Is Bitcoin about to break its last surviving valuation model?


Over a fairly long period of time, all of the long-term bitcoin valuation models have ultimately broken down, however, the one that has held the strongest narrative in this cycle has been the power law model.

Historically, in previous cycles, bitcoin has tended to surpass this model during bull markets and fall below it during bear markets, but in the current cycle the price has largely remained close to the model’s trajectory.

Bitcoin’s power law framework provides a mathematical view of long-term price trends, revealing that bitcoin’s historical performance follows a power law distribution on a logarithmic scale. This implies a relationship between time and price. However, the model is based on historical observations.

In theory, it is a backward-looking model that does not guarantee the accuracy of future predictions, especially given the unpredictable nature of financial markets. The model is useful for understanding long-term structural trends.

Below $90,000, bitcoin is currently trading at a steep discount to the model. The power law value sits near $118,000, putting the spot price approximately 32% below the model. This is the largest deviation since the yen carry trade was disabled in August 2024, resulting in a 35% deviation from the trend line and taking three months to recover.

From a broader perspective, bitcoin has spent most of this cycle tracking close to the model, while in previous cycles it deviated much more aggressively both above and below it.

In the last cycle, the most prominent model was the stock to flow framework created by anonymous analyst Plan B, which assumes that scarcity directly drives value. The model is not valid as of January 2021 and, based on current Glassnode data, would imply a price of approximately $1.3 million per bitcoin today.

The key question now is whether the bitcoin average returns to the power law trend or falls lower and challenges the validity of another long-standing model.

Stock to flow (Glassnode)



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