Bitcoin’s bear market is not just vibes and charts, according to Charles Schwab’s Jim Ferraioli. On Bloomberg Wednesday, Ferraioli framed the selloff as having a measurable cost floor rooted in energy economics, not a random sentiment collapse.
Ferraioli’s key move is simple. Ask what it costs to manufacture Bitcoin, then treat that number like a structural gravity well. In his framework, the most efficient miners can produce one BTC at roughly $60,000, while less efficient operators sit closer to $95,000. Bitcoin Magazine reports these figures as the all-in cost ranges tied to power prices and hardware capability.
What $60,000 is supposed to mean
The argument starts with the drawdown math. Bitcoin peaked around $126,000 in the fall and then fell to roughly $60,000 in February, a 50% correction. Bitcoin Magazine says that matters because it is far less severe than the 75% and higher implosions that marked prior Bitcoin bear markets.
From there, Ferraioli points to “production cost for the best miners” as the floor. Bitcoin Magazine ties the ~$60,000 number to powering a facility at about $0.07 per kilowatt-hour using next-generation ASIC hardware at scale. For miners that are less efficient, Bitcoin Magazine cites Glassnode data from Schwab’s May 2026 research report, placing production cost at about $95,000 per BTC.
That gap is also cast as the explanation for today’s valuation range. The desk’s logic, as presented in Bitcoin Magazine, goes like this. When spot trades near the most efficient miners’ cost, the least efficient players shut down. Difficulty adjusts, the network hash rate changes, and the average cost per coin trends lower.
Forced sellers: ETF and ETP holders, plus “active” basis
Ferraioli does not lean only on mining economics. Bitcoin Magazine says he also tracked where selling pressure comes from, and it skews demographically toward investors who bought in the last 18 months.
Schwab tracks two cost-basis metrics in Bitcoin Magazine’s account:
- Average acquisition cost for U.S. spot ETF and ETP holders, near $83,000
- Active investor cost basis, around $78,000, excluding coins rewarded to miners
Those figures sit above the reported spot level near February’s lows. Bitcoin Magazine describes that as a ceiling of overhead supply, not a support floor. In other words, many recent entrants are underwater, so selling can persist until losses get processed.
Glassnode data is brought in for corroboration. Bitcoin Magazine says an attempted rally stalled at the aggregate ETF cost basis near $83,000. It also cites “total realized losses” spiking to $1.35 billion per day and long-term holders capitulating from cycle-top positions.
Hedge funds complicate the story. Bitcoin Magazine reports that hedge funds hold about 30% of spot ETP ownership but run market-neutral basis trades rather than directional bets. That setup, per the reporting, means they do not naturally step in with bid support when prices fall.
Mining-to-inference: how miners might monetize power
Ferraioli’s construction becomes more bullish in a very specific way. Bitcoin Magazine says every major publicly traded Bitcoin miner has announced a pivot toward high-performance computing for AI inference workloads.
The desk’s point is that inference revenue can look better per megawatt-hour than mining during peak demand windows. But demand for inference is not evenly distributed across the day. Bitcoin Magazine highlights that models run during business hours and idle overnight and on weekends. That creates an opportunity for miners to avoid leaving capacity unused.
In Schwab’s model, per Bitcoin Magazine, Bitcoin mining becomes the baseload monetization of off-peak power. Inference overlays on top of peak business-hour demand. The practical pitch is utilization. Keep the facility running across a full 24-hour cycle, reduce the need for forced BTC sales to cover operating costs, and lower structural risk across bear market cycles.
Energy economics and network mechanics
The broader thesis in Bitcoin Magazine is that Bitcoin, for all its rhetoric, behaves like an energy-backed commodity. Bitcoin has no earnings, no free cash flow, and no corporate guidance, so value flows from the energy cost needed to produce it.
Bitcoin Magazine also ties the model to historical market behavior in commodity terms: prices generally cannot sit sustainably below production cost without miners shutting down, supply contracts breaking, and equilibrium resetting.
As of May 2026, Bitcoin Magazine says the average mining cost across all Bitcoin miners sits near $85,604. At the same time, Bitcoin was trading in the mid-$60,000s. Under Ferraioli’s framework, that configuration has historically preceded recoveries rather than further collapse.
The key numbers Schwab uses
| Metric | Figure | Source in text |
|---|---|---|
| BTC peak cited | ~$126,000 | Bitcoin Magazine |
| Feb low cited | ~ $60,000 | Bitcoin Magazine |
| Efficient miner cost | ~ $60,000 per BTC | Schwab via Bitcoin Magazine |
| Efficient miner energy assumption | ~$0.07 per kWh | Schwab via Bitcoin Magazine |
| Less efficient miner cost | ~ $95,000 per BTC | Glassnode via Schwab May 2026 report, cited by Bitcoin Magazine |
| Average ETF and ETP acquisition cost | ~ $83,000 | Schwab via Bitcoin Magazine |
| Active investor cost basis | ~ $78,000 | Schwab via Bitcoin Magazine |
| Realized losses spike | $1.35B per day | Glassnode via Bitcoin Magazine |
| Hedge funds’ share of spot ETP ownership | ~ 30% | Bitcoin Magazine |
| Average mining cost across all miners | ~$85,604 | Bitcoin Magazine |
| Mining cost vs price context | Mid-$60,000s price with ~$85,604 cost | Bitcoin Magazine |
Ferraioli’s case is not a promise. It is a hypothesis that production economics and investor cost bases can explain why the market may stop falling when efficient miners’ costs become the binding constraint. Schwab’s argument also implicitly depends on miners finding enough alternative monetization through AI HPC, so they can run longer without dumping BTC just to pay bills.
So if Bitcoin Magazine is right, the desk is watching energy cost curves and cost-basis positioning as much as it watches price levels. A “floor” here is conditional. When costs move or demand for power monetization shifts, the math changes.