Modelling Crypto-Currencies Financial Time-Series

40 Pages Posted: 1 Sep 2017 Last revised: 28 Oct 2019

See all articles by Leopoldo Catania

Leopoldo Catania

Aarhus University - School of Business and Social Sciences; Aarhus University - 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 606 crypto currencies, indicates that a robust filter for the volatility of crypto currencies is strongly required. Forecasting results show that the inclusion of time{varying skewness systematically improves volatility, density, and quantile predictions at different horizons. Going forward, as this new and unexplored market will develop, our results will be important for asset allocation, risk management, and pricing of derivative securities.

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)

Aarhus University - 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

Aarhus University - 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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