EconPapers    
Economics at your fingertips  
 

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

Viktor Manahov ()
Additional contact information
Viktor Manahov: The University of York

Annals of Operations Research, 2018, vol. 260, issue 1, 321-352

Abstract: 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 markets; High frequency trading; Algorithmic trading; Evolutionary algorithms; Market regulation; Market efficiency (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://link.springer.com/10.1007/s10479-016-2286-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:260:y:2018:i:1:d:10.1007_s10479-016-2286-1

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla ().

 
Page updated 2019-11-06
Handle: RePEc:spr:annopr:v:260:y:2018:i:1:d:10.1007_s10479-016-2286-1