TY - CONF TI - Behavior based learning in identifying High Frequency Trading strategies T2 - 2012 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr) SP - 1 EP - 8 AU - S. Yang AU - M. Paddrik AU - R. Hayes AU - A. Todd AU - A. Kirilenko AU - P. Beling AU - W. Scherer PY - 2012 KW - Markov processes KW - commodity trading KW - electronic commerce KW - learning (artificial intelligence) KW - linear programming KW - E-Mini S&P 500 futures market KW - IRL-based approach KW - MDP KW - Markov decision process KW - behavior based learning KW - computer based algorithmic trading KW - electronic markets KW - financial asset trading KW - financial markets KW - high frequency trading strategy identification KW - inverse reinforcement learning KW - linear programming KW - optimal decision policy KW - order book dynamics KW - reward functions KW - trader behavior characterization KW - Accuracy KW - Correlation KW - Data models KW - Learning KW - Linear programming KW - Markov processes KW - Sensitivity KW - Algorithmic trading KW - High Frequency Trading KW - Inverse Reinforcement Learning KW - Limit order book KW - Markov Decision Process KW - Price impact KW - Spoofing DO - 10.1109/CIFEr.2012.6327783 JO - 2012 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr) IS - SN - 2380-8454 VO - VL - JA - 2012 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr) Y1 - 29-30 March 2012 ER -