The Stock to Flow model measures the relationship between the currently available stock of a resource and its production rate. It’s typically applied to precious metals and other commodities, but some argue it may apply to Bitcoin as well. It attempts to value BTC in a way similar to other scarce assets like gold and silver.

Its basic concept is that widely produced commodities like oil, wheat, and copper aren’t good stores of value because new supply is always coming online. But only small amounts of new BTC, gold and silver are regularly introduced.

This theoretically makes its value more stable. In simple terms, the Stock to Flow (SF or S2F) model is a way to measure the abundance of a particular resource. In this sense, Bitcoin may be viewed as a scarce digital resource. The higher the Stock to Flow ratio, the less new supply enters the market relative to the total supply. As such, an asset with a higher Stock to Flow ratio should, in theory, retain its value well over the long-term.

The stock to flow model is a bad model because of the following;

Not Supported By Research

While Stock to Flow is an interesting model for measuring scarcity, it doesn’t account for all parts of the picture. Models are only as strong as their assumptions. For one thing, Stock to Flow relies on the assumption that scarcity, as measured by the model, should drive value. According to critics of Stock to Flow, this model fails if Bitcoin doesn’t have any other useful qualities other than supply scarcity. Historical data from Coinmetrics shows that bitcoins volatility should also decrease over time.

The Model is Bogus

Obscure math has allowed stock-to-flow proponents to dismiss all criticism so it may be more intuitive to understand conceptually why the SF model is irrelevant for future price predictions.

The model supplied in the SF paper is the same slope-intercept equation everyone learns in high school: y = mx + b. An ordinary-least-squares (OLS) regression is not a predictive model but rather an estimation of them and b values that minimize the difference between the actual y values and the estimated y values given by the equation mx+b. In other words, every change in x equates to a corresponding change in y.

Recall that OLS is estimating how much y (Market Cap) changes for a given change in x (SF). On a month-to-month basis in which the model is derived, the change in x is effectively 0. As a result, the OLS model is doing nothing more than estimating Bitcoin’s historical growth rate. 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 before eventually converging to infinity as bitcoin’s flow approaches 0.

Using the estimated slope-intercept formula is making the most naive prediction possible because bitcoin grew by X in the past, it will grow by X in the future. One should remember that past results are not representative of future returns.