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Longs bear $125M of $144M crypto liquidation wave
Longs absorbed $125M of a $144M crypto liquidation wave in just four hours. CoinGlass data shows the crowded trade behind the cascade and what confirms more risk ahead.
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A concentrated wave of forced closures swept crypto futures markets over a four-hour window. CoinGlass data shows total liquidations reached $144 million, with long positions absorbing $125 million – roughly 87% of the total. The event is a textbook example of how crowded leverage on one side of the market can unwind violently.
Liquidations occur when a trader’s position loses enough value that the exchange closes the trade automatically. The process often accelerates in a cascade: a price move against the crowded side triggers margin calls, which force more selling, which triggers additional margin calls.
Four Hours, $144M in Forced Closures
CoinGlass Data Shows 87% Were Longs
CoinGlass, the primary real-time liquidation tracker across centralized exchanges, captured the event on its four-hour timeframe. The dashboard shows that long positions accounted for the vast majority of forced closures. Short positions contributed roughly $19 million, a figure within normal volatility bounds.
Binance and Bybit Carried the Bulk
Major derivatives exchanges Binance and Bybit typically host the highest liquidation volumes during sharp moves. This event followed that pattern. Long liquidation rates on those platforms exceeded 90% of total forced closures during the window. Bitcoin (BTC) and Ethereum (ETH) led the asset-specific breakdown, consistent with their dominance in futures open interest.
The Cascade Mechanism: Crowded Trades and Margin Calls
Why a 2-3% Move Triggers Much Larger Losses
When a large number of traders pile into the same directional bet, the market becomes fragile. A relatively small price move against the crowded side can trigger margin calls. Those forced sells push prices further, hitting more liquidation levels. In this case, a move of roughly 2-3% against long positions was enough to spark the cascade.
Key insight: The liquidation data does not show the underlying cause of the initial price move. That trigger could have been an ETF flow shift, a macro data release, or profit-taking. The cascade effect multiplied the damage.