An Application of Support Vector Machines in the Prediction of Acquisition Targets: Evidence from the EU Banking Sector
In: Handbook of Financial Engineering
Author
Abstract
Suggested Citation
DOI: 10.1007/978-0-387-76682-9_14
Download full text from publisher
To our knowledge, this item is not available for download. To find whether it is available, there are three options:1. Check below whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Katsafados, Apostolos G. & Androutsopoulos, Ion & Chalkidis, Ilias & Fergadiotis, Manos & Leledakis, George N. & Pyrgiotakis, Emmanouil G., 2020. "Textual Information and IPO Underpricing: A Machine Learning Approach," MPRA Paper 103813, University Library of Munich, Germany.
- Apostolos G. Katsafados & Dimitris Anastasiou, 2024.
"Short-term prediction of bank deposit flows: do textual features matter?,"
Annals of Operations Research, Springer, vol. 338(2), pages 947-972, July.
- Katsafados, Apostolos & Anastasiou, Dimitris, 2022. "Short-term Prediction of Bank Deposit Flows: Do Textual Features matter?," MPRA Paper 111418, University Library of Munich, Germany.
- Pasiouras, Fotios & Tanna, Sailesh, 2010. "The prediction of bank acquisition targets with discriminant and logit analyses: Methodological issues and empirical evidence," Research in International Business and Finance, Elsevier, vol. 24(1), pages 39-61, January.
- Pasiouras, Fotios & Gaganis, Chrysovalantis & Zopounidis, Constantin, 2010. "Multicriteria classification models for the identification of targets and acquirers in the Asian banking sector," European Journal of Operational Research, Elsevier, vol. 204(2), pages 328-335, July.
More about this item
Keywords
Support Vector Machine; Banking Sector; European Central Bank; Probabilistic Neural Network; Radial Basis Function Kernel;All these keywords.
Statistics
Access and download statisticsCorrections
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:spr:spochp:978-0-387-76682-9_14. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.