Why the Stock-to-Flow Bitcoin Valuation Model Is Wrong
(Source: coindesk.com)

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(Original link: coindesk.com)

Please consider using a different web browser for better experience. Please enable JavaScript in your browser for a better site experience. Why the Stock-to-Flow Bitcoin Valuation Model Is Wrong Jun 30, 2020 at 13:36 UTC Updated Jun 30, 2020 at 13:43 UTC opinion Nico Cordeiro Why the Stock-to-Flow Bitcoin Valuation Model Is Wrong Nico Cordeiro is the chief investment officer and fund manager at Strix Leviathan. He oversees quantitative research, strategy development, risk management and portfolio allocation. A longer version of this post can be found here . The stock-to-flow model (SF), popularized by a pseudonymous Dutch institutional investor who operates under the Twitter account “ PlanB ,” has been widely praised and is the leading valuation model for bitcoin proponents. SF has achieved viral popularity and inspired rags-to-riches dreams for those gambling it all on the future of bitcoin. However, we believe the model’s accuracy will likely be about as successful at forecasting bitcoin’s future price as the astrological models of the past were at predicting financial outcomes. Stanford Professor Paul Pleifderer coined the term “chameleons” to describe models that are built upon dubious assumptions and are given more credence than they deserve. An initial evaluation of any model should begin with a critical look at the model’s theoretical assumptions, he says. As an example, Pleifderer provides the following scenario:
Imagine an asset pricing model based on the assumption that there is no uncertainty about any asset's returns. … No serious person would suggest that the predictions of the model should be subjected to rigorous empirical testing before rejecting it. The model can be rejected simply on the basis that a critical assumption is contradicted by what we already know to be true. Chameleons are particularly difficult to spot and dispute because they appear to be meaningful. It’s only under further scrutiny that you realize they are built upon assumptions that do not map to what we know about the real world. Introducing stock-to-flow PlanB’s paper “ Modeling Bitcoin Value with Scarcity ” states that certain precious metals have maintained a monetary role throughout history because of their unforgeable costliness and low rate of supply. For example, gold is valuable both because new supply (mined gold) is insignificant to the current supply and because it is impossible to replicate the vast stores of gold around the globe. PlanB then argues this same logic applies to bitcoin, which becomes more valuable as new supply is reduced every four years, ultimately culminating in a supply of 21 million bitcoin. Low rate of supply, which PlanB defines as “scarcity,” can be quantified using a metric called Stock-to-Flow (SF), which is the ratio between current supply and new supply. This premise is then translated into the hypothesis, “…that scarcity, as measured by SF, directly drives value.” PlanB then plots bitcoin’s SF against USD market capitalization as well as two arbitrarily chosen SF data points for gold and silver. Taken from "Modeling Bitcoin Value with Scarcity," by PlanB. PlanB then runs a linear regression using the natural logarithm of bitcoin’s SF metric as the independent variable and the USD market capitalization as the dependent variable. The paper ends with the conclusion that there is a statistically significant relationship between USD market capitalization and SF values, as evidenced by the linear regression resulting in an R2 (a statistical measure of how close the data fits to a regression line) of ~0.95. The two randomly chosen data points for gold and silver are in line with bitcoin’s trajectory and presented as further evidence of the hypothesis. PlanB suggests that investors can forecast the future USD market capitalization of bitcoin using the above formula. This has helped give credence to those $100,000 bitcoin projections. Problems abound There are several deficiencies within the paper, both in its theoretical proposition and its empirical foundation. From a theoretical point of view, the model is based on the rather strong assertion that the USD market capitalization of a monetary good (e.g. gold and silver) is derived directly from their rate of new supply. No evidence or research is provided to support this idea, other than the singular data points selected to chart gold and silver’s market capitalization against bitcoin’s trajectory.
This becomes quite obvious when one extends the model into the near future. By 2045, the model estimates each Bitcoin will be worth $235,000,000,000. The second is the naïve application of a linear regression that results in a high probability of a researcher finding spurious results. “Good” statistical results, such as a high R-square, do not constitute a meaningful finding. It is common for researchers to underestimate how often such techniques lead to false results. And particularly in this situation, where there is a large degree of freedom ...