This paper has just been published:
Bitcoin Spreads Like a VirusAbstract
We illustrate, by way of example, that Bitcoin’s long-term price is non-random and can be modeled as a function of the logistic growth of number of users n over time. Using observed data for both Facebook and Bitcoin, we derive the relationships between price, number of users, and time, and show that the resulting market capitalizations likely follow a Gompertz sigmoid growth function. This function, historically used to describe the growth of biological organisms like bacteria, tumors, and viruses, likely has some application to network economics. We conclude that the long-term growth rate in users has considerable effect on the long-term price of bitcoin.
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The Study gives the conclusion..
A key application of our findings is the ability to evaluate data and marketplace news with the
intent to separate meaningful information from misleading noise. Noise is a dominant driver of price and
volatility in the short-term. It is not noteworthy that markets disseminate and consume noise about bitcoin
or any other cryptocurrency. Forecasts of sky-high prices and doomsday crashes are common with bitcoin.
In many cases, cryptocurrency information (positive and negative) is crafted in a convincing way by
experienced and knowledgeable sources and presented by reputable media. In isolation, these predictions
are indistinguishable from information, even though they are probably noise.
Though value is not observable, even an imperfect assessment of value serves to keep markets
efficient. Over time price tends toward value. The model we have presented serves as a backdrop against
which potential information can be evaluated. It does not predict that bitcoin’s price will soar or crash.
Rather, it suggests that the probability of those extreme those events is very small because ultimately
number of users drives price.
To date, the typical approach to cryptocurrency valuation has been via Metcalfe’s law. Commonly
expressed in shorthand as n2, it is the approximate value of P when n is large. We show that price is a
function of n users, as Metcalfe’s law states. Our research differs from past models in that we derive that
n may grow at a non-constant rate over time, as a Gompertz function would indicate. This function,
usually used to describe the growth of biological organisms like bacteria, tumors, and viruses, likely has
some application to network economics, including cryptocurrency valuation. Lastly, we confirm past
research that the long-term growth rate in users has considerable effect on the long-term price of bitcoin.
Metcalfe law has been quite a mystery to me, even thou it was one of my three fundamental approach at valuing bitcoin when i originally invested. This study can reingorce the findings, even thou a R2=0,57 may seem not much.
