أعرض تسجيلة المادة بشكل مبسط

dc.creator Schäfer, Dirk
dc.creator Moro, R. A.
dc.creator Härdle, Wolfgang Karl
dc.date 2004
dc.date.accessioned 2013-10-16T06:58:20Z
dc.date.available 2013-10-16T06:58:20Z
dc.date.issued 2013-10-16
dc.identifier http://hdl.handle.net/10419/18111
dc.identifier ppn:385540310
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/10419/18111
dc.description The goal of this work is to introduce one of the most successful among recently developed statistical techniques – the support vector machine (SVM) – to the field of corporate bankruptcy analysis. The main emphasis is done on implementing SVMs for analysing predictors in the form of financial ratios. A method is proposed of adapting SVMs to default probability estimation. A survey of practically and commercially applied methods is given. This work proves that support vector machines are capable of extracting useful information from financial data although extensive data sets are required in order to fully utilise their classification power.
dc.language eng
dc.publisher Deutsches Institut für Wirtschaftsforschung (DIW) Berlin
dc.relation DIW-Diskussionspapiere 416
dc.rights http://www.econstor.eu/dspace/Nutzungsbedingungen
dc.subject C45
dc.subject G33
dc.subject C14
dc.subject ddc:330
dc.subject Support vector machines
dc.subject Company rating
dc.subject Default probability estimation
dc.subject Kreditwürdigkeit
dc.subject Mustererkennung
dc.subject Schätzung
dc.subject Theorie
dc.subject Vereinigte Staaten
dc.subject support vector machine
dc.title Rating Companies with Support Vector Machines
dc.type doc-type:workingPaper


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أعرض تسجيلة المادة بشكل مبسط