Although altogether different in purpose and complexity, this reminds me of the famous Black-Scholes Model for pricing options. What is interesting to me is the psychology of people represents a fairly well-known set of behavioral patterns. When enough people are given access to the same information, they can act in fairly predictable ways. For example, look at how everyone can point to support and resistance and trendlines and such on charts, and convince themselves their effective chartists. I believe most people apply the same parameter values for all the chart indicators they use, and thus end up not acting very independently at all.

What I'm Getting At

Black-Scholes came from an academic analysis, and was publicly available. It remains useful. But years ago I read about a trading company that did quite well with a proprietary model they'd spent a ton of money to develop. They claimed it was indeed more accurate than the model everyone else was using. Let's assume they told the truth and their customers were happy with the trading edge they benefited from. That pricing model remained proprietary.

When only Ed Seykota had access to his exponential moving average trading system, he had a true advantage. As it grew in popularity, people started trading the same way, and it became both more and less reliable (see above on everyone using the same parameters, and I now recall Seykota didn't invent the EMA).

This Stock-to-Flow ratio is very interesting, and potentially useful. What happens to all those who blindly use it to guide their trading, to reinforce whatever predispositions they have about Bitcoin? They'll exhibit the same behavior, and like an increasing use of a given arbitrage scenario, the potential advantage of S2F as applied to Bitcoin will become more mysterious and could dissipate.

The fundamental calculation would remain the same, but the result in the market of a bunch of messy traders acting upon the same information in the same way could force a change in the way it must be used in order to remain useful. I'm not attacking it at all; I'm curious to learn more. I'm merely instantly fascinated by both the danger and utility of such a calculation, as it becomes more broadly known and applied in people's trading toolbox.

And as you say:

The market is complex, and many factors play a role in price discovery. Therefore, it is impossible for anyone (and mathematical models and algorithms) to accurately predict the future long-term price changes of an asset.

Cheers!

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