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A solo developer has built a pre-trade risk check tool for Solana trading agents that detects insider wallet clusters via shared first funders, providing a JSON API with safety scores and risk signals.
This paper introduces META, a multi-agent framework with episodic memory for financial trading that integrates specialized indicator agents to improve decision-making under market regimes.
Binance announces new bStock listings, enabling users to trade AGPUB, AMCB, and CYPHB against USDT with 24/7 access and 1:1 free exchange for actual stocks.
FinRL is an open-source framework for financial reinforcement learning, with about 16,000 stars on GitHub, supporting training and backtesting for trading in stocks, cryptocurrencies, etc., and pointing to the next-generation version FinRL-X.
This paper introduces the Generic Multi-Agent Trading System (GMATS) framework to study adversarial attacks on LLM-based trading systems, showing that even simple input attacks can degrade performance but robust system designs can improve robustness.
ViperQ is a reinforcement learning trading system that uses Auction Market Theory primitives for state representation, demonstrating high ROI in backtests on financial tick data for stocks like TSLA and NVDA.
A 13-year-old boy created a script for trading on Polymarket, shared it for free on GitHub, and later received $20,000 from a trader who made over $200,000 using it.
BinanceUS promotes instant account funding using credit or debit cards for quick cryptocurrency trading.
A wallet address spent $2.9K on Robinhood chain to buy $AI token, achieving a 183x return and earning $531.7K. Another new wallet made $62.7K in 17 hours.
TrustWallet announces a significant update with enhanced trading features such as 5x faster price and orderbook processing, advanced charts, and improved UI, scheduled for release next week.
Binance Thailand shares questions about trading styles and warns about the high risk of investing in cryptocurrencies.
The article discusses a research paper where LLMs used to write and review a trading feature missed a future-data bug, highlighting the need for structural redesigns in agent systems to prevent such issues.
During intense volatility in the cryptocurrency market, a user shared the performance differences between Binance and OKX applications, noting that Binance's system recovered more quickly under high traffic, while OKX remained relatively normal.
The paper explains how removing market beta and factor exposure reveals true trading signals, emphasizing rigorous stress testing to avoid overfitting and false confidence in backtests.
Grok AI has learned market strategies, including two phases and a three-step approach, involving economic concepts such as Federal Reserve policies, market volatility, and asset performance.
Binance introduces Agent OS, a new platform that integrates AI agents with market intelligence, trading, and payment capabilities to automate cryptocurrency trading.
Binance has launched Agent OS, a platform enabling AI agents to analyze markets and execute cryptocurrency trades on users' behalf, with built-in controls for security and permission management.
The author built PortfolioLab, an AI agent pipeline for trading that stages models through backtesting, paper trading, and read-only API execution to prevent premature exposure to real money. They are seeking feedback on trust patterns in AI agent architectures for high-stakes applications.
CME Group is launching futures contracts tied to AI computing power, allowing companies to trade and hedge GPU rental costs based on Silicon Data indexes.
A new open-source Python framework called TradingAgents has been released for multi-agent LLM trading, and it's available for free.