Time Series Analysis of Ether Cryptocurrency Prices: Efficiency, Predictability, and Arbitrage on Exchange Rates

Abstract

The Ether cryptocurrency, based on the blockchain of the Ethereum project for smart contracts, has long had the 2nd market capitalization, next to the Bitcoin. Despite its importance and the innovative features of the entire Ethereum ledger ecosystem, Ether has attracted far less attention than Bitcoin in terms of the time series analysis. This work provides an analysis of the R/S Hurst Exponent for the Ether time series in order to test to what extent the price dynamics may be predictable by deterministic methods including machine learning. Daily log returns, volatility time series, and transaction count sequences are analyzed. Support Vector Machine algorithm is used for testing the marginal predictability level. Ether-mediated triangular arbitrage between six major fiat currencies is also studied—we provide the distributions of the logarithmic rate of arbitrage transaction return for the 15 currency pair combinations. We also study the cointegration process of Ether-exchange rates with the foreign exchange rates that are the cause and driving force of the adjustment process towards dynamic market equilibrium eliminating arbitrage windows. The efficiency of the Ether market is found to increase with time.