Thomas P968_ Jones

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How does algorithmic trading evolve with AI integration?

Traditional algos followed rule-based instructions—buy at breakout, sell at support. AI integration allows algorithms to learn from data, adapt, and self-improve. Institutions deploy adaptive algos that optimize in real time, adjusting to volatility and liquidity. Retail traders gain access via AI-enhanced bots on popular platforms. Benefits: adaptability, efficiency, and reduced human error. Risks: overreliance, black-box opacity, and potential systemic shocks if algos misfire. AI-driven algos mark a new era: markets increasingly trade with themselves, and human traders must adapt by focusing on oversight, design, and strategic interpretation.