On a single day, 83 stock bull whales stopped out and liquidated their positions, with 121 large long positions incurring $23.6 million in total losses.

According to TradingBeats monitoring, from the opening of U.S. stock markets last night to noon today, on Hyperliquid’s HIP-3 individual stock, index, and ETF contracts, at least 83 addresses reduced or liquidated 121 million-dollar-level long positions at a loss, with total losses of approximately $23.65 million. Among these, at least 6 addresses saw individual account cumulative losses exceeding $1 million. This round of losses was mainly concentrated in individual stocks, while indices and ETFs accounted for more exit trades. S&P 500, Nasdaq 100, and their related indices and ETFs together recorded 51 loss-making position reductions, making up about 42.1% of all exited positions, with total losses of around $3.26 million, accounting for 13.8% of the total losses. Specifically, the S&P 500 mapped contract had 19 loss-making reductions, and the Nasdaq 100 had 15, totaling 34 trades, which is about 28% of all exited positions. For individual stocks, SK Hynix (its Korean stock SKHX and ADR contract SKHY) saw concentrated position reductions, while SanDisk (SNDK) recorded huge losses from a single asset. SK Hynix’s SKHX and SKHY contracts together had 28 loss-making long position reductions, totaling around $3.62 million in losses, making it the individual stock combination with the most addresses and positions involved. SanDisk (SNDK) only had 7 loss-making reductions, but its cumulative losses reached approximately $8.42 million, accounting for 35.6% of all losses, making it the single largest loss source in this round. Nebius, Meta, and Micron also saw large-scale loss exits, with losses of around $2.65 million, $2.17 million, and $1.76 million respectively. Notably, the loss size of SanDisk’s 7 positions already exceeded the total losses from all 51 exited positions of indices and ETFs. This large-scale long position retreat was mainly concentrated in individual stocks, especially those in the previously heavily held semiconductor and AI industry chains.