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Modelling Crypto-Currencies Financial Time-Series

Leopoldo Catania () and Stefano Grassi ()

No 417, CEIS Research Paper from Tor Vergata University, CEIS

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 (search for similar items in EconPapers)
JEL-codes: C01 C22 C51 C58 (search for similar items in EconPapers)
Pages: 39 pages
Date: 2017-12-11, Revised 2017-12-11
New Economics Papers: this item is included in nep-ban, nep-ecm, nep-ore, nep-pay and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (37)

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Persistent link: https://EconPapers.repec.org/RePEc:rtv:ceisrp:417

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