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2016 | OriginalPaper | Chapter

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

Author : Alexandru Stan

Published in: Business Information Systems

Publisher: Springer International Publishing

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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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Metadata
Title
High-Frequency Trading, Computational Speed and Profitability: Insights from an Ecological Modelling
Author
Alexandru Stan
Copyright Year
2016
DOI
https://doi.org/10.1007/978-3-319-39426-8_1

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