Testing of Random Walk Hypothesis in the Cryptocurrency Market

Abstract

Cryptocurrency as a financial asset has emerged as a fad among investors, academicians and policymakers alike. In a financial purview, this study intends to empirically test the behaviour of the cryptocurrency return, inferring its market efficiency. For this purpose, daily data of five cryptocurrencies (Bitcoin, Ethereum, Litecoin, Tether and Ripple) have been collected from 1 January 2016 to 31 March 2021 to investigate the well-known financial theory of random walk hypothesis for this young market. To provide statistical evidence and ensure the robustness of results, analysis is performed using the variance ratio test, augmented Dickey–Fuller test, Philip–Perron test, Breusch–Godfrey serial correlation LM test and ARIMA model. The statistical results illustrated strong evidence refuting the presence of the random walk hypothesis in this emerging market, thus implying inefficiency in the cryptocurrency market. Furthermore, the absence of random walk in the cryptocurrency makes this financial asset predictable, giving investors an arbitrage edge to earn abnormal gains using trading strategies, which is euphoria.