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Is Bitcoin About to Break Its Last Surviving Valuation Model?

Over a long enough time horizon, every long-term valuation model for Bitcoin eventually breaks down, but the one that holds the strongest narrative through this cycle is the power law model.

Historically, in previous cycles, Bitcoin has tended to move outside 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.

The Bitcoin 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 means the relationship between time and price. However, the model relies on historical observations.

In theory, this is a backward-looking model and cannot guarantee the accuracy of future predictions, especially given the unpredictability of financial markets. The model is useful for understanding long-term structural trends.

Bitcoin is currently trading below $90,000, a significant discount to this model. The power law value is close to $118,000, which makes the spot price about 32% lower than the model. This is the largest deviation since the unwinding of the yen carry trade in August 2024, when the yen carry trade deviated 35% from the trend line and took three months to recover.

From a broader perspective, Bitcoin has spent much of this cycle approaching this model, whereas in previous cycles it deviated much more both above and below it.

During the last cycle, the most prominent model was the stock-to-flow framework created by anonymous analyst Plan B, which posits that scarcity directly drives value. The model has been invalid since January 2021, which according to current Glassnode data would mean the price per Bitcoin today would be around $1.3 million.

The key question now is whether the Bitcoin mean will revert to a power law trend or break below and challenge the validity of another long-standing model.

Inventory to flow (Glassnode)

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