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Bitcoin Caught Between Hawkish Fed and Dovish Warsh

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Bitcoin Caught Between Hawkish Fed and Dovish Warsh

The Federal Reserve’s January meeting minutes revealed a surprisingly hawkish committee. Several officials openly discussed rate hikes. That sets the stage for a dramatic policy clash when Kevin Warsh takes over as chair this summer.

The Fed’s hawkish stance now threatens to box in Warsh before he even starts, raising the stakes for both monetary policy and crypto markets.

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A Committee Tilting Hawkish — Right Before a Leadership Change

The FOMC voted 10-2 on Jan. 28 to hold rates at 3.5%-3.75%. Governors Christopher Waller and Stephen Miran dissented. Both preferred a quarter-point cut, citing labor market risks.

But the broader committee leaned the other way. Several participants warned that further easing amid elevated inflation could signal a weakened commitment to the 2% target. A larger group favored holding rates steady. They wanted a “clear indication that disinflation was firmly back on track” before cutting again.

Most strikingly, several officials wanted the post-meeting statement to reflect possible “upward adjustments” to the federal funds rate. This was a direct reference to potential rate hikes.

Powell Out, Warsh In — And a Policy Collision Looms

Chair Jerome Powell’s term ends in May. He has two more meetings at the helm. Trump announced on Jan. 30 that former Fed Governor Warsh would replace him.

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Warsh has spoken in favor of lower rates. That aligns with Trump’s repeated calls for cheaper borrowing. The White House on Wednesday insisted recent data showed inflation was “cool and stable.”

But the committee’s hawkish majority may not cooperate. Rate decisions are made by 12 voting members. Only a few lean dovish. The rest see inflation risks as the top priority.

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Analysts noted that the committee’s hawkish tone could complicate Warsh’s confirmation process and limit his room to pivot toward cuts early in his tenure.

If confirmed, Warsh’s first meeting as chair would be in June. Futures traders price the next cut around the same time. But the Fed’s preferred inflation gauge — the PCE Price Index — is expected to re-accelerate in the coming months. That could delay any easing further.

Asian Liquidity Returns, Amplifying the Selloff

Bitcoin began sliding shortly after the minutes dropped during US afternoon trading. It fell from around $68,300 to below $66,500 by early Asian morning hours. That marked a 1.6% decline over 24 hours.

The timing mattered. Asian traders were returning from the Lunar New Year holiday. Rising volumes and turnover amplified the move lower. Escalating US-Iran tensions added fuel. Oil prices surged more than 4%, further weighing on risk appetite across crypto markets.

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Coinbase CEO Brian Armstrong called the decline psychological rather than fundamental. He said the exchange was buying back shares and accumulating Bitcoin at lower prices.

What Comes Next

The Fed’s next meeting is on March 17-18. A cut there is effectively off the table. Markets now look to June as the earliest window.

But the real question extends beyond timing. It is whether Warsh can steer a deeply divided committee toward cuts while inflation remains sticky. The hawkish majority has made its position clear. Changing that will require more than a new chair.

For Bitcoin, the macro backdrop remains challenging. The combination of a hawkish Fed, a contested leadership transition, and returning Asian liquidity points to continued volatility in the weeks ahead.

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Crypto World

Moonwell’s AI-coded oracle glitch misprices cbETH at $1, drains $1.78M

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Crypto VC Funding Reaches $244M as Mesh Leads

Moonwell’s lending pools racked up about $1.78M in bad debt after a cbETH oracle mispriced the token at nearly $1 instead of around $2.2k, enabling bots and liquidators to drain collateral within hours of a misconfigured Chainlink-based update reportedly using AI-generated logic.

Summary

  • Misconfigured cbETH oracle set price near $1 vs roughly $2.2k, triggering a ~99% valuation gap that broke Moonwell’s collateral math.
  • Liquidators repaid around $1 per position to seize over 1,096 cbETH, leaving Moonwell with roughly $1.78M in protocol-level bad debt.
  • Faulty formula and scaling logic were reportedly co-authored by AI model Claude Opus 4.6, spotlighting new DeFi risk around AI-written oracle and pricing code.

Decentralized finance lending protocol Moonwell suffered a $1.78 million exploit due to a pricing oracle bug that misvalued Coinbase-wrapped ETH (cbETH), according to reports from the platform.

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The vulnerability originated in oracle calculation logic reportedly generated by the AI model Claude Opus 4.6, which introduced an incorrect scaling factor in the asset price feed, according to the protocol’s disclosure. Attackers borrowed against severely underpriced collateral, extracting funds before the error was detected and corrected.

The cbETH mispricing effectively collapsed the collateral requirement for borrowing within affected pools. Because lending systems rely on accurate collateral ratios, the incorrect price allowed attackers to extract assets with minimal backing value, according to the protocol’s technical analysis.

Price oracles represent critical security components in DeFi lending systems. Incorrect asset valuation can enable under-collateralized borrowing or liquidation failures. Many major DeFi exploits have historically involved oracle manipulation or pricing errors rather than core protocol flaws, according to industry security reports.

The Moonwell incident differs from traditional oracle exploits in that the faulty logic appears linked to automated AI code generation rather than malicious oracle data feeds, according to the protocol’s preliminary investigation.

The exploit highlights risks associated with AI-assisted smart-contract development in financial applications. Language models can accelerate coding workflows, but financial protocols require precise numerical correctness, unit handling and edge-case validation, according to blockchain security experts.

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In DeFi systems, small arithmetic or scaling mistakes can translate into systemic vulnerabilities affecting collateral valuation and solvency. The incident raises questions about whether AI-generated contract components may require stricter auditing standards than manually written code, according to security researchers.

AI-assisted development is increasingly used across Web3 engineering workflows, from contract templates to integration logic. Security models and audit frameworks have not yet fully adapted to AI-generated contract code, according to industry observers.

The broader implications center on how automated code generation errors in financial logic represent a new category of DeFi risk. Oracle math, scaling factors and unit conversions remain high-precision domains where automation failures can propagate into protocol-level vulnerabilities, according to technical analysis of the incident.

As AI-assisted smart-contract development expands, audit methodologies will likely need to evolve toward verifying not only code correctness but generation provenance and numerical invariants, according to blockchain security firms.

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Kalshi Data Could Inform Fed Reserve Policy, Say Researchers

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Kalshi Data Could Inform Fed Reserve Policy, Say Researchers

Three researchers at the US Federal Reserve argue that prediction market Kalshi can better measure macroeconomic expectations in real time than existing solutions and thus should be incorporated into the Fed’s decision-making process.

The “Kalshi and the Rise of Macro Markets” paper was released on Feb. 12 by Federal Reserve Board principal economist Anthony Diercks, Federal Reserve research assistant Jared Dean Katz and Johns Hopkins research associate Jonathan Wright.

Kalshi data was compared with traditional surveys and market-implied forecasts to examine how beliefs about future economic outcomes change in response to macroeconomic news and statements from policymakers.

Source: Tarek Mansour

“Managing expectations is central to modern macroeconomic policy. Yet the tools that are often relied upon—surveys and financial derivatives—have many drawbacks,” the researchers said, adding that Kalshi can capture the market’s “beliefs directly and in real time.”

“Kalshi markets provide a high-frequency, continuously updated, distributionally rich benchmark that is valuable to both researchers and policymakers.”

Kalshi traders can bet on a range of markets tied to the Federal Reserve’s decision-making, including consumer price index inflation and payroll, in addition to other macroeconomic outcomes such as gross domestic product growth and gas prices.

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The Fed researchers said Kalshi data should be used to provide a risk-neutral probability density function, which shows all possible outcomes of Fed interest rate decisions and how likely each one is. 

“Overall, we argue that Kalshi should be used to provide risk-neutral [probability density functions] concerning FOMC decisions at specific meetings” arguing that the current benchmark is “too far removed from the monetary policy interest rate decision.”

However, Fed research papers are only “preliminary materials circulated to stimulate discussion” and do not impact the central bank’s decision-making.