Cryptocurrency returns' causality and prediction by using Vector error corection model

Abstract

The main goal of the research is to predict the future monthly returns of cryptocurrencies using the Vector Error Correction Model (VECM). Time series for the period 2018-2021 consists o f data on monthly returns for the cryptocurrencies Bitcoin, Ethereum and Ripple, as well as monthly returns on gold and the S&P500 stock index. Within the VECM, using the Johansen and Granger tests, short-term cointegration and causality among variables were determined, without the existence o f long-term equilibrium. The resulting model for short-term prediction o f the monthly returns o f the cryptocurrency Bitcoin was evaluated as unbiased and stable with a realistic forecast error o f 0.168 (16.8%).