Abstract
This study introduces a comprehensive Google search volume based Bitcoin sentiment index (BSI) by following the methodology of Da, Engelberg, and Gao (2014). BSI is investigated for its association with Bitcoin returns, trade volume, volatility, and United States dollar exchange rates (USD). Results of the simple OLS regression clarify that BSI has a positive impact on Bitcoin returns and trade volume while it has a negative impact on the volatility of Bitcoin returns. Furthermore, the Auto-regressive distributed lag (ARDL) model has been used to capture the relationship between BSI and Bitcoin price with USD. Empirical results of the ARDL model demonstrate that Bitcoin sentiments affect USD in the short-run but not long-run. However, Bitcoin's price can negatively affect USD in short as well as in the long-run. Error correction term represents a 38.50% adjustment towards the long-run equilibrium in one month if there is a deviation in the short-run. The results imply that investors in FOREX or public in general interested in Bitcoin trading should foresee sentiments of the public towards Bitcoin.
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