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Low-latency liquidity inefficiency strategies

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  • Christian Oesch
  • Dietmar Maringer

Abstract

The vast amount of high-frequency data heralds the use of new methods in financial data analysis and quantitative trading. This study delivers a proof-of-concept for a high frequency-based trading system based on an evolutionary computation method. Motivated by a theoretical liquidity asymmetry theorem from the market microstructure literature, grammatical evolution is used to exploit volume inefficiencies at the bid–ask spread. Using NASDAQ Historical TotalView-ITCH level two limit order book data, execution volumes can be tracked. This allows for testing of the strategies with minimal assumptions. The system evolves profitable and robust strategies with high returns and low risk.

Suggested Citation

  • Christian Oesch & Dietmar Maringer, 2017. "Low-latency liquidity inefficiency strategies," Quantitative Finance, Taylor & Francis Journals, vol. 17(5), pages 717-727, May.
    • Handle: RePEc:taf:quantf:v:17:y:2017:i:5:p:717-727
    DOI: 10.1080/14697688.2016.1242765
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    References listed on IDEAS

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    1. Jean-Philippe Bouchaud & Yuval Gefen & Marc Potters & Matthieu Wyart, 2004. "Fluctuations and response in financial markets: the subtle nature of 'random' price changes," Quantitative Finance, Taylor & Francis Journals, vol. 4(2), pages 176-190.
    2. Anthony Brabazon & Michael O’Neill, 2004. "Evolving technical trading rules for spot foreign-exchange markets using grammatical evolution," Computational Management Science, Springer, vol. 1(3), pages 311-327, October.
    3. Lillo Fabrizio & Farmer J. Doyne, 2004. "The Long Memory of the Efficient Market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(3), pages 1-35, September.
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