Adaptive Execution: Exploration and Learning of Price Impact

DOI10.1287/opre.2015.1415zbMath1347.91146arXiv1207.6423OpenAlexW3124026636MaRDI QIDQ2795866

Beomsoo Park, Benjamin van Roy

Publication date: 22 March 2016

Published in: Operations Research (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1207.6423

zbMATH Keywords

reinforcement learningregret boundprice impactadaptive execution

Mathematics Subject Classification ID

Microeconomic theory (price theory and economic markets) (91B24) Portfolio theory (91G10)

Related Items

A reinforcement learning approach to optimal execution, Optimal portfolio execution problem with stochastic price impact, Deep learning for limit order books, Relatively robust decisions

Cites Work

• No-dynamic-arbitrage and market impact
• Continuous Auctions and Insider Trading
• Extended least squares and their applications to adaptive control and prediction in linear systems
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• Optimal execution strategies in limit order books with general shape functions
• Price Manipulation and Quasi-Arbitrage
• Least squares estimates in stochastic regression models with applications to identification and control of dynamic systems