Resumen:
This paper deals with the analysis of volatility persistence in 12 main cryptocurrencies (Bitcoin, Bitshare, Bytecoin, Dash, Ether, Litecoin, Monero, Nem, Ripple, Siacoin, Stellar and Tether) taking into account the possibility of structural breaks. Using fractional integration methods, the results indicate that both absolute and squared returns display long memory features, with orders of integration confirming the long memory hypothesis. However, after accounting for structural breaks, we find a reduction in the degree of persistence in the cryptocurrency market. The evi-dence of persistence in volatility imply that market participants who want to make gains across trading scales need to factor the persistence properties of cryptocurrencies in their valuation and forecasting models since that will help improve long-term volatility market forecasts and optimal hedging decisions.
