Volatility estimation for Bitcoin: A comparison of GARCH models

By Paraskevi Katsiampa. 2017

995 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Information Systems

View Paper: https://www.semanticscholar.org/paper/886e6a9047853392a0e695b1f7f466a0de1fc158

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Information Systems

Citations in the corpus

An empirical investigation of volatility dynamics in the cryptocurrency market (2019, positive): “Katsiampa (2017) compared several GARCH-type models and found that the Component CARCH model, which consists of both a short-run and a long-run component of conditional variance, fits Bitcoin price returns better than the other GARCH-type models considered in her study.”
An Empirical Study on Modeling and Prediction of Bitcoin Prices With Bayesian Neural Networks Based on Blockchain Information (2018, methodology): “Generalized Autoregressive Conditional Heteroskedasticity (GARCH) volatility analysis is performed to explore the time series of Bitcoin price [2], [3].”
Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance (2018, positive): “Conrad et al. (2018), Catania & Grassi (2017), Dyhrberg (2016), Katsiampa (2017), and Chu et al. (2017) use univariate volatility models to analyze the volatility structure of Bitcoin and other cryptocurrencies.”
Return, volatility and shock spillovers of Bitcoin with energy and technology companies (2018, result): “Our study expands previous efforts in cryptocurrencies’ literature that analyze the diversification benefits and interdependencies with financial assets (Dyhrberg, 2016; Ciaian et al., 2018; Corbet et al., 2018) and explore Bitcoin returns and volatility (Balcilar et al., 2017; Katsiampa, 2017).”
Do cryptocurrencies and traditional asset classes influence each other? (2019, background): “Rapid development of cryptocurrencies attracted lot of attention in recent research (Brandvold, Molnár, Vagstad, and Valstad, 2005; Bouri, Jalkh, Molnár, and Roubaud, 2017; Urquhart, 2016; Katsiampa, 2017; Urquhart, 2017; Nadarajah and Chu, 2017).”
Volatility co-movement between Bitcoin and Ether (2019, background): “…market efficiency of cryptocurrencies (Urquhart, 2016; Nadarajah and Chu, 2017), and the existence of bubbles in cryptocurrencies (Cheah and Fry, 2015; Corbet et al., 2017), while the price volatility of cryptocurrencies has been studied by Katsiampa (2017) and Phillip et al. (2018), among others.”
Some stylized facts of the cryptocurrency market (2018, background): “With a few exceptions, there are also some studies on banning effect, Google searches, models fitting and price controls of Bitcoin (Gandal et al., Forthcoming; Hendrickson and Luther 2017; Katsiampa 2017; Yelowitz and Wilson 2015).”