Analysis: AI trading agents may change the high-frequency trading-driven model by linking returns to client portfolio performance

According to Odaily, as AI trading agents enter the financial markets, the structural issues of retail trading are facing potential changes. The current business model of exchanges and brokers relies on frequent customer trading to generate profit through commissions, spreads, and order flow. Research shows that 74% to 89% of retail investors ultimately incur losses, and the payment for order flow mechanism behind zero-commission trading means platform profits are independent of client returns. Independent, programmable AI trading agents can encourage disciplined trading rather than trading frequency by linking the agent’s earnings to the client’s portfolio performance. These agents can also align interests by reducing positions, avoiding impulsive operations, and protecting client assets in highly volatile markets. (CoinDesk)