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Bitcoin whale sell-off: a single large Bitcoin holder rotated BTC into ETH and used Hyperliquid derivatives, triggering a rapid cascade of sell orders that pushed Bitcoin down ~2.2% in under 10 minutes and briefly dropped the price toward $112K.
Rapid BTC-to-ETH rotation by an OG whale caused a liquidity squeeze
Approximately 24,000 BTC moved to Hyperliquid; ~18,142 BTC (~$2B) appears sold and rotated into ETH.
Flash crash: BTC fell from $114,666 to $112,174 in nine minutes; ETH fell ~4% then partially recovered.
Bitcoin whale sell-off triggered a rapid BTC flash crash; learn how the whale’s BTC→ETH rotation and derivatives trades moved markets — read the analysis and next steps.
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Bitcoin dropped over 2% in under 10 minutes as a large OG whale rotated Bitcoin into Ether and executed leveraged derivatives positions, producing a cascade of sell orders and a temporary market dislocation. Analysis below summarizes on-chain flows, trading strategy, and potential follow-on risks.
What caused the Bitcoin flash crash to $112K?
Bitcoin whale sell-off and rotation: a long-dormant OG whale moved large BTC balances to Hyperliquid, selling roughly 18,142 BTC (~$2 billion) and rotating proceeds into ETH, which, together with closing leveraged positions, created rapid downward pressure and a brief flash crash.
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Source: Willy Woo
How did on-chain flows and concentration amplify the move?
Supply concentration among OG whales raises the amount of fresh capital required to absorb selling. Analyst Willy Woo noted that older holders bought at single-digit prices, creating a wide cost-basis gap that magnifies market impact when they sell.
Blockchain monitoring shows a cluster of transfers totalling ~24,000 BTC to Hyperliquid since Aug. 16. Of these, ~18,142 BTC appear sold and largely converted to ETH, with 416,598 ETH credited to the receiving addresses.
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How did the whale’s derivatives positions influence price action?
The whale opened large leveraged long positions in ETH (total exposure cited at 551,861 ETH) and used spot purchases to push short-term momentum. When the whale began closing longs, other traders reversed positions, precipitating a cascade of sell orders that magnified the flash crash.
Bitcoin’s change in price over the last 24 hours. Source: CoinGecko
When did the flash crash occur and how deep was the move?
CoinGecko price snapshots show BTC fell ~2.2% from $114,666 at 19:31 UTC to $112,546 in nine minutes, bottoming near $112,174. ETH declined ~4% in the same window and later recovered roughly half of the losses.
Why might the whale be pivoting to ETH long-term?
On-chain staking data indicates ~275,500 ETH (≈$1.3B) was staked, suggesting a longer-term ETH allocation beyond short-term trading. The whale’s activity is consistent with seeking ETH exposure while using derivatives to manage and monetize price moves.
Source: Jacob King
Frequently Asked Questions
Did one whale cause the entire market drop?
One large whale materially contributed to the flash crash by rotating ~24,000 BTC to Hyperliquid and selling about 18,142 BTC, but market structure, liquidity depth, and synchronized trader reactions amplified the move across BTC and ETH.
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How much BTC does the whale still hold?
Blockchain analysis shows the whale retains roughly 152,874 BTC across additional addresses — indicating potential for further market impact if more coins are moved or sold.
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Key Takeaways
Concentrated supply matters: OG whales with large cost-basis differentials can require substantial fresh capital to soak up selling.
Derivatives amplify moves: Large leveraged positions and their closure can turn spot rotations into cascade sell events.
Monitor on-chain signals: Large transfers to platforms and staking activity are early indicators of strategic reallocations.
Conclusion
Bitcoin’s brief flash crash was driven by a large whale’s rotation from BTC to ETH and strategic derivatives trading, exposing the market’s sensitivity to concentrated supply. Market participants should monitor on-chain flows and derivatives exposure closely. COINOTAG will continue tracking wallet activity and liquidity metrics for further developments.
