IDEAS home Printed from https://ideas.repec.org/a/aio/fpvfcf/v1y2015i17p113-121.html
   My bibliography  Save this article

Algorithmic Trading at Bucharest Stock Exchange

Author

Listed:
  • Adrian Victor SANDITA

    (University of Craiova Faculty of Economics and Business Administration)

Abstract

Very conservative estimates indicate that over 40% of transactions on the stock exchanges in the United States are based on automatically generated orders. Such systems are designed to do algorithmic trading on the basis of a predefined set of rules that determine the composition of the portfolio and the moment in which the purchases and sales of securities are done. Applying highly diverse trading strategies, algorithmic trading systems ultimately aim to maximize profit and minimize risk taking. Algorithmic trading on the Bucharest Stock Exchange is still in its incipient phase. Now, automated trading systems are used only for participants who act as Market Makers for the actions of a few issuers. Estimates indicate a volume of algorithmic trading on the Bucharest Stock Exchange of under 1% of its total transactions. This paper aims to describe a general way that algorithmic trading systems can be connected to the Bucharest Stock Exchange and to present some of our results in the implementation of such a system.

Suggested Citation

  • Adrian Victor SANDITA, 2015. "Algorithmic Trading at Bucharest Stock Exchange," Finante - provocarile viitorului (Finance - Challenges of the Future), University of Craiova, Faculty of Economics and Business Administration, vol. 1(17), pages 113-121, December.
    • Handle: RePEc:aio:fpvfcf:v:1:y:2015:i:17:p:113-121
    as

    Download full text from publisher

    File URL: http://feaa.ucv.ro/FPV/017-013.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hendershott, Terrence & Riordan, Ryan, 2013. "Algorithmic Trading and the Market for Liquidity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(4), pages 1001-1024, August.
    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. Marios Panayides & Barbara Rindi & Ingrid M.Werner, 2017. "Trading Fees and Intermarket Competition," BAFFI CAREFIN Working Papers 1751, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    2. NIdhi Aggarwal & Venkatesh Panchapagesan & Susan Thomas, 2022. "When is the Order to Trade Ratio fee effective?," Working Papers 8, xKDR.
    3. Robert J. Kauffman & Yuzhou Hu & Dan Ma, 2015. "Will high-frequency trading practices transform the financial markets in the Asia Pacific Region?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-27, December.
    4. 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.
    5. Ben Ammar, Imen & Hellara, Slaheddine, 2022. "High-frequency trading, stock volatility, and intraday crashes," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 337-344.
    6. George Jiang & Ingrid Lo & Giorgio Valente, 2014. "High-Frequency Trading around Macroeconomic News Announcements: Evidence from the U.S. Treasury Market," Staff Working Papers 14-56, Bank of Canada.
    7. Aggarwal, Nidhi & Panchapagesan, Venkatesh & Thomas, Susan, 2023. "When is the order-to-trade ratio fee effective?," Journal of Financial Markets, Elsevier, vol. 62(C).
    8. Breckenfelder, Johannes, 2019. "Competition among high-frequency traders, and market quality," Working Paper Series 2290, European Central Bank.
    9. Ya‐Kai Chang & Robin K. Chou, 2022. "Algorithmic trading and market quality: Evidence from the Taiwan index futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1837-1855, October.
    10. Chordia, Tarun & Miao, Bin, 2020. "Market efficiency in real time: Evidence from low latency activity around earnings announcements," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    11. Boilard, J.-F. & Kanazawa, K. & Takayasu, H. & Takayasu, M., 2018. "Empirical scaling relations of market event rates in foreign currency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1152-1161.
    12. Karkowska, Renata & Palczewski, Andrzej, 2023. "Does high-frequency trading actually improve market liquidity? A comparative study for selected models and measures," Research in International Business and Finance, Elsevier, vol. 64(C).
    13. Comerton-Forde, Carole & Jones, Charles M. & Putniņš, Tālis J., 2016. "Shorting at close range: A tale of two types," Journal of Financial Economics, Elsevier, vol. 121(3), pages 546-568.
    14. Biais, Bruno & Foucault, Thierry & Moinas, Sophie, 2015. "Equilibrium fast trading," Journal of Financial Economics, Elsevier, vol. 116(2), pages 292-313.
    15. Austin Gerig & David Michayluk, 2010. "Automated Liquidity Provision and the Demise of Traditional Market Making," Papers 1007.2352, arXiv.org.
    16. Delaney, L., 2016. "Equilibrium Investment in High Frequency Trading Technology: A Real Options Approach," Working Papers 15/14, Department of Economics, City University London.
    17. Ramos, Henrique Pinto & Righi, Marcelo Brutti, 2020. "Liquidity, implied volatility and tail risk: A comparison of liquidity measures," International Review of Financial Analysis, Elsevier, vol. 69(C).
    18. Davis, Ryan L. & Roseman, Brian S. & Van Ness, Bonnie F. & Van Ness, Robert, 2017. "1-share orders and trades," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 109-117.
    19. Corsetti, Giancarlo & Lafarguette, Romain & Mehl, Arnaud, 2019. "Fast trading and the virtue of entropy: evidence from the foreign exchange market," Working Paper Series 2300, European Central Bank.
    20. 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.

    More about this item

    Keywords

    Algorithmic trading; Multi Agent Systems; Information management; Bucharest Stock Exchange;
    All these keywords.

    JEL classification:

    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

    Statistics

    Access and download statistics

    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:aio:fpvfcf:v:1:y:2015:i:17:p:113-121. 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: Alina Manta (email available below). General contact details of provider: https://edirc.repec.org/data/fecraro.html .

    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.