Todd Feldman

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About

Todd Feldman is a financial economist whose research bridges behavioral finance, agent-based modeling, and market microstructure. His work explores how human decision-making interacts with automated trading systems, particularly during periods of financial instability. In his highly cited study "Human and Artificial Agents in a Crash-Prone Financial Market" (2010), Feldman introduced human traders into an agent-based simulation designed to generate bubbles and crashes. This innovative experiment revealed a striking asymmetry: while human traders earned lower overall profits than their algorithmic counterparts ("robots"), they outperformed these automated agents during the most crash-intensive periods. The finding suggests that human intuition and adaptability may offer unique advantages in extreme market conditions—a counterintuitive insight with implications for both market design and trading strategy. Though early in his citation trajectory, Feldman's work has been foundational in experimental finance, demonstrating the value of hybrid human-AI market systems. His research continues to inform debates on financial stability, the limits of algorithmic trading, and the role of human judgment in increasingly automated markets.