Abstract
Agent-based modeling is alternative framework for providing explanations of the behavior of financial markets. In this paper, we consider a simple agent-based model designed to understand the effects of smart order routing in a multi-market setting. The goal is to understand how the prevalence of smart order routing results in different levels of market integration. We find that only a small percentage of smart order routing results in a remarkable level of market integration.
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References
Lamont, O., Thaler, R.: Anomalies: The Law of One Price in Financial Markets. J. Econ. Perspect. 17(4), 191–202 (2003)
LeBaron, B.: Agent-based Computational Finance. Handbook of Computational Economics 2, 1187–1233 (2006)
Puneet, H., Schwartz, R.: Limit Order Trading. Journal of Finance, 1835–1861 (1996)
Securities Exchange Commission: Regulation NMS, 43–45
Preece, R.: The Structure, Regulation and Transparency of European Equity Markets under MiFID. CFA Institute Position Paper (2011)
O’Hara, M., Ye, M.: Is market fragmentation harming market quality? J. of Fin. Economics, 459–474 (2011)
Smith, E., Farmer, J., Gillemot, L., Krishnamurthy, S.: Statistical theory of the continuous double auction. Quantitative Finance 3, 481–514 (2003)
Szabolcs, M., Farmer, J.: An empirical behavioral model of liquidity and volatility. J. Econ. Dyn. Control. 34, 200–234 (2008)
Mastromatteo, I., Toth, B., Bouchaud, J.: Agent-based models for latent liquidity and concave price impact. Physical Review E. 89, 042805 (2014)
Wah, E., Wellman, M.: Latency Arbitrage, Market Fragmentation, and Efficiency: A Two-Market Model. In: Proceedings of the 14th ACM Conference on Electronic Commerce, pp. 855–872 (2013)
Mo, S., Paddrik, M., Yang, S.: A study of dark pool trading using an agent-based model. In: Proceedings of the Conference on Computational Intelligence for Financial Engineering & Economics, pp. 19–26 (2013)
Huang, W., Chen, Z.: Modeling regional linkage of financial markets. J. Econ. Behav. Organ. 99, 18–31 (2014)
Newman, M.: Power laws, Pareto distributions and Zipf’s law. Contemporary Physics 46(5), 323–351 (2005)
Lillo, F., Mike, S., Farmer, J.: Theory for long memory in supply and demand. Physical Review E 71, 066121 (2005)
Toth, B., Palit, I., Lillo, F., Farmer, J.: Why is equity order flow so persistent? J. Econ. Dyn. Control. 51, 218–239 (2015)
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Todd, A., Beling, P., Scherer, W. (2015). Agent-Based Model for Order Routing and Financial Market Integration. In: Bajo, J., et al. Trends in Practical Applications of Agents, Multi-Agent Systems and Sustainability. Advances in Intelligent Systems and Computing, vol 372. Springer, Cham. https://doi.org/10.1007/978-3-319-19629-9_3
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DOI: https://doi.org/10.1007/978-3-319-19629-9_3
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19628-2
Online ISBN: 978-3-319-19629-9
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