Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/247618 
Year of Publication: 
2021
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 9 [Issue:] 3 [Publisher:] MDPI [Place:] Basel [Year:] 2021 [Pages:] 1-17
Publisher: 
MDPI, Basel
Abstract: 
Recently, the world of cryptocurrencies has experienced an undoubted increase in interest. Since the first cryptocurrency appeared in 2009 in the aftermath of the Great Recession, the popularity of digital currencies has, year by year, risen continuously. As of February 2021, there are more than 8525 cryptocurrencies with a market value of approximately USD 1676 billion. These particular assets can be used to diversify the portfolio as well as for speculative actions. For this reason, investigating the daily volatility and co-volatility of cryptocurrencies is crucial for investors and portfolio managers. In this work, the interdependencies among a panel of the most traded digital currencies are explored and evaluated from statistical and economic points of view. Taking advantage of the monthly Google queries (which appear to be the factors driving the price dynamics) on cryptocurrencies, we adopted a mixed-frequency approach within the Dynamic Conditional Correlation (DCC) model. In particular, we introduced the Double Asymmetric GARCH-MIDAS model in the DCC framework.
Subjects: 
covariance matrix
cryptocurrency
Double Asymmetric GARCH&#x2013
MIDAS
Dynamic Conditional Correlation
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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