Will the Bitcoin power law model still work in 2025 after S2F fails?

Considering S2F, the live power law channel indicates that BTC is around 20% below fair value, but ETF flows could push BTC towards either extreme.

Bitbo deploys Giovanni Santostasi’s model, with price near $109,700, fair value near $136,100, support near $48,300, and resistance near $491,800, structuring the current cycle within an upward corridor derived from a power law that fits price over time.

This channel is constructed by performing a linear regression of log(price) versus log(time since generation) and replicating that line in parallel to form upper and lower bounds that include the historically periodic extremes.

The result is a time-based compound curve in which the rail moves upward over time, making the model more like a location map than a point prediction.

The core claim can be easily evaluated in the live market. Bitcoin is trading around 20 percentage points below its fair value regression and more than twice above the model’s lower bound, an intermediate zone position that contrasts with the previous cycle’s highs and troughs, where price hit channel resistance and support.

The parameterization used by BGeometrics represents the fair value curve as P ≈ 1.0117×10^-17 × (days since generation) ^ 5.82, and the commonly referenced floor is approximately 0.42 times the curve, which matches the current gap between the spot price and Bitbo’s floor rail.

While this specification includes historical drawdowns, it also takes into account late-cycle overextension towards the upper band.

The logic behind this approach treats adoption as a power function of time and expects volatility to decay as the network matures. This characteristic manifests itself as oscillations around the regression line becoming smaller over successive cycles.

Bitcoin maintains power law lane as ETFs rewrite cycle

Recent flows help explain why price is in the middle of the channel rather than at the extremes. Net inflows into exchange-traded products (ETPs) hit a record $5.95 billion for the week ending October 4, 2025, with strong demand for U.S. spot Bitcoin ETFs pushing Bitcoin to an all-time high of approximately $126,000.

Over the next two weeks, we learned that the flow was not a one-way input. CoinShares recorded net inflows of $3.17 billion, but then reversed to record net outflows of $513 million, including $946 million in Bitcoin outflows for the week.

In the past two days alone, $958 million has been out of US Bitcoin ETFs, and on October 30th, $290 million was out of BlackRock.

This pace is consistent with a power law framework, where temporary demand spikes and air pockets push prices toward the upper and lower rails over weeks, while the long-term trajectory is locked into the time-based power curve. October’s highs are tied to a breakout wave in ETF subscriptions, which is now a visible macro lever for crypto demand.

Therefore, the question going forward is not whether the power law structure still applies, but where within the channel Bitcoin will trade on the next leg.

In the base case path, the price continues to oscillate around the regression neighborhood, currently near $136,100, but the amplitude decays if the volatility damping characteristic holds.

On the bullish path, continued ETF inflows and a favorable macro environment will pull the price towards today’s upper resistance near $491,800, which has historically been reached in late trading.

A bearish scenario could trigger a retest of the floor near $48,300 due to macro tightening, regulatory shocks, or sustained ETF outflows. This level has historically seen a core of surrender before re-entering the Channel.

These levels increase over time, indexed by the number of days since the outbreak. Rails are directional guardrails, not fixed targets.

To help readers track levels at a glance, the live models range as follows:

The debate over model selection is shaped by the collapse of the once popular stock-to-flow approach.

PlanB’s S2F pass required $98,000 by November 2021 and $135,000 by December 2021, but the goal was not met.

Prices then remained below the S2F orbit for many years. This was an out-of-sample failure and weakened confidence in using univariate stock-to-flow ratios to set definitive targets.

Vitalik Buterin has criticized S2F for providing false precision, and many analysts have pointed to methodological problems such as overfitting, omitting demand and liquidity variables, and treating half-lives as gradual valuation changes that do not take into account market microstructure.

Institutional researchers continue to warn that S2F is not a reliable tool for long-term pricing. As such, S2F remains a scarcity story rather than a predictive model.

In contrast, proponents of power laws argue that the length and amplitude of the cycle can be limited without strictly specifying the consequences.

igcurrencynews previously outlined a broad window in which the price of Bitcoin would not remain below roughly six digits after 2028, and could reach seven-digit levels at some point between 2028 and 2037.

These are ranges rather than calendar calls and inherit the same caveats as models that ignore policy shocks and structural changes in market access.

The new structural change is ETF flows, which act as a demand valve that overwhelms the marginal issuance reduction associated with the halving.

Continued weekly spot inflows above $2 billion to $3 billion increase the probability of an upper band test, while continued outflows increase the likelihood of a regression or floor retest.

Macro liquidity, including interest rates, the dollar, and the evolution of central bank balance sheets, remains central to determining whether prices move above regression or towards the lower rail. This macro overlay does not exist in S2F, only indirectly in power law fitting. Therefore, practitioners track flows and policies in parallel with channels.

Given the increasing use of models in institutional decks, method clarity is critical.

A power law channel is constructed by taking the daily closing price of BTCUSD, converting it to log(price) versus log(time since occurrence), fitting a simple linear regression as a fair value curve, and copying that line in parallel up and down to form resistances and supports that historically surround the price.

Its elegance lies in the generation of a monotonically rising time-based framework with visible error margins, which so far captures cycle extremes without claiming to know the dates or magnitude of future blows.

The trade-off is that known factors such as ETF demand and liquidity cycles are not mechanically incorporated. These factors should be monitored to understand where the price within the channel is likely to be in the short term.

For now, live reading is easy. Prices are about a fifth below regression and well above the lower bound, and ETF flows and macroeconomic conditions will determine whether Bitcoin tags the upper band or fades towards support before reverting to the mean.

The channel continues to rise over time and the rails define the tradable map.