On the robust drivers of cryptocurrency liquidity : the case of Bitcoin

This study aims to identify the factors that robustly contribute to Bitcoin liquidity, employing a rich range of potential determinants that represent unique characteristics of the cryptocurrency industry, investor attention, macroeconomic fundamentals, and global stress and uncertainty. To construct liquidity metrics, we compile 60-min high-frequency data on the low, high, opening, and closing exchange rates of Bitcoin against the US dollar. Our empirical investigation is based on the extreme bounds analysis (EBA), which can resolve model uncertainty issues. The results of Leamer's version of the EBA suggest that the realized volatility of Bitcoin is the sole variable relevant to explaining liquidity. With the Sala-i-Martin's variant of EBA, however, four more variables, (viz. Bitcoin's negative returns, trading volume, hash rates, and Google search volume) are also labeled as robust determinants. Accordingly, our evidence confrms that Bitcoin-specifc factors and developments, rather than global macroeconomic and fnancial variables, matter for explaining its liquidity. The fndings are largely insensitive to our proxy of liquidity and to the estimation method used.