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Agent-Based Modelling of Stock Markets Using Existing Order Book Data

  • Conference paper
Multi-Agent-Based Simulation XIII (MABS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7838))

Abstract

We propose a new method for creating alternative scenarios for the evolution of a financial time series over short time periods. Using real order book data from the Chi-X exchange, along with a number of agents to interact with that data, we create a semi-synthetic time series of stock prices. We investigate the impact of using both simple, limited intelligence traders, along with a more realistic set of traders. We also test two different hypotheses about how real participants in the market would modify their orders in the alternative scenario created by the model. We run our experiments on 3 different stocks, evaluating a number of financial metrics for intra- and inter-day variability. Our results using realistic traders and relative pricing of real orders were found to outperform other approaches.

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Panayi, E., Harman, M., Wetherilt, A. (2013). Agent-Based Modelling of Stock Markets Using Existing Order Book Data. In: Giardini, F., Amblard, F. (eds) Multi-Agent-Based Simulation XIII. MABS 2012. Lecture Notes in Computer Science(), vol 7838. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38859-0_8

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  • DOI: https://doi.org/10.1007/978-3-642-38859-0_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38858-3

  • Online ISBN: 978-3-642-38859-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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