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Algorithmic and high-frequency trading in Borsa Istanbul

Author

Listed:
  • Oguz Ersan
  • Cumhur Ekinci

Abstract

This paper investigates the levels of algorithmic trading (AT) and high-frequency trading (HFT) in an emerging market, Borsa Istanbul (BIST), utilizing a dataset of 354 trading days between January 2013 and May 2014. We find an upward trend in AT by using common proxies: number of messages per minute and algo_trad of Hendershott et al. (2011). Mean algo_trad for BIST 100 index constituents varies between 18 and 13 which is parallel to 2003e2005 levels of NASDAQ large cap stocks. Initially, we measure HFT involvement by detecting linked messages as in the way proposed in Hasbrouck and Saar (2013). Next, we propose an extended HFT measure which captures various HFT strategies. This measure attributes approximately 6% of the orders to HFT. HFT involvement is higher in large orders (11.96%), in orders submitted by portfolio/fund management firms (10.40%), after improvement of BIST's order submission platform and tick size reduction for certain stocks.

Suggested Citation

  • Oguz Ersan & Cumhur Ekinci, 2016. "Algorithmic and high-frequency trading in Borsa Istanbul," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 16(4), pages 233-248, December.
    • Handle: RePEc:bor:bistre:v:16:y:2016:i:4:p:233-248
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    File URL: http://www.sciencedirect.com/science/article/pii/S2214845015300582
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    Citations

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    Cited by:

    1. Coskun, Yener & Cetin, Muge, 2018. "Menkul Kiymet Borsalarinda Pi̇yasa Mi̇kro Yapisi: Tasarim Ve Ri̇skler [STOCK EXCHANGE MICROSTRUCTURE: DESIGN and RISKS]," MPRA Paper 105590, University Library of Munich, Germany.
    2. Goudarzi, Mostafa & Bazzana, Flavio, 2023. "Identification of high-frequency trading: A machine learning approach," Research in International Business and Finance, Elsevier, vol. 66(C).
    3. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Karikari, Nana Kwasi & Gil-Alana, Luis Alberiko, 2022. "The outbreak of COVID-19 and stock market liquidity: Evidence from emerging and developed equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    4. Olgun, Onur & Ekinci, Cumhur & Arıkan, Ramazan, 2024. "The performance of selected high-frequency trading proxies: An application on Turkish index futures market," Finance Research Letters, Elsevier, vol. 65(C).
    5. Ekinci, Cumhur & Ersan, Oguz, 2018. "A new approach for detecting high-frequency trading from order and trade data," Finance Research Letters, Elsevier, vol. 24(C), pages 313-320.
    6. Jurich, Stephen N. & Mishra, Ajay Kumar & Parikh, Bhavik, 2020. "Indecisive algos: Do limit order revisions increase market load?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    7. Ersan, Oguz & Simsir, Serif Aziz & Simsek, Koray D. & Hasan, Afan, 2021. "The speed of stock price adjustment to corporate announcements: Insights from Turkey," Emerging Markets Review, Elsevier, vol. 47(C).
    8. 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).

    More about this item

    Keywords

    Algorithmic trading; High-frequency trading; Borsa Istanbul; Market microstructure;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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