Bitcoin is undoubtedly the most popular cryptocurrency. Earlier studies have found that Bitcoin is mainly used as an asset, and hence analysing its volatility is of great importance. In this article, we explore the optimal conditional heteroskedasticity model with regards to goodness-of-fit to the data. It is found that the best conditional heteroskedasticity model is the AR-CGARCH model, highlighting the significance of including both a short-run and a long-run component of the conditional variance.

Through the application of three pair-wise bivariate BEKK models, this paper examines the conditional volatility dynamics along with interlinkages and conditional correlations between three pairs of cryptocurrencies, namely Bitcoin-Ether, Bitcoin-Litecoin, and Ether-Litecoin. While cryptocurrency price volatility is found to be dependent on its own past shocks and past volatility, we find evidence of bi-directional shock transmission effects between Bitcoin and both Ether and Litecoin, and uni-directional shock spillovers from Ether to Litecoin. Finally, we identify bi-directional volatility spillover effects between all the three pairs and provide evidence that time-varying conditional correlations exist and are mostly positive.

Abtract:We study the tail behaviour of the returns of five major cryptocurrencies. By employing an extreme value analysis and estimating Value-at-Risk and Expected Shortfall as tail risk measures, we find that Bitcoin Cash is the riskiest, while Bitcoin and Litecoin are the least risky cryptocurrencies.

Using a bivariate Diagonal BEKK model, this paper investigates the volatility dynamics of the two major cryptocurrencies, namely Bitcoin and Ether. We find evidence of interdependencies in the cryptocurrency market, while it is shown that the two cryptocurrencies' conditional volatility and correlation are responsive to major news. In addition, we show that Ether can be an effective hedge against Bitcoin, while the analysis of optimal portfolio weights indicates that Bitcoin should outweigh Ether. Understanding volatility movements and interdependencies in cryptocurrency markets is important for appropriate investment management, and our study can thus assist cryptocurrency users in making more informed decisions.

This is a repository copy of High frequency volatility co-movements in cryptocurrency markets.