Predicting Financial Distress of Banks Using Random Subspace Ensembles of Support Vector Machines

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F15%3A39899764" target="_blank" >RIV/00216275:25410/15:39899764 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-18476-0_14" target="_blank" >http://dx.doi.org/10.1007/978-3-319-18476-0_14</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-18476-0_14" target="_blank" >10.1007/978-3-319-18476-0_14</a>

Result language
angličtina
Original language name
Predicting Financial Distress of Banks Using Random Subspace Ensembles of Support Vector Machines
Original language description
Models for financial distress predictions of banks are increasingly important tools used as early warning signals for the whole banking systems. In this study, a model based on random subspace method is proposed to predict investment/non-investment rating grades of U.S. banks. We show that support vector machines can be effectively used as base learners in the meta-learning model. We argue that both financial and non-financial (sentiment) information are important categories of determinants in financialdistress prediction. We show that this is true for both banks and other companies.
Czech name
—
Czech description
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Project
<a href="/en/project/GA13-10331S" target="_blank" >GA13-10331S: The role of text information in corporate financial distress prediction models – country-specific and industry-specific approaches</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Artificial Intelligence Perspectives and Applications (CSOC2015)
ISBN
978-3-319-18475-3
ISSN
2194-5357
e-ISSN
—
Number of pages
10
Pages from-to
131-140
Publisher name
Springer
Place of publication
Berlin
Event location
Zlín
Event date
Apr 27, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000371407800014

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