Arbeitspapier

Rating Companies with Support Vector Machines

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.

Language
Englisch

Bibliographic citation
Series: DIW Discussion Papers ; No. 416

Classification
Wirtschaft
Neural Networks and Related Topics
Bankruptcy; Liquidation
Semiparametric and Nonparametric Methods: General
Subject
Support vector machines
Company rating
Default probability estimation
Kreditwürdigkeit
Mustererkennung
Schätzung
Theorie
Vereinigte Staaten
support vector machine

Event
Geistige Schöpfung
(who)
Schäfer, Dirk
Moro, R. A.
Härdle, Wolfgang Karl
Event
Veröffentlichung
(who)
Deutsches Institut für Wirtschaftsforschung (DIW)
(where)
Berlin
(when)
2004

Handle
Last update
10.03.2025, 11:45 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Schäfer, Dirk
  • Moro, R. A.
  • Härdle, Wolfgang Karl
  • Deutsches Institut für Wirtschaftsforschung (DIW)

Time of origin

  • 2004

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