Volatility Dynamics of Non-Linear Volatile Time Series and Analysis of Information Flow: Evidence from Cryptocurrency Data

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...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy:	Muhammad Sheraz, Silvia Dedu, Vasile Preda
Format:	Artykuł
Język:	English
Wydane:	MDPI AG 2022-10-01
Seria:	Entropy
Hasła przedmiotowe:	volatility transfer entropy mutual information flow of information financial time series
Dostęp online:	https://www.mdpi.com/1099-4300/24/10/1410

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