On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure

Abstract

We propose to measure volatilities of 102 active cryptocurrencies using Garman and Klass (GK) volatility measures and model the measures using asymmetric bilinear Conditional Autoregressive Range (ABL-CARR) model. Results reveal volatility persistence and leverage effects which can improve the predictability of volatility, reduce risk and hence lessen the level of speculation in cryptocurrency market. We further relate volatility features for the top five cryptocurrencies to their time of development and transaction speed and recommend investors to distinguish between long-term or short-term speculation in their investment profile.