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ETH $2,514.19 +1.80%
BNB $750.42 -0.07%
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SOL $104.54 +1.64%
TRX $0.3387 -0.09%
DOGE $0.0911 +2.11%
ADA $0.2210 +1.01%
BCH $259.89 +1.74%
LINK $12.21 -2.07%
HYPE $86.71 +4.75%
AAVE $130.28 +0.99%
SUI $0.8159 +0.70%
XLM $0.1893 +0.52%
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first_img Renzo renamed itself Renzo Finance and launched the Hyperliquid basis trading product

The re-staking protocol Renzo Protocol announced its rebranding to Renzo Finance and launched its first on-chain structured yield product Renzo Basis, which will go live on Hyperliquid, initially supporting BTC and HYPE. Lucas Kozinski, founder of Renzo Labs, stated that basis trading earns funding rate income by simultaneously holding a spot long and a perpetual contract short. Since the long and short positions hedge each other, asset price fluctuations do not affect the yield, and users earn the fees paid by perpetual traders every hour.Renzo stated that the product achieves automation through a triple protection mechanism, including hedge protection, yield protection, and security buffer. Currently, the product does not use AI automation but relies on Hyperliquid's proxy wallet (API wallet) to conduct trading and strategy monitoring with user authorization, without holding user funds. Relevant protection parameters can be customized by users. Renzo emphasized that its product differs from competitors like Ethena and Bitwise's Superstate by being fully on-chain, self-custodied, and allowing depositors to choose assets, trading venues, and risk parameters.Renzo Basis plans to support all assets on Hyperliquid that have both spot and perpetual markets in the future and expand to other DeFi platforms, with the next stop being Lighter on Robinhood, where on-chain stock perpetual basis trading will be introduced.

Bitget August Transparency Report: Institutional Business Completes Multiple Product and Infrastructure Upgrades

Bitget released its transparency report for August 2026, disclosing its latest progress in the construction of a multi-asset trading ecosystem. In terms of U.S. stock tokens, taking rNVDA as an example, its daily trading volume reached $38.5 million, with over 4,200 users completing approximately 112,800 transactions, of which about 36% of the trading volume occurred outside regular U.S. trading hours, reflecting that rToken is becoming a core tool for investors to break through traditional trading time constraints and achieve 24/7 global asset allocation.On the institutional business front, Bitget launched an institutional-level CFD liquidity solution aimed at quantitative teams, proprietary trading firms, funds, brokers, and high-net-worth professional traders, supporting high-frequency quantitative trading, arbitrage between futures and spot, and automated trading scenarios such as EA.At the same time, the platform launched FCN (Fixed Coupon Notes), bringing traditional financial structured products into the tokenized U.S. stock market, becoming the first cryptocurrency exchange to combine the FCN structure with USDT settlement and U.S. stock rToken delivery. As related products and trading infrastructure continue to improve, Bitget is further strengthening its capabilities in institutional-level services, multi-asset coverage, and liquidity.In addition, third-party data shows that Bitget performs outstandingly in terms of liquidity and execution efficiency for tokenized stocks and stock perpetual contracts. In a liquidity benchmark test targeting the five stock spot markets of MSTR, SPY, QQQ, CRCL, and NVDA, DeFiLlama recorded Bitget with the lowest median bid-ask spread of 0.83 basis points and the deepest order book liquidity among all sample markets. In execution benchmark tests covering 36 stock perpetual contracts and 8 types of metal and commodity perpetual contracts, Bitget maintained a significant lead in approximately 90% of trading pairs.

first_img Analysis: 91% of the YC 2026 Summer Batch are AI companies, with the application layer's proportion dropping to 39%

User chris__lu posted that they compiled all 236 companies and 470 founders from the YC Summer 2026 batch, categorizing each company into an AI technology stack layer and comparing it to the Spring batch using the same criteria. This batch still has 91% related to AI. The model companies increased from 8% to 20%, the application layer decreased from 55% to 39%, horizontal applications dropped from 58 to 32, and vertical applications remained at 25%.In the Spring, 45% of companies delivered autonomous agents, while in the Summer, it was 33%, with "agent" in a one-sentence introduction dropping from 27% to 19%. 21 companies are engaged in computational infrastructure, 11 focus on inference costs, and there are also companies for training data and reinforcement learning environments. Scale AI is listed as an alternative target by 8 companies. The industrial category increased from 12% to 24%, with 45 companies delivering physical products, 24 being robots or physical AI, and 21 companies operating their own businesses rather than selling software.This batch is the youngest, with 37% of founders being students or graduates in the last two years, 59 teams are entirely student teams, the dropout rate increased from 3% to 9%, and repeat founders decreased from 32% to 23%, with 84% having a technical background. 39 from Berkeley, 32 from MIT, and 25 from Stanford. Amazon is the largest source of talent. Sales and marketing AI decreased from 18 to 6. Only 19 founders come from AI labs, accounting for 4%. 8 founding teams come from the same previous employer.
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