EconPapers    
Economics at your fingertips  
 

Conditional heteroskedasticity in crypto-asset returns

Charles Shaw

MPRA Paper from University Library of Munich, Germany

Abstract: In a recent contribution to the financial econometrics literature, Chu et al. (2017) provide the first examination of the time-series price behaviour of the most popular cryptocurrencies. However, insufficient attention was paid to correctly diagnosing the distribution of GARCH innovations. When these data issues are controlled for, their results lack robustness and may lead to either underestimation or overestimation of future risks. The main aim of this paper therefore is to provide an improved econometric specification. Particular attention is paid to correctly diagnosing the distribution of GARCH innovations by means of Kolmogorov type non-parametric tests and Khmaladze's martingale transformation. Numerical computation is carried out by implementing a Gauss-Kronrod quadrature. Parameters of GARCH models are estimated using maximum likelihood. For calculating P-values, the parametric bootstrap method is used. Further reference is made to the merits and demerits of statistical techniques presented in the related and recently published literature.

Keywords: Autoregressive conditional heteroskedasticity (ARCH); generalized autoregressive conditional heteroskedasticity (GARCH); market volatility; nonlinear time series; Khmaladze transform. (search for similar items in EconPapers)
JEL-codes: C22 C58 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ets, nep-pay and nep-rmg
Date: 2018-11-01
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Published in Journal of Statistics: Advances in Theory and Applications 1.20(2018): pp. 15-65

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/90437/1/MPRA_paper_90437.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:90437

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().

 
Page updated 2019-01-21
Handle: RePEc:pra:mprapa:90437