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Estimating probabilities of default with support vector machines
Härdle, Wolfgang (contributor); Moro, Rouslan (contributor) - 2007
This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...
Persistent link: https://www.econbiz.de/10003633940
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Estimating Probabilities of Default with Support Vector Machines
Härdle, Wolfgang - 2016
This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...
Persistent link: https://www.econbiz.de/10012989283
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Learning Machines Supporting Bankruptcy Prediction
Härdle, Wolfgang - 2017
In many economic applications it is desirable to make future predictions about the financial status of a company. The focus of predictions is mainly if a company will default or not. A support vector machine (SVM) is one learning method which uses historical data to establish a classification...
Persistent link: https://www.econbiz.de/10012966307
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Learning machines supporting bankruptcy prediction
Härdle, Wolfgang; Moro, Rouslan; Hoffmann, Linda - 2010
In many economic applications it is desirable to make future predictions about the financial status of a company. The focus of predictions is mainly if a company will default or not. A support vector machine (SVM) is one learning method which uses historical data to establish a classification...
Persistent link: https://www.econbiz.de/10003973650
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Kombinierte Liquiditäts- und Solvenzkennzahlen und ein darauf basierendes Insolvenzprognosemodell für deutsche GmbHs
Perederiy, Volodymyr (contributor) - 2007
Eine große Herausforderung der multivariablen Analyse mit bilanziellen Kennzahlen besteht in der Identifikation derjenigen Kennzahlen, die zur besten Modellperformance führen und dabei möglichst leicht interpretierbar und intuitiv bleiben. Die Menge der in Frage kommenden Kennzahlen ist in...
Persistent link: https://www.econbiz.de/10003635001
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Ein Vergleich des binären Logit-Modells mit künstlichen neuronalen Netzen zur Insolvenzprognose anhand relativer Bilanzkennzahlen
Franken, Ronald (contributor) - 2007
Jahresabschlüssen von Kapitalgesellschaften abgeleitet werden können. In der aktuellen Praxis der empirischen Insolvenz- und …
Persistent link: https://www.econbiz.de/10003634014
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The Economic Value of Nonlinear Predictions in Asset Allocation
Kruse, Friedrich - 2012
Predictions of asset returns and volatilities are heavily discussed and analyzed in the finance research literature. In this paper, we compare linear and nonlinear predictions for stock- and bond index returns and their covariance matrix. We show in-sample and out-of-sample prediction accuracy...
Persistent link: https://www.econbiz.de/10013116144
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Forecasting economic activity using a neural network in uncertain times : Monte Carlo evidence and application to the German GDP
Holtemöller, Oliver; Kozyrev, Boris - Leibniz-Institut für Wirtschaftsforschung Halle - 2024
In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an...
Persistent link: https://www.econbiz.de/10014496850
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The Quality of Bankruptcy Data and its Impact on the Evaluation of Prediction Models : Creating and Testing a German Database
Huettemann, Martin - 2018
This study assesses the impact of the quality of bankruptcy data on the estimation and evaluation of bankruptcy prediction models. To meet this objective, we develop a systematic methodology to obtain bankruptcy information from corporate news releases and public sources. Then, applying this...
Persistent link: https://www.econbiz.de/10012914120
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Improving the Comparability of Insolvency Predictions (Verbesserung Der Vergleichbarkeit Von Schaetzgueteergebnissen Von Insolvenzprognosestudien) (German Version)
Bemmann, Martin - 2005
This working paper aims at improving the comparability of forecast quality measures of in-solvency prediction studies …. For this purpose, in a first step commonly used accuracy measures for categorial, ordinal and cardinal insolvency … cardinal into ordinal accuracy measures is presented, by which comparisons of insolvency prediction results of older and …
Persistent link: https://www.econbiz.de/10014064427