分析：AI交易代理或终结交易所高频交易模式，为散户带来公平激励

Odaily Planet Daily News: With the entry of AI trading agents into financial markets, the structural issues facing retail trading are undergoing potential changes. The current business models of exchanges and brokerages rely on high-frequency customer trading, profiting from commissions, spreads, and order flow regardless of gains or losses. Research shows that 74% to 89% of retail traders end up losing money, while the Payment for Order Flow (PFOF) mechanism hidden behind commission-free trading makes platform profits independent of customer returns.

Independent, programmable AI trading agents can address this structural contradiction: by linking agent compensation to customer portfolio returns, they encourage disciplined trading rather than trading frequency. Agents can choose to reduce positions, avoid impulsive actions, and protect customer assets in highly volatile markets, achieving true alignment of interests.

With the U.S. abolishing minimum asset requirements for day trading and the EU set to implement a PFOF ban, traditional exchange models are facing regulatory pressure. Meanwhile, AI agents are reconstructing trading architectures through innovative channels such as on-chain payments, gasless transactions, and decentralized exchanges, providing retail traders with transparent, fair, and verifiable trading intermediaries. (CoinDesk)