Using the spillover index approach and its variants, we examine both static and dynamic volatility connectedness among eight typical cryptocurrencies. The results reveal that their connectedness fluctuates cyclically and has shown an obvious rise trend since the end of 2016. In the variance decomposition framework, we further construct a volatility connectedness network linking 52 cryptocurrencies using the LASSO-VAR for estimating high-dimensional VARs. We find that these 52 cryptocurrencies are tightly interconnected and “mega-cap” cryptocurrencies are more likely to propagate volatility shocks to others. However, some unnoticeable cryptocurrencies (e.g., Maidsafe Coin) are also significant net-transmitters of volatility connectedness and even have larger contribution of volatility spillovers to others.
Description
Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency? - ScienceDirect
%0 Journal Article
%1 YI201898
%A Yi, Shuyue
%A Xu, Zishuang
%A Wang, Gang-Jin
%D 2018
%J International Review of Financial Analysis
%K ba crypto_curr volatility
%P 98-114
%R https://doi.org/10.1016/j.irfa.2018.08.012
%T Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?
%U https://www.sciencedirect.com/science/article/pii/S1057521918304095
%V 60
%X Using the spillover index approach and its variants, we examine both static and dynamic volatility connectedness among eight typical cryptocurrencies. The results reveal that their connectedness fluctuates cyclically and has shown an obvious rise trend since the end of 2016. In the variance decomposition framework, we further construct a volatility connectedness network linking 52 cryptocurrencies using the LASSO-VAR for estimating high-dimensional VARs. We find that these 52 cryptocurrencies are tightly interconnected and “mega-cap” cryptocurrencies are more likely to propagate volatility shocks to others. However, some unnoticeable cryptocurrencies (e.g., Maidsafe Coin) are also significant net-transmitters of volatility connectedness and even have larger contribution of volatility spillovers to others.
@article{YI201898,
abstract = {Using the spillover index approach and its variants, we examine both static and dynamic volatility connectedness among eight typical cryptocurrencies. The results reveal that their connectedness fluctuates cyclically and has shown an obvious rise trend since the end of 2016. In the variance decomposition framework, we further construct a volatility connectedness network linking 52 cryptocurrencies using the LASSO-VAR for estimating high-dimensional VARs. We find that these 52 cryptocurrencies are tightly interconnected and “mega-cap” cryptocurrencies are more likely to propagate volatility shocks to others. However, some unnoticeable cryptocurrencies (e.g., Maidsafe Coin) are also significant net-transmitters of volatility connectedness and even have larger contribution of volatility spillovers to others.},
added-at = {2021-12-20T16:06:15.000+0100},
author = {Yi, Shuyue and Xu, Zishuang and Wang, Gang-Jin},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/28b12d18a421a355d03f378fd8c0a8a5a/georglender},
description = {Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency? - ScienceDirect},
doi = {https://doi.org/10.1016/j.irfa.2018.08.012},
interhash = {65c113af4f517ef8ba609baf082adffe},
intrahash = {8b12d18a421a355d03f378fd8c0a8a5a},
issn = {1057-5219},
journal = {International Review of Financial Analysis},
keywords = {ba crypto_curr volatility},
pages = {98-114},
timestamp = {2021-12-20T15:06:15.000+0100},
title = {Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?},
url = {https://www.sciencedirect.com/science/article/pii/S1057521918304095},
volume = 60,
year = 2018
}
