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Ýlk Halka Arzlarda Uzun Dönem Getirilerinin Yapay Sinir Aðlarý ile ÝMKB Ýçin Ampirik Bir Çalýþma


  • Ulas UNLU

    () (Nevsehir University)

  • Birol YILDIZ

    () (Eskisehir Osmangazi University)

  • Abdullah YALAMA

    () (Eskisehir Osmangazi University)


The purpose of this study is to estimate the long run IPO (Initial Public Offerings) returns using artificial neural network (ANN). In wide-ranging literature OLS (Ordinary Least Squares) is commonly preferred to estimate long run IPO returns. This study applies artificial neural network addition to OLS. As a result of comparing the performance of ANN and OLS, ANN has better estimation than OLS for long run IPO returns in Turkey.

Suggested Citation

  • Ulas UNLU & Birol YILDIZ & Abdullah YALAMA, 2009. "Ýlk Halka Arzlarda Uzun Dönem Getirilerinin Yapay Sinir Aðlarý ile ÝMKB Ýçin Ampirik Bir Çalýþma," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 10(1), pages 29-47, December.
  • Handle: RePEc:ist:ancoec:v:10:y:2009:i:1:p:29-47

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    Cited by:

    1. Fatih Macit & Ahmet Sekreter & Selver Seda Ada & Esra Simsek, 2015. "What Determines Post-IPO Market Performance: Evidence From Turkish IPOs," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 4(2), pages 73-79, June.

    More about this item


    Initial public offerings; long-run performance; ANN; OLS; ISE;

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G39 - Financial Economics - - Corporate Finance and Governance - - - Other


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