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In detail, we focus on the time window in which Bitcoin experienced its higher price volatility the results suggest that it is disconnected from the one predicted by the model. During the last months of 2018, the prices seem to converge again, following a common path. It seems that the historical price fluctuated around the model (or implied) price until 2017, when the Bitcoin price significantly increased.
#Crypto currency compare specs drivers
Our main results put on evidence that there aren't ultimate drivers for Bitcoin price probably many factors should be expressed and studied at the same time, taking into account their variability and different relevance over time. The interconnection between this price and the historical one is analyzed, adopting a Vector Autoregression (VAR) model. After collecting the technical information required and computing a cost and a profit function for each period, an implied price for the Bitcoin value is derived. We construct a sample model, composed of the hardware devices employed in the mining process. We carry out an empirical analysis based on a cost of production model, trying to detect whether the Bitcoin price could be justified by and connected to the profits and costs associated with the mining effort. For this reason, the present analysis is focused on studying its price determination, which seems to be still almost unpredictable.
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“Bitcoin” is the expression of its main application since it was the first new currency that gained popularity some years after its release date and it is still the major cryptocurrency in the market. The present work investigates the impact on financial intermediation of distributed ledger technology (DLT), which is usually associated with the blockchain technology and is at the base of the cryptocurrencies' development. Department of Economics and Management, University of Padova, Padua, Italy.