A new look at Cryptocurrencies

By A. Phillip, J. Chan, S. Peiris. 2018

332 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Information Systems

View Paper: https://www.semanticscholar.org/paper/8c839b711a837cc36aea2e832b7f06d7a3155785

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 Finance

In Information Systems

Citations in the corpus

Asymmetric volatility in cryptocurrency markets: New evidence from smooth transition GARCH models (2020, unknown): “Even a handful of trading volume makes altcoins more vulnerable to price manipulation (see, e.g., Phillip et al., 2018).”
An empirical investigation of volatility dynamics in the cryptocurrency market (2019, unknown): “, 2018), heavy tail behaviour (Osterrieder and Lorenz, 2017; Osterrieder et al., 2017; Gkillas and Katsiampa, 2018; Phillip et al., 2018) and leverage effects (Phillip et al.”
An application of extreme value theory to cryptocurrencies (2018, unknown): “In fact, cryptocurrency returns not only are more volatile and riskier than traditional currencies but also exhibit heavier tail behaviour (Osterrieder et al., 2017; Phillip et al., 2018).”
The predictive power of public Twitter sentiment for forecasting cryptocurrency prices (2020, background): “In an article by Silverman et al. (2017), William Goetzmann - an economist at Yale University - states that due to the lack of intrinsic value and the prices of cryptocurrencies being driven by speculation, there is no way for cryptocurrencies to be valued fundamentally, making the market irrational”
Forecasting the volatility of Bitcoin: The importance of jumps and structural breaks (2020, unknown): “…et al 2018), the hedging and diversification benefits (Bouri et al 2017; Corbet et al 2018a; Urquhart and Zhang 2018; Borri 2019), the existence of bubbles (Cheah and Fry 2015; Corbet et al 2018b) and the behaviour of Bitcoin returns (Urquhart 2017; Corbet and Katsiampa 2018; Phillip et al 2018).”
Regime changes in Bitcoin GARCH volatility dynamics (2019, unknown): “To evaluate the goodness–of–fit of the models, we use the Deviance information criterion (DIC) obtained from the Bayesian estimation (Spiegelhalter et al., 2002). The DIC is not intended for identification of the correct model, but rather merely as a method of comparing a collection of alternative f”
Optimal vs naïve diversification in cryptocurrencies (2018, unknown): “…diversification benefits of Bitcoin (Bouri et al 2017a; Corbet et al 2018a), the unique features of cryptocurrencies (Gkillas and Katsiampa 2018; Phillip et al 2018), the relationship between transaction activity and Bitcoin returns (Koutmos 2018) and price clustering within Bitcoin prices…”