IDEAS home Printed from https://ideas.repec.org/a/ahs/journl/v10y2025i2p549-567.html
   My bibliography  Save this article

Short-term Price Prediction in Initial Public Offerings Using XGBoost: Bist Technology Sector Example

Author

Listed:
  • Gazme Şekeroğlu
  • Ayşe Merve Acılar

Abstract

The aim of the study is to predict the closing price of the next trading day's stocks, of the initial public offering firms in the short term (between 5 and 10 days). For this purpose, firstly, the companies that went public in BIST in 2022, 2023, and 2024 are listed. Among these sectors, the decision was made to conduct the research in the technology sector, which experienced the highest number of initial public offerings in 2024. Using the model created with the XGBoost algorithm, price prediction for the Borsa Istanbul technology sector was made. The data to be used in the analyses consist of the daily closing stock prices of FORTE, which was the first IPO in 2023 and operates in the technology sector, from 15.06.2023 to 28.06.2024. It also includes the daily closing values of the BIST TECHNOLOGY and BIST IPO indices, and the first four-day closing stock prices of the technology sector companies (ODINE, PATEK, and ALTNY) that were the first IPOs in 2024. As a result of the coding steps performed using Python, it was found that the difference between the predicted prices and the actual prices gradually decreased from the fifth to the tenth day after the IPO.

Suggested Citation

  • Gazme Şekeroğlu & Ayşe Merve Acılar, 2025. "Short-term Price Prediction in Initial Public Offerings Using XGBoost: Bist Technology Sector Example," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 10(2), pages 549-567.
    • Handle: RePEc:ahs:journl:v:10:y:2025:i:2:p:549-567
    DOI: 10.30784/epfad.1622717
    as

    Download full text from publisher

    File URL: https://dergipark.org.tr/tr/download/article-file/4533149
    Download Restriction: no
    File URL: https://libkey.io/10.30784/epfad.1622717?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
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

    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:ahs:journl:v:10:y:2025:i:2:p:549-567. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Ersan Ersoy (email available below). General contact details of provider: https://epfjournal.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.