Machine Learning
Strategic sequential bidding in auctions using dynamic programming
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
Optimal Control of Execution Costs for Portfolios
Computing in Science and Engineering
Competitive algorithms for VWAP and limit order trading
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Electronic Trading in Order-Driven Markets: Efficient Execution
CEC '05 Proceedings of the Seventh IEEE International Conference on E-Commerce Technology
Reinforcement Learning on a Futures Market Simulator
KES-AMSTA '07 Proceedings of the 1st KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
Algorithmic trading strategy optimization based on mutual information entropy based clustering
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
Towards automated trading based on fundamentalist and technical data
SBIA'10 Proceedings of the 20th Brazilian conference on Advances in artificial intelligence
Planning under the uncertainty of the technical analysis of stock markets
IBERAMIA'10 Proceedings of the 12th Ibero-American conference on Advances in artificial intelligence
Prediction in financial markets: The case for small disjuncts
ACM Transactions on Intelligent Systems and Technology (TIST)
Modesty is the best policy: automatic discovery of viable forecasting goals in financial data
EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
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We present the first large-scale empirical application of reinforcement learning to the important problem of optimized trade execution in modern financial markets. Our experiments are based on 1.5 years of millisecond time-scale limit order data from NASDAQ, and demonstrate the promise of reinforcement learning methods to market microstructure problems. Our learning algorithm introduces and exploits a natural "low-impact" factorization of the state space.