Bitwise Analyst Raises Doubts on Bitcoin Price Models Despite Bullish Forecasts

Bitcoin's Stock-to-Flow (S2F) model is flashing one of its most bullish forecasts yet, projecting BTC to reach $222,000 by 2026 and a staggering 10-year valuation of $10.9 million per BTC, with an annualized compound growth rate of approximately 58.3%. However, André Dragosch, Head of Research for Europe at Bitwise, has cautioned that Bitcoin's maturing market may be outgrowing these predictive frameworks, urging investors to exercise caution.

The S2F model, created by PlanB in 2019, measures Bitcoin's value based on scarcity by comparing the existing supply (stock) to the annual new supply (flow). It links price increases to halving events, which reduce new coin issuance every four years. Despite its historical prominence, Dragosch pointed out that the model is misspecified and suffers from statistical issues, as it excludes demand-side drivers and shows residuals with a negative drift. "The S2F model is undeniably one of the more bullish frameworks – but use it with caution. Its statistical issues and exclusion of demand-side drivers limit its reliability," he wrote.

Dragosch also compared other valuation models, noting that the Bitcoin Autocorrelated Exchange Rate Model (BAERM) estimates Bitcoin's fair value at $159,000, projecting $173,000 by the end of 2025 and $7.59 million over ten years, with an 88% R² fit since the second halving. However, he suggested BAERM may be outdated as it doesn't fully account for institutional buying or adoption trends. The Power Law model, while aligning with a 99% R² in log-log regressions, is more conservative, predicting a 10-year price of $2.03 million based on diminishing returns.

Highlighting the evolving market, Dragosch stressed that institutional demand via Bitcoin ETPs and treasury holdings now outweighs the annualized supply reduction from the latest halving by more than 7 times. He added that technological adoption curves and the rise of ETFs since January 2024 challenge traditional models, meaning past post-halving performance patterns might not apply. Thus, while these models offer valuable perspectives, they increasingly fall short in capturing today's demand-driven market dynamics.