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Volatility spillover in crypto-currency markets: Some evidences from GARCH and wavelet analysis

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  • Kumar, Anoop S.
  • Anandarao, S.

Abstract

We study the dynamics of volatility spillover across four major cryptocurrency returns namely Bitcoin, Ethereum, Ripple and Litecoin from 15−08−2015 to 18−01−2018 . In the first step, an IGARCH (1,1)-DCC (1,1) multivariate GARCH model is estimated to quantify the nature of volatility spillovers. From GARCH results, it is seen that there is statistically significant volatility spillover from Bitcoin to Ethereum and Litecoin during the period of analysis. The conditional correlation measures point towards the possibility of moderate return co-movement among the crypto-currency returns. The conditional covariance measures show negligible volatility spillover during the initial periods and provide evidence towards increased volatility spillover after 2017. Wavelet coherence measures shows evidence towards correlation among the crypto-currencies to be persistent across the short run, while the pairwise wavelet cross-spectral analysis confirms the findings obtained from conditional covariance measures. It is found that other crypto-currencies are influenced by fluctuations in bitcoin prices. Overall, the results indicate the possibility of turbulence in the crypto-currency markets and point towards the possibility of herding behaviour in crypto-currency markets.

Suggested Citation

  • Kumar, Anoop S. & Anandarao, S., 2019. "Volatility spillover in crypto-currency markets: Some evidences from GARCH and wavelet analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 448-458.
    • Handle: RePEc:eee:phsmap:v:524:y:2019:i:c:p:448-458
    DOI: 10.1016/j.physa.2019.04.154
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    References listed on IDEAS

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