IDEAS home Printed from https://ideas.repec.org/a/acc/malfin/v37y2022i117p215-232.html
   My bibliography  Save this article

BIST Corporate Governance Index Price Prediction With a Facebook Prophet Analysis Method

Author

Listed:
  • Güzhan Gülay

    (Borsa İstanbul)

  • Veclal Gündüz

    (Bahcesehir Cyprus University)

  • Erdem Öncü

    (University Of Mediterranean Karpasia)

  • Hüseyin Karşılı

    (Bahcesehir Cyprus University)

Abstract

At the core of corporate governance are various financial policies that consider maximizing the wealth of shareholders as the main objective. Corporate governance has become a multidisciplinary subject in recent years. In Turkish Capital Markets the Corporate Governance Index (XKURY), which is calculated with the market prices of the companies selected according to the criteria determined within the scope of corporate governance data within the body of Borsa Istanbul (BIST), is of great importance as the tool in which the effect of corporate governance criteria on companies is best observed. In this study, which aims to test the effectiveness of this index and therefore the corporate governance criteria, Facebook Prophet Analysis (FPA), a new and ambitious analysis method, was used and the value estimates of the index for the year 2022 were made using the daily values of the index between 01.03.2019 and 30.11.2021. The results show that the index will start with an upward trend in the first half of 2022, and after the first quarter, it will enter a downward trend and move below its value at the beginning of the year. However, it is observed that it will enter a continuous upward trend from the second half of the year and close the year 2022 with an increase in a trend pattern similar to the previous year. The consistency of the FPA method used was measured by the Mean Absolute Percent Error (MAPE) method and the low rates obtained showed that the results of FPA method were consistent. In another analysis on consistency.

Suggested Citation

  • Güzhan Gülay & Veclal Gündüz & Erdem Öncü & Hüseyin Karşılı, 2022. "BIST Corporate Governance Index Price Prediction With a Facebook Prophet Analysis Method," Journal of Finance Letters (Maliye ve Finans Yazıları), Maliye ve Finans Yazıları Yayıncılık Ltd. Şti., vol. 37(117), pages 215-232, April.
  • Handle: RePEc:acc:malfin:v:37:y:2022:i:117:p:215-232
    DOI: https://doi.org/10.33203/mfy.1081901
    as

    Download full text from publisher

    File URL: https://dergipark.org.tr/en/download/article-file/2286005
    Download Restriction: no

    File URL: https://libkey.io/https://doi.org/10.33203/mfy.1081901?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
    ---><---

    References listed on IDEAS

    as
    1. Joey Wenling Yang & Jerry Parwada, 2012. "Predicting stock price movements: an ordered probit analysis on the Australian Securities Exchange," Quantitative Finance, Taylor & Francis Journals, vol. 12(5), pages 791-804, October.
    2. Fábio Frezatti, 2007. "The “economic paradigm” in management accounting: Return on equity and the use of various management accounting artifacts in a Brazilian context," Managerial Auditing Journal, Emerald Group Publishing, vol. 22(5), pages 514-532, May.
    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. Dimitrakopoulos, Stefanos & Tsionas, Mike, 2019. "Ordinal-response GARCH models for transaction data: A forecasting exercise," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1273-1287.
    2. Dimitrakopoulos, Stefanos & Dey, Dipak K., 2017. "Discrete-response state space models with conditional heteroscedasticity: An application to forecasting the federal funds rate target," Economics Letters, Elsevier, vol. 154(C), pages 20-23.
    3. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos & Verousis, Thanos, 2020. "A conditional fuzzy inference approach in forecasting," European Journal of Operational Research, Elsevier, vol. 283(1), pages 196-216.
    4. Liu, Keyan & Zhou, Jianan & Dong, Dayong, 2021. "Improving stock price prediction using the long short-term memory model combined with online social networks," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    5. Dimitrakopoulos, Stefanos & Tsionas, Mike G. & Aknouche, Abdelhakim, 2020. "Ordinal-response models for irregularly spaced transactions: A forecasting exercise," MPRA Paper 103250, University Library of Munich, Germany, revised 01 Oct 2020.
    6. Rasika Yatigammana & Shelton Peiris & Richard Gerlach & David Edmund Allen, 2018. "Modelling and Forecasting Stock Price Movements with Serially Dependent Determinants," Risks, MDPI, vol. 6(2), pages 1-22, May.

    More about this item

    Keywords

    Corporate Governance; Facebook Prophet Analysis; Price Forecasting;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:acc:malfin:v:37:y:2022:i:117:p:215-232. 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: Süleyman Kale (email available below). General contact details of provider: https://dergipark.org.tr/en/pub/mfy .

    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.