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...

Descripción completa

Detalles Bibliográficos
Autores principales: Sheraz, Muhammad, Dedu, Silvia, Preda, Vasile
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
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

Internet

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