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Stock to Flow overlay

The Stock to Flow overlay (often shortened to S2F) is a Cryptowatch overlay that expresses the relationship between production (flow) and current supply (stock). Stock-to-flow ratios calculate the value of the current supply of a commodity against the rate that it can be produced. This model is based on the hypothesis that scarcity drives value — as production rates decrease, scarcity increases, and existing stock becomes more valuable.

You can read an in-depth analysis of Stock to Flow from the popularizer of the model, 100trillionUSD, in his blog post here.

Using Bitcoin as an example, we know that the supply is fixed (21 million bitcoins) and the production rate is reduced by half every 210,000 blocks (every 4 years, roughly). By applying the Stock to Flow overlay to a BTC/USD chart, we can see that Bitcoin’s inherent flow reduction from each halving has a positive impact on the value of the asset.

The Stock to Flow overlay in Kraken’s BTC/USD market, 2016 to present, set to default inputs.

This overlay is best visualized on long-term candle periods (3 days to 1 week) using a logarithmic scale. The overlay derives its projections from available stock over a period which can be defined in the Inputs tab in the Analysis menu. The default data range is 365 days previous to the current date.

When we apply this overlay to BTC/USD, the halvings (dates when block rewards are reduced by half) are very apparent in the projection. This is because the flow rate (production rate) of new coins decreases by half at each instance, which increases the scarcity of the current supply. We can see this trend continuing alongside future halving dates:

The Stock to Flow overlay in Kraken’s BTC/USD market, present to 2025, set to default inputs.

The center line in the overlay shows the model’s price forecast at any given point in time. The Stock to Flow model — without factoring in coins lost from Bitcoin’s total supply — forcasts the price of Bitcoin will reach an average of roughly $100,000 in May/June 2021, then $130,000 after the halving in March/April 2024.

We can edit the inputs of this overlay in the Analysis menu. The three input fields are defined here:



Stock/Flow Days

The amount of look-back days factored into the S2F calculation. Currently the largest amount of periods you can factor is 365 days. PlanB recommends an annual model — this is typical of commodities markets, like Gold and Silver.

Std Dev

The distance in standard deviations of the outer lines from the dashed mean line of the indicator. Changing the value increases or decreases the span of the outer deviation lines from the mean line. The default setting is 2 standard deviations.

Lost Coins %

The percentage of total bitcoins lost forever and out of circulation, such as bitcoins trapped by lost private keys, for example. The default value is 0, assuming all bitcoins ever mined are currently in circulation. This field takes positive values only and lowers the projection on the y-axis as the percentage increases.

These are the default field inputs for the Stock to Flow overlay.

Lost bitcoins

In late 2017 the New York City research firm Chainanalysis performed a study concluding that 3.79 million bitcoins (roughly one-fifth of all bitcoin ever mined at the time) had been taken out of circulation (source). This number has likely grown, but it gives us a good place to start.

3.79 million lost bitcoins out of the current total supply of (roughly) 18.33 million bitcoins (source) are lost — approximately 20.676%. We can round that value up to 21% for the Lost Coins % input.

After adjusting the Lost Coins % input we can see the projection is unchanged along the x-axis, but has adjusted down on the y-axis:

With lost bitcoins taken into consideration, the model forecasts roughly $55,000 per bitcoin in May/June 2021, then $75,000 after the halving in March/April 2024.

If Bitcoin trends towards these milestones in the coming months and years, the Stock to Flow model may prove to be an accurate model of Bitcoin’s future value.

Want to learn more about the Stock to Flow model? Check out our Blog Post!