Bernstein analysts reiterated a $150,000 bitcoin value goal for the top of 2026, arguing the present drawdown is the “weakest bear case” within the asset’s historical past.
The notice, led by Gautam Chhugani, framed the selloff as a disaster of confidence moderately than a breakdown in bitcoin’s underlying system.
The analysts wrote:
“What we’re experiencing is the weakest bitcoin bear case in its historical past.”
Why Bernstein says this cycle is completely different
Bernstein stated the same old triggers seen in previous downturns haven’t appeared, citing no main failures, hidden leverage, or systemic blowups.
As an alternative, it pointed to institutional alignment, together with a pro-bitcoin U.S. president, rising spot ETF adoption, and rising company treasury participation.
US spot bitcoin ETF infrastructure was highlighted as a channel positioned to profit if liquidity situations enhance, alongside company capital-raising mechanisms.
Liquidity, gold, and the macro backdrop
Responding to claims that bitcoin has lagged gold throughout latest macro volatility, the analysts stated bitcoin nonetheless trades primarily as a liquidity-sensitive threat asset moderately than a mature secure haven.
They added that tighter monetary situations and elevated charges have concentrated features in choose areas similar to treasured metals and AI-linked equities.
Quantum and forced-selling issues
Bernstein additionally pushed again on arguments that bitcoin is shedding relevance in an AI-driven financial system, saying programmable wallets and blockchains match an rising “agentic” atmosphere.
On quantum computing, the agency stated future cryptographic dangers warrant preparation however argued bitcoin will not be uniquely uncovered versus different mission-critical programs.
The notice additionally dismissed fears round leveraged company accumulation and miner capitulation, citing feedback that Technique would solely want restructuring if bitcoin fell to $8,000 and stayed there for 5 years.
Bernstein stated miners have diversified by reallocating energy property towards AI knowledge heart demand, decreasing production-cost stress and forced-selling threat.