Abstract
This study examines the volatility of nine leading cryptocurrencies by market capitalization—Bitcoin, XRP, Ethereum, Bitcoin Cash, Stellar, Litecoin, TRON, Cardano, and IOTA-by using a Bayesian Stochastic Volatility (SV) model and several GARCH models. We find that when we deal with extremely volatile financial data, such as cryptocurrencies, the SV model performs better than the GARCH family models. Moreover, the forecasting errors of the SV model, compared with the GARCH models, tend to be more accurate as forecast time horizons are longer. This deepens our insight into volatility forecast models in the complex market of cryptocurrencies.
Highlights
Understanding the relationships among cryptocurrencies is important for policymakers whose role is to maintain the stability of financial markets as well as for investors whose investment portfolios contain a portion of cryptocurrencies
We report out-of-sample mean square (prediction) error (MSE) losses in both the Stochastic Volatility (SV) and generalized ARCH (GARCH) models with the observed time series data, where the evaluation is based on two different volatility proxies for the conditional volatility
We discussed the volatility of nine cryptocurrencies by using the GARCH and SV models
Summary
Understanding the relationships among cryptocurrencies is important for policymakers whose role is to maintain the stability of financial markets as well as for investors whose investment portfolios contain a portion of cryptocurrencies. Cryptocurrency is a non-centralized digital currency that is exchanged between peers without the need of a central government. Because the prices of cryptocurrencies have been increased such as speculative investment purposes and/or a digital asset for real use, they have received growing attention from the media, academics, and the finance industry. Since the inception of Bitcoin in 2009, over several thousand alternative digital currencies have been developed, and there have been a number of studies on the analysis of the exchange rates of cryptocurrency [3]. The degree of the return volatility has been regarded as a crucial characteristic of cryptocurrencies for investors including them in their portfolio. Since [4,5], empirical investigations of Bitcoin showed that
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