AI RESEARCH
Risk-Aware Linear Bandits: Theory and Applications in Smart Order Routing
arXiv CS.LG
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ArXi:2208.02389v3 Announce Type: replace Motivated by practical considerations in machine learning for financial decision-making, such as risk aversion and large action space, we consider risk-aware bandits optimization with applications in smart order routing (SOR). Specifically, based on preliminary observations of linear price impacts made from the NASDAQ ITCH dataset, we initiate the study of risk-aware linear bandits.