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USD 137M Hyperliquid Whale Shorts: 40x BTC and 20x ETH After USD 11.6M ETH Profit, Liquidation Prices 129,848 and 5,109 | Flash News Detail | Blockchain.News
Latest Update
10/5/2025 8:11:00 AM

USD 137M Hyperliquid Whale Shorts: 40x BTC and 20x ETH After USD 11.6M ETH Profit, Liquidation Prices 129,848 and 5,109

USD 137M Hyperliquid Whale Shorts: 40x BTC and 20x ETH After USD 11.6M ETH Profit, Liquidation Prices 129,848 and 5,109

According to @EmberCN, the tracked whale sold 6,037 ETH at 4,221 USD on Sep 22 after buying at 2,299 USD in June, realizing about 11.6 million USD profit, source: @EmberCN. After selling, the market kept rising and the trader opened roughly 137 million USD in shorts on Hyperliquid with about 4 million USD unrealized loss, source: @EmberCN and hyperbot.network/trader/0x8deCc13b6E83873a78126E99036F9442019FD0b5. Position details show a 40x short of 800 BTC at 120,892 entry with 129,848 liquidation and a 20x short of 8,000 ETH at 4,502 entry with 5,109 liquidation, source: @EmberCN and hyperbot.network/trader/0x8deCc13b6E83873a78126E99036F9442019FD0b5.

Source

Analysis

In the volatile world of cryptocurrency trading, a prominent whale has captured attention with bold moves that highlight the risks and rewards of high-stakes positions. According to on-chain analyst EmberCN, this trader initially purchased 6,037 ETH in June at an average price of $2,299 per token after closing out previous short positions. By September 22, the whale liquidated this entire ETH holding at $4,221, securing a substantial profit of $11.6 million as Ethereum's price surged. However, the market's upward momentum continued post-sale, prompting the trader to pivot aggressively into short positions. Over the past two days, the whale has established massive shorts on Hyperliquid, totaling $137 million in value across BTC and ETH, currently facing a floating loss of $4 million. This scenario raises critical questions for traders: is this a case of chasing losses by shorting after selling too early, or a calculated attempt to call the market top?

Breaking Down the Whale's Short Positions and Market Implications

Diving deeper into the specifics, the whale's short strategy involves high leverage, amplifying both potential gains and risks. On Bitcoin, the position includes a 40x leveraged short of 800 BTC, valued at $100 million, with an entry price of $120,892 and a liquidation price of $129,848. For Ethereum, it's a 20x leveraged short of 8,000 ETH, worth $37 million, entered at $4,502 with liquidation at $5,109. These details, tracked via Hyperliquid's on-chain data as of early October 2025, show the whale betting heavily against further upside. From a trading perspective, this move comes amid broader market rallies, where BTC and ETH have shown resilience above key support levels. For instance, Bitcoin has been testing resistance around $120,000-$130,000, while Ethereum hovers near $4,500-$5,000. Traders monitoring these levels might see opportunities in volatility plays, such as longing dips below support or shorting breakouts above resistance, but the whale's floating loss underscores the peril of over-leveraged bets in a bullish environment.

Trading Opportunities Amid Whale Activity

For retail and institutional traders, this whale's actions offer valuable insights into market sentiment and potential reversals. The initial ETH sale at $4,221 preceded a continued uptrend, suggesting the whale may have underestimated bullish catalysts like network upgrades or institutional inflows. Now, with $137 million shorted and $4 million in unrealized losses as of the latest data, this could signal overconfidence in a downturn. Crypto traders might consider contrarian strategies, such as buying ETH on pullbacks toward $4,000 support, where historical volume data indicates strong buying interest. On-chain metrics, including increased ETH trading volumes on platforms like Hyperliquid, point to heightened liquidity that could fuel quick reversals. Meanwhile, BTC's position near its all-time highs invites analysis of cross-market correlations; if Bitcoin breaks above $130,000, it could drag ETH higher, potentially liquidating the whale's shorts and creating cascading buying pressure. Risk management is key here—traders should set stop-losses around these liquidation prices to capitalize on volatility without excessive exposure.

Broader market context ties this event to ongoing trends in cryptocurrency and even stock markets, where AI-driven sentiment influences crypto valuations. As whales like this one deploy massive capital, it affects overall liquidity and price discovery. For stock traders eyeing crypto correlations, movements in tech-heavy indices could amplify BTC and ETH volatility, offering hedging opportunities through futures or options. Ultimately, this whale's journey from profitable ETH longs to aggressive shorts serves as a cautionary tale: in crypto trading, timing the top is notoriously difficult, and leveraging up during uncertainty can lead to significant drawdowns. Traders are advised to monitor real-time on-chain data for shifts in whale behavior, potentially signaling entry points for longs if the market defies the short bias.

Reflecting on the bigger picture, this incident highlights the interplay between individual whale strategies and macroeconomic factors. With no immediate signs of reversal in the bullish trend as of October 5, 2025, the whale's $4 million floating loss might grow if positive catalysts emerge, such as regulatory approvals or ETF inflows. For those analyzing trading volumes, the surge in Hyperliquid activity around these positions indicates growing interest in leveraged perpetuals, where daily volumes have spiked. Savvy traders could explore pairs like ETH/BTC for relative value trades, betting on Ethereum's outperformance if it breaks resistance. In summary, while the whale's bold shorts present risks, they also illuminate trading opportunities in a market ripe with momentum—emphasizing the need for disciplined analysis of price levels, volumes, and on-chain indicators to navigate these turbulent waters effectively.

余烬

@EmberCN

Analyst about On-chain Analysis