Xiaoqin Cai

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About

Xiaoqin Cai investigates the intersection of human decision-making and algorithmic trading, focusing on how individuals interact with automated systems in financial markets. Her research explores the dynamics of human-robot collaboration, particularly when traders can choose to deploy, halt, or override algorithms. In her landmark 2024 study, "Humans in charge of trading robots: the first experiment," Cai examines how different levels of control—such as compulsory deployment versus flexible halting—affect market outcomes, revealing critical insights into trust, efficiency, and risk. Her earlier work, "For Better or For Worse: Algorithmic Choice in Experimental Markets" (2022), further dissects the consequences of giving traders the freedom to select or reject algorithmic assistance. Though her citation counts are currently modest (3 and 2 citations respectively), these pioneering experiments are foundational to understanding the behavioral economics of automated trading. Cai’s contributions are especially timely as financial markets increasingly integrate AI, and her findings have implications for designing regulatory frameworks that balance human oversight with algorithmic autonomy. Her work stands out for its innovative experimental design, directly addressing the practical challenges of human-robot interaction in high-stakes environments.