Volatility models for cryptocurrencies and applications in the options market

•We investigate various volatility models using BTC and ETH price series.•The GARCH model performs well both in sample and out of sample.•We observe insignificant asymmetric volatility reponse to past returns.•The GARCH volatility forecast outperforms the option implied volatility.•A volatility-spread trading strategy with delta hedging yields robust profits. We investigate the effectiveness of various volatility models using the Bitcoin (BTC) and Ethereum (ETH) price series. Amongst the single-variate models, the GARCH model performs well both in sample and out of sample. Moreover, we do not observe any significant asymmetric volatility reponse to past returns in the GJR-GARCH model. Although the multi-variate VARMA-DCC-AGARCH model outperforms in sample, it performs worse out of sample than the single-variate GARCH model. Furthermore, the GARCH volatility forecast outperforms the option implied volatility in forecasting future realized volatility. We formulate an option trading strategy by exploiting the volatility spread between the GARCH volatility forecast and the option implied volatility. We show that a simple volatility-spread trading strategy with delta-hedging can yield robust profits for both BTC and ETH options. We interpret the strategy profitability as evidence for the pricing inefficiencies in the cryptocurrency options market during our sample period.