The rise of the machines in commodities markets: new evidence obtained using Strongly Typed Genetic Programming

Advances of OR in Commodities and Financial Modelling

DOI: 10.1007/s10479-016-2286-1

Cite this article as:
Manahov, V. Ann Oper Res (2016). doi:10.1007/s10479-016-2286-1
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Abstract

Market regulators around the world are still debating whether or not high-frequency trading (HFT) is beneficial or harmful to market quality. We develop artificial commodities market populated with HFT scalpers and traditional commodities traders using Strongly Typed Genetic Programming (STGP) trading algorithm. We simulate real-life commodities trading at the millisecond timeframe by applying STGP to the S&P GSCI data stamped at the millisecond interval. We observe that HFT scalpers anticipate the order flow leading to severe damages to institutional traders. To mitigate the negative implications of HFT scalpers on commodities markets, we propose a minimum resting trading order period of more than 150 ms.

Keywords

Commodities marketsHigh frequency tradingAlgorithmic tradingEvolutionary algorithmsMarket regulationMarket efficiency

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.The University of YorkYorkUnited Kingdom