Modelling Crypto-Currencies Financial Time-Series

38 Pages Posted: 1 Sep 2017 Last revised: 20 Dec 2017

Leopoldo Catania

University of Aarhus - School of Business and Social Sciences; University of Aarhus - CREATES

Stefano Grassi

University of Rome, Tor Vergata, Faculty of Economics, Department of Economics, Law and Institutions

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Date Written: August 16, 2017

Abstract

This paper studies the behaviour of crypto-currencies financial time-series of which Bitcoin is the most prominent example. The dynamic of those series is quite complex displaying extreme observations, asymmetries and several nonlinear characteristics which are difficult to model. We develop a new dynamic model able to account for long-memory and asymmetries in the volatility process as well as for the presence of time-varying skewness and kurtosis. The empirical application, carried out on a large set of crypto-currencies, shows evidence of long memory and leverage effect that has a substantial contribution in the volatility dynamic. Going forward, as this new and unexplored market will develop, our results will be important for investment and risk management purposes.

Keywords: Crypto-Currency, Bitcoin, Score-Driven Model, Leverage Effect, Long Memory, Higher Order Moments

Suggested Citation

Catania, Leopoldo and Grassi, Stefano, Modelling Crypto-Currencies Financial Time-Series (August 16, 2017). Available at SSRN: https://ssrn.com/abstract=3028486 or http://dx.doi.org/10.2139/ssrn.3028486

Leopoldo Catania (Contact Author)

University of Aarhus - School of Business and Social Sciences ( email )

Fuglesangs Allé 4
Aarhus V, DK-8210
Denmark
+4587165536 (Phone)

HOME PAGE: http://pure.au.dk/portal/en/leopoldo.catania@econ.au.dk

University of Aarhus - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Stefano Grassi

University of Rome, Tor Vergata, Faculty of Economics, Department of Economics, Law and Institutions ( email )

Via Columbia, 2
Rome, 00133
Italy

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