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http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/7271| Title: | Modeling Stock Order Flows and Learning Market-Making from Data |
| Keywords: | AI input/output HMM market-making reinforcement learning stock order flow model |
| Issue Date: | 9-Oct-2013 |
| Description: | Stock markets employ specialized traders, market-makers, designed to provide liquidity and volume to the market by constantly supplying both supply and demand. In this paper, we demonstrate a novel method for modeling the market as a dynamic system and a reinforcement learning algorithm that learns profitable market-making strategies when run on this model. The sequence of buys and sells for a particular stock, the order flow, we model as an Input-Output Hidden Markov Model fit to historical data. When combined with the dynamics of the order book, this creates a highly non-linear and difficult dynamic system. Our reinforcement learning algorithm, based on likelihood ratios, is run on this partially-observable environment. We demonstrate learning results for two separate real stocks. |
| URI: | http://koha.mediu.edu.my:8181/xmlui/handle/1721 |
| Other Identifiers: | AIM-2002-009 CBCL-217 http://hdl.handle.net/1721.1/7271 |
| Appears in Collections: | MIT Items |
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