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High-Frequency Trading, Computational Speed and Profitability: Insights from an Ecological Modelling

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Business Information Systems (BIS 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 255))

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Abstract

High-frequency traders (HFTs) account for a considerable component of equity trading but we know little about the source of their trading profits and how those are affected by such attributes as ultra-low latency or news processing power. Given a fairly modest amount of empirical evidence on the subject, we study the relation between the computational speed and HFTs’ profits through an experimental artificial agent-based equity market. Our approach relies on an ecological modelling inspired from the r/K selection theory, and is designed to assess the relative financial performance of two classes of aggressive HFT agents endowed with dissimilar computational capabilities. We use a discrete-event news simulation system to capture the information processing disparity and order transfer delay, and simulate the dynamics of the market at a millisecond level. Through Monte Carlo simulation we obtain in our empirical setting robust estimates of the expected outcome.

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Acknowledgement

This work was financed by UEFISCI, under project PN-II-PTPCCA-2013-4-1644.

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Authors and Affiliations

  1. Business Information Systems Department, Babeş-Bolyai University, Cluj-Napoca, Romania

    Alexandru Stan

Authors
  1. Alexandru Stan
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Correspondence to Alexandru Stan .

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Editors and Affiliations

  1. Department of Information Systems, Poznan Univ of Economics and Business, Poznan, Poland

    Witold Abramowicz

  2. Institut für Wirtschaftsinformatik, Universität Leipzig, Leipzig, Sachsen, Germany

    Rainer Alt

  3. Information System Institute, University of Leipzig, Leipzig, Germany

    Bogdan Franczyk

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Stan, A. (2016). High-Frequency Trading, Computational Speed and Profitability: Insights from an Ecological Modelling. In: Abramowicz, W., Alt, R., Franczyk, B. (eds) Business Information Systems. BIS 2016. Lecture Notes in Business Information Processing, vol 255. Springer, Cham. https://doi.org/10.1007/978-3-319-39426-8_1

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