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Currently, there is no consensus on the real properties of Bitcoin. Thediscussion comprises its use as a speculative or safe haven assets, while otherauthors argue that the augmented attractiveness could end accomplishing money'sfunctions that economic theory demands. This paper explores the associationbetween Bitcoin's market price and a set of internal and external factors usingBayesian Structural Time Series Approach. I aim to contribute to the discussionby differentiating among several attractiveness sources and employing a methodthat provides a more flexible analytic framework that decompose each of thecomponents of the time series, apply variable selection, include information onprevious studies, and dynamically examine the behavior of the explanatoryvariables, all in a transparent and tractable setting. The results show thatthe Bitcoin price is negatively associated with a neutral investor's sentiment,gold's price and Yuan to USD exchange rate, while positively related to stockmarket index, USD to Euro exchange rate and variated signs among the differentcountries' search trends. Hence, I find that Bitcoin has mixed properties sincestill seems to act as a speculative, safe haven and a potential a capitalflights instrument.

Exploring the determinants of Bitcoin's price: an application of Bayesian Structural Time Series