UCR

Computer Science and Engineering



Christian R. Shelton, Professor

An Electronic Market-Maker (2001)

by Nicholas T. Chan and Christian R. Shelton


Abstract: This paper presents an adaptive learning model for market-making under the reinforcement learning framework. Reinforcement learning is a learning technique in which agents aim to maximize the long-term accumulated rewards. No knowledge of the market envrionment, such as the order arrival or price process, is assumed. Instead, the agent learns from real-time market experience and develops explicit market-making strategies, achieving multiple objectives including the maximizing of profits and minimization of the bid-ask spread. The simulation results show initial success in bringing learning techniques to building market-making algorithms.

Download Information

Nicholas T. Chan and Christian R. Shelton (2001). "An Electronic Market-Maker." Technical report. MIT AI Lab, AI Memo 2001-005. pdf   ps ps.gz    

Bibtex citation

@techreport{ChaShe01b,
   author = "Nicholas T. Chan and Christian R. Shelton",
   title = "An Electronic Market-Maker",
   institution = "{MIT} {AI} Lab",
   type = "AI Memo",
   year = 2001,
   number = "2001-005",
   month = Apr,
}

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E-mail: cshelton@cs.ucr.edu

 


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