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

Viktor Manahov

doi:10.1007/s10479-016-2286-1

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

Viktor Manahov

Management

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	321-352
Number of pages	32
Journal	Annals of Operations Research
Volume	260
Issue number	1-2
Early online date	25 Aug 2016
DOIs	https://doi.org/10.1007/s10479-016-2286-1
Publication status	Published - 1 Jan 2018

Keywords

Algorithmic trading
Commodities markets
Evolutionary algorithms
High frequency trading
Market efficiency
Market regulation

Access to Document

10.1007/s10479-016-2286-1

Cite this

@article{ce1eb9beb17f4f9584dca38ca9fdf5d8,

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

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 = "Algorithmic trading, Commodities markets, Evolutionary algorithms, High frequency trading, Market efficiency, Market regulation",

author = "Viktor Manahov",

year = "2018",

month = jan,

day = "1",

doi = "10.1007/s10479-016-2286-1",

language = "English",

volume = "260",

pages = "321--352",

journal = "Annals of Operations Research",

issn = "1572-9338",

publisher = "Springer",

number = "1-2",

}

TY - JOUR

T1 - The rise of the machines in commodities markets:

T2 - new evidence obtained using Strongly Typed Genetic Programming

AU - Manahov, Viktor

PY - 2018/1/1

Y1 - 2018/1/1

N2 - 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.

AB - 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.

KW - Algorithmic trading

KW - Commodities markets

KW - Evolutionary algorithms

KW - High frequency trading

KW - Market efficiency

KW - Market regulation

UR - http://www.scopus.com/inward/record.url?scp=84983419698&partnerID=8YFLogxK

U2 - 10.1007/s10479-016-2286-1

DO - 10.1007/s10479-016-2286-1

M3 - Article

SN - 1572-9338

VL - 260

SP - 321

EP - 352

JO - Annals of Operations Research

JF - Annals of Operations Research

IS - 1-2

ER -