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Bitcoin Bulls’ Favorite Stock-to-Flow Model is Flawed


Anatol Antonovici | Nov 25, 2019 | 13:37

Bitcoin Bulls Favorite Stock to Flow Ratio is Flawed Bitcoin

Bitcoin Bulls’ Favorite Stock-to-Flow Model is Flawed


Anatol Antonovici | Nov 25, 2019 | 13:37


The stock-to-flow (SF) measure proposed by PlanB has become widely accepted as an accurate model to predict the price of Bitcoin given the strong correlation that persists to this day. We’ve previously discussed this model on several occasions, However, according to crypto analysis resource Byte Tree, the model has some underlying flaws.

SF Is Nice, But Bitcoin Demand is Key

Over the weekend, Byte Tree’s Charlie Morris argued that while PlanB’s SF model was simple and nice, it doesn’t necessarily mean that the Bitcoin price will continue to follow its pattern. Instead, much depends on the demand and velocity of the cryptocurrency.

For those unfamiliar, the SF ratio of an asset is calculated by dividing the current supply by the number of new units of that asset produced in a given period. Bitcoin SF equals its supply divided by the number of new coins per a given period. The indicator is usually applied to commodities to show the scarcity or abundance of an asset. For example, gold is the commodity with the highest SF ratio, which points to its scarcity and production difficulty.

If Bitcoin were to follow the SF-based pattern, it could surge to as high as $100,000 within the next few years.

However, we shouldn’t have high expectations based only on the SF model, Morris says. In order for Bitcoin to reach a trillion dollar market cap, it has to experience mass adoption first.

Bitcoin Price is Directly Linked to Network Activity

Bitcoin’s network value, expressed in USD market cap, has a high correlation with the level of network activity, expressed in dollar transaction value (TV$). The chart below shows the direct link between the Bitcoin price and the 12-week average USD transaction value.

byte tree bitcoin stock to flow model

Thus, it is the Bitcoin activity that has been driving prices.

We can get even more interesting insights from Bitcoin’s NVT ratio (Network Value to Transactions), which is similar to the PE ratio used in the stock markets. The NVT ratio is measured by dividing the Network Value (market cap) by the daily or weekly USD volume transmitted via Bitcoin’s blockchain. As per ByteTree data, the current NVT is 9 weeks. This is because the current TV$ figure is $14 billion per week, and when we divide the total market cap (adjusted to exclude unspent coins) by the current TV$ reading, we get 9 weeks. Bitcoin NVT’s historic average is about 7 weeks.

Any NVT reading higher than 12 weeks points to high valuation that is usually caused by speculators. High valuations don’t last for long. For example, Bitcoin has been only 7% of the time with a NVT figure higher than that.

The next halving, scheduled for the first half of 2020, is expected to at least double the price of BTC according to the SF model. However, it will also mean that the NVT figure will rise from 9 weeks to 18 weeks. The problem is that BTC has seen only 16 days with its NVT above 18. Thus, Bitcoin should see increased network activity as a mandatory condition for the price to double or triple.

Active Coins

The Bitcoin price is also driven by the active stock moved on-chain. If we analyze the HODL waves, we can see that bull markets are associated with an increased proportion of moving Bitcoins.

In the chart above, the hotter colors show the proportion of BTC that have been on the move within the last 24 hours, while the purple color points to the number of coins that haven’t been moved for over 5 years. This could be because they are lost, dead or stored by hodlers. The sleeping coins don’t add value, but their weigh is increasing over time.

All in all, the SF model is good at providing useful insights from the supply side, though it fails at covering the demand aspect for Bitcoin.

Do you think that the Bitcoin SF prediction model is accurate? Share your thoughts in the comments section!

Images via Shutterstock, Charts by Byte Tree

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