Title: Are Bitcoin Bubbles Predictable? Combining a Generalized Metcalfe's Law and the LPPLS Model,
Abstract: We develop a strong diagnostic for bubbles and crashes in bitcoin, by
analyzing the coincidence (and its absence) of fundamental and technical
indicators. Using a generalized Metcalfe's law based on network properties, a
fundamental value is quantified and shown to be heavily exceeded, on at least
four occasions, by bubbles that grow and burst. In these bubbles, we detect a
universal super-exponential unsustainable growth. We model this universal
pattern with the Log-Periodic Power Law Singularity (LPPLS) model, which
parsimoniously captures diverse positive feedback phenomena, such as herding
and imitation. The LPPLS model is shown to provide an ex-ante warning of market
instabilities, quantifying a high crash hazard and probabilistic bracket of the
crash time consistent with the actual corrections; although, as always, the
precise time and trigger (which straw breaks the camel's back) being exogenous
and unpredictable. Looking forward, our analysis identifies a substantial but
not unprecedented overvaluation in the price of bitcoin, suggesting many months
of volatile sideways bitcoin prices ahead (from the time of writing, March
2018).