Forecasting the Volatility of the Cryptocurrency Market by GARCH and Stochastic Volatility

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 several GARCH models. We find that when we deal with extremely volatile financial data, such as cryptocurrencies, SV performs better than family Moreover, forecasting errors model, compared models, tend to be more accurate forecast time horizons are longer. deepens our insight into models in complex cryptocurrencies.