Abstract
The cryptocurrency market has experienced stunning growth, with market value exceeding USD 1.5 trillion. We use a DCC-MGARCH model to examine the return and volatility spillovers across three distinct classes of cryptocurrencies: coins, tokens, and stablecoins. Our results demonstrate that conditional correlations are time-varying, peaking during the COVID-19 pandemic sell-off of March 2020, and that both ARCH and GARCH effects play an important role in determining conditional volatility among cryptocurrencies. We find a bi-directional relationship for returns and long-term (GARCH) spillovers between BTC and ETH, but only a unidirectional short-term (ARCH) spillover effect from BTC to ETH. We also find spillovers from BTC and ETH to USDT, but no influence running in the other direction. Our results suggest that USDT does not currently play an important role in volatility transmission across cryptocurrency markets. We also demonstrate applications of our results to hedging and optimal portfolio construction.
Highlights
Since the emergence of Bitcoin in 2009, the cryptocurrency market has experienced exponential growth
Our empirical results demonstrate that both a unidirectional short-term (ARCH) and GARCH effects play an important role in determining conditional volatility among cryptocurrencies
We find spillovers from BTC and ETH to USDT, but no influence running in the other direction, suggesting that USDT does not play an important role in volatility transmission across cryptocurrency markets
Summary
Since the emergence of Bitcoin in 2009, the cryptocurrency market has experienced exponential growth. We find spillovers from BTC and ETH to USDT, but no influence running in the other direction, suggesting that USDT does not play an important role in volatility transmission across cryptocurrency markets. This study utilises a series of daily returns for Bitcoin (BTC), Ether (ETH), and Tether (USDT) cryptocurrencies for a sample period running from 1-Janary-2016 to 30-June-2021. Note: This table provides summary statistics for daily returns of the cryptocurrencies used in our study; Bitcoin (BTC), Ether (ETH), and Tether (USDT). There are clusters of volatility from mid-2017 to early 2018 and in early 2021 (both consistent with a sharp rise and subsequent fall in cryptocurrency prices at those times) along with a correlation (Table 2). Obs × R-squared is Engle’s LM test statistic
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