「Quad-Shorter with 75% Win Rate on ETH」 Goes Short 20x Leveraged on 20,000 ETH, Currently Sitting on $1.12 Million Unrealized Gain
BlockBeats News, July 29th, according to HyperInsight monitoring, the "Four-Battle ETH 75% Win Rate Whale" went short with 20x leverage on 20,000 ETH, currently with a floating profit of $1.12 million. The position is worth $75.76 million, with an opening price of $3,843 and a liquidation price of $3,999.
Previously, in June, he shorted 50,000 ETH, with a peak floating profit of $22.83 million but did not close the position. Not until early July when ETH began to rise rapidly, he closed the short position near the cost line, ending up losing $0.71 million.
You may also like

Particle Founder: The entrepreneurial insights I have gained the most from in the past year

Huang Renxun's latest podcast transcript: The future of Nvidia, the development of embodied intelligence and agents, the explosion of inference demand, and the public relations crisis of artificial intelligence

OKX Ventures Research Report: AI Agent Economic Infrastructure Research Report (Part 1)

The migration of settlement rights: B18 and the institutional starting point of on-chain banks

From Tencent and Circle: Looking at the Simple and Difficult Questions of Investment

The second half of stablecoins no longer belongs to the crypto circle

Cursor "Shell" Kimi Controversy Reversed: From Copyright Infringement Allegations to Authorized Collaboration, China's Open Source Model Once Again Becomes a Global AI Foundation

The Real Reason Tokens Don't Sell: 90% of Crypto Projects Overlook Investor Relations

Is the income of pump.fun real, earning a million dollars a day despite the market downturn?

The real reason why tokens are not selling: 90% of crypto projects neglect investor relations

Who is the true winner of the "Tokenization" narrative?

Moss: The Era of AI-Traded by Anyone | Project Introduction

Chip Smuggling Case Exposes Regulatory Loophole | Rewire News Evening Update

How a Structured AI Crypto Trading Bot Won at the WEEX Hackathon
Ritmex demonstrates how disciplined risk control and structured signals can make an AI crypto trading bot more stable and reliable on WEEX, highlighting the importance of combining execution discipline with scalable AI trading systems.

Old Indicator Fails, Three Major New Signals Emerge: BTC True Bottom May Still Be Below $60K

Meeting OpenClaw Founder at a Hackathon: What Else Can Lobsters Do?

Huang Renxun's Latest Podcast Transcript: NVIDIA's Future, Embodied Intelligence and Agent Development, Soaring Demand for Inferencing, and AI's PR Crisis
How a Structured AI Crypto Trading Bot Won at the WEEX Hackathon
Crypto_Trade shows how structured inputs and controlled adaptability can build a more stable and reliable AI crypto trading bot within the WEEX AI Trading Hackathon, highlighting a practical path toward scalable AI trading systems.