IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v260y2018i1d10.1007_s10479-016-2286-1.html
   My bibliography  Save this article

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

Author

Listed:
  • Viktor Manahov

    (The University of York)

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.

Suggested Citation

  • Viktor Manahov, 2018. "The rise of the machines in commodities markets: new evidence obtained using Strongly Typed Genetic Programming," Annals of Operations Research, Springer, vol. 260(1), pages 321-352, January.
    • Handle: RePEc:spr:annopr:v:260:y:2018:i:1:d:10.1007_s10479-016-2286-1
    DOI: 10.1007/s10479-016-2286-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-016-2286-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-016-2286-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. repec:hal:wpspec:info:hdl:2441/f6h8764enu2lskk9p4oq9ig8k is not listed on IDEAS
    2. Sandrine Jacob Leal & Mauro Napoletano & Andrea Roventini & Giorgio Fagiolo, 2016. "Rock around the clock: An agent-based model of low- and high-frequency trading," Journal of Evolutionary Economics, Springer, vol. 26(1), pages 49-76, March.
    3. Biais, Bruno & Foucault, Thierry & Moinas, Sophie, 2015. "Equilibrium fast trading," Journal of Financial Economics, Elsevier, vol. 116(2), pages 292-313.
    4. repec:hal:spmain:info:hdl:2441/f6h8764enu2lskk9p4oq9ig8k is not listed on IDEAS
    5. Meade, Nigel, 2002. "A comparison of the accuracy of short term foreign exchange forecasting methods," International Journal of Forecasting, Elsevier, vol. 18(1), pages 67-83.
    6. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    7. Albert J. Menkveld & Marius A. Zoican, 2017. "Need for Speed? Exchange Latency and Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1188-1228.
    8. Edward Sun & Timm Kruse & Min-Teh Yu, 2014. "High frequency trading, liquidity, and execution cost," Annals of Operations Research, Springer, vol. 223(1), pages 403-432, December.
    9. Alex Frino & Vito Mollica & Robert I. Webb, 2014. "The Impact of Co‐Location of Securities Exchanges' and Traders' Computer Servers on Market Liquidity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(1), pages 20-33, January.
    10. Benos, Evangelos & Sagade, Satchit, 2012. "High-frequency trading behaviour and its impact on market quality: evidence from the UK equity market," Bank of England working papers 469, Bank of England.
    11. Eric Budish & Peter Cramton & John Shim, 2015. "Editor's Choice The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1547-1621.
    12. DeFusco, Richard A & Johnson, Robert R & Zorn, Thomas S, 1990. "The Effect of Executive Stock Option Plans on Stockholders and Bondholders," Journal of Finance, American Finance Association, vol. 45(2), pages 617-627, June.
    13. Dwight R. Sanders and Scott H. Irwin, 2013. "Measuring Index Investment in Commodity Futures Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    14. Connolly, Robert A., 1989. "An Examination of the Robustness of the Weekend Effect," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(2), pages 133-169, June.
    15. Thierry Foucault & Roman Kozhan & Wing Wah Tham, 2017. "Toxic Arbitrage," The Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1053-1094.
    16. Ben R. Marshall & Nhut H. Nguyen & Nuttawat Visaltanachoti, 2012. "Commodity Liquidity Measurement and Transaction Costs," The Review of Financial Studies, Society for Financial Studies, vol. 25(2), pages 599-638.
    17. Eugene F. Fama & Kenneth R. French, 2015. "Commodity Futures Prices: Some Evidence on Forecast Power, Premiums, and the Theory of Storage," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 4, pages 79-102, World Scientific Publishing Co. Pte. Ltd..
    18. Hasbrouck, Joel & Saar, Gideon, 2009. "Technology and liquidity provision: The blurring of traditional definitions," Journal of Financial Markets, Elsevier, vol. 12(2), pages 143-172, May.
    19. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: II. Agent-based models," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 1013-1041.
    20. Christian L. Dunis & Jason Laws & Andreas Karathanasopoulos, 2013. "GP algorithm versus hybrid and mixed neural networks," The European Journal of Finance, Taylor & Francis Journals, vol. 19(3), pages 180-205, March.
    21. Wu, Chih-Chiang & Chung, Huimin & Chang, Yu-Hsien, 2012. "The economic value of co-movement between oil price and exchange rate using copula-based GARCH models," Energy Economics, Elsevier, vol. 34(1), pages 270-282.
    22. Michael Goldstein & Michael A. Goldstein & Pavitra Kumar & Frank C. Graves, 2014. "Computerized and High-Frequency Trading," The Financial Review, Eastern Finance Association, vol. 49(2), pages 177-202, May.
    23. Delaney, L., 2015. "An Examination of the Optimal Timing Strategy for a Slow Trader Investing in a High Frequency Trading Technology," Working Papers 15/04, Department of Economics, City University London.
    24. Michael Goldstein & Elvis Jarnecic & Mark Snape, 2014. "The Provision of Liquidity by High-Frequency Participants," The Financial Review, Eastern Finance Association, vol. 49(2), pages 371-394, May.
    25. B. Wade Brorsen, 1989. "Liquidity costs and scalping returns in the corn futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 9(3), pages 225-236, June.
    26. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frédéric Abergel, 2011. "Econophysics review: II. Agent-based models," Post-Print hal-00621059, HAL.
    27. Joon Chae & Jaeuk Khil & Eun Jung Lee, 2013. "Who Makes Markets? Liquidity Providers Versus Algorithmic Traders," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(5), pages 397-420, May.
    28. Silber, William L, 1984. "Marketmaker Behavior in an Auction Market: An Analysis of Scalpers in Futures Markets," Journal of Finance, American Finance Association, vol. 39(4), pages 937-953, September.
    29. Miles Kumaresan & Nataša Krejić, 2015. "Optimal trading of algorithmic orders in a liquidity fragmented market place," Annals of Operations Research, Springer, vol. 229(1), pages 521-540, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhou, Hao & Kalev, Petko S., 2019. "Algorithmic and high frequency trading in Asia-Pacific, now and the future," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 186-207.
    2. Viktor Manahov, 2021. "High‐frequency trading order cancellations and market quality: Is stricter regulation the answer?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5385-5407, October.
    3. Ekinci, Cumhur & Ersan, Oğuz, 2022. "High-frequency trading and market quality: The case of a “slightly exposed” market," International Review of Financial Analysis, Elsevier, vol. 79(C).
    4. Breckenfelder, Johannes, 2024. "Competition among high-frequency traders and market quality," Journal of Economic Dynamics and Control, Elsevier, vol. 166(C).
    5. Aggarwal, Nidhi & Panchapagesan, Venkatesh & Thomas, Susan, 2023. "When is the order-to-trade ratio fee effective?," Journal of Financial Markets, Elsevier, vol. 62(C).
    6. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
    7. Oliver Linton & Soheil Mahmoodzadeh, 2018. "Implications of High-Frequency Trading for Security Markets," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 237-259, August.
    8. Frino, Alex & Mollica, Vito & Webb, Robert I. & Zhang, Shunquan, 2017. "The impact of latency sensitive trading on high frequency arbitrage opportunities," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 91-102.
    9. Gianluca Piero Maria Virgilio, 2019. "High-frequency trading: a literature review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 183-208, June.
    10. Manahov, Viktor, 2016. "A note on the relationship between high-frequency trading and latency arbitrage," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 281-296.
    11. Markus Baldauf & Joshua Mollner, 2020. "High‐Frequency Trading and Market Performance," Journal of Finance, American Finance Association, vol. 75(3), pages 1495-1526, June.
    12. Khapko, Mariana & Zoican, Marius, 2021. "Do speed bumps curb low-latency investment? Evidence from a laboratory market," Journal of Financial Markets, Elsevier, vol. 55(C).
    13. Hautsch, Nikolaus & Scheuch, Christoph & Voigt, Stefan, 2018. "Limits to arbitrage in markets with stochastic settlement latency," CFS Working Paper Series 616, Center for Financial Studies (CFS).
    14. Jørgensen, Kjell & Skjeltorp, Johannes & Ødegaard, Bernt Arne, 2018. "Throttling hyperactive robots – Order-to-trade ratios at the Oslo Stock Exchange," Journal of Financial Markets, Elsevier, vol. 37(C), pages 1-16.
    15. Brolley, Michael & Cimon, David A., 2020. "Order-Flow Segmentation, Liquidity, and Price Discovery: The Role of Latency Delays," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(8), pages 2555-2587, December.
    16. Tomy Lee, 2019. "Latency in Fragmented Markets," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 33, pages 128-153, July.
    17. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    18. Brogaard, Jonathan & Hendershott, Terrence & Riordan, Ryan, 2017. "High frequency trading and the 2008 short-sale ban," Journal of Financial Economics, Elsevier, vol. 124(1), pages 22-42.
    19. Gerig, Austin & Michayluk, David, 2017. "Automated liquidity provision," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 1-13.
    20. Breedon, Francis & Chen, Louisa & Ranaldo, Angelo & Vause, Nicholas, 2023. "Judgment day: Algorithmic trading around the Swiss franc cap removal," Journal of International Economics, Elsevier, vol. 140(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:260:y:2018:i:1:d:10.1007_s10479-016-2286-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.