MODELING THE INFORMATION CONTENT OF THE LIMIT ORDER BOOK BY BAGGING Li, Wenyi Finance Computer science Operations research bagging high frequency trading information content machine learning profitability the limit order book I propose a bagging tree framework to study the information content of the limit order book in U.S. equity market. By measuring the predictability and profitability of the order book data up to 5 levels, I find that the limit orders book is informative. In addition to market orders, limit orders behind the best bid and ask prices also contributes to short-term future price movements. Finally, I design simple strategies to show that this information content can be effectively and consistently translated to economic value. My results may provide important implications for both researchers and market practitioners. Cooper, Ricky 2018 Dissertation application/pdf islandora:1001293 http://hdl.handle.net/10560/islandora:1001293 Illinois Institute of Technology SSB / Stuart School of Business en In Copyright http://rightsstatements.org/page/InC/1.0/ Restricted Access