and other financial assets
por: Ghorbel, Achraf, et al.
Publicado: (2021)