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Browsing by Author "Moro, Rouslan"
Now showing items 1-7 of 7
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2009-02-17DiskussionspapierA Microeconomic Explanation of the EPK Paradox Härdle, Wolfgang Karl; Krätschmer, Volker; Moro, RouslanSupported by several recent investigations the empirical pricing kernel paradox might be considered as a stylized fact. In Chabi-Yo et al. (2008) simulation studies have been presented which suggest that this paradox might ...
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2007-04-04DiskussionspapierEmpirical Pricing Kernels and Investor Preferences Detlefsen, Kai; Härdle, Wolfgang Karl; Moro, RouslanThis paper analyzes empirical market utility functions and pricing kernels derived from the DAX and DAX option data for three market regimes. A consistent parametric framework of stochastic volatility is used. All empirical ...
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2007-06-01DiskussionspapierEstimating Probabilities of Default With Support Vector Machines Härdle, Wolfgang Karl; Moro, Rouslan; Schäfer, DorotheaThis 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 ...
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2006-11-16DiskussionspapierEstimation of Default Probabilities with Support Vector Machines Chen, Shiyi; Härdle, Wolfgang Karl; Moro, RouslanPredicting default probabilities is important for firms and banks to operate successfully and to estimate their specific risks. There are many reasons to use nonlinear techniques for predicting bankruptcy from financial ...
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2006-02-24DiskussionspapierGraphical Data Representation in Bankruptcy Analysis Härdle, Wolfgang Karl; Moro, Rouslan; Schäfer, DorotheaGraphical data representation is an important tool for model selection in bankruptcy analysis since the problem is highly non-linear and its numerical representation is much less transparent. In classical rating models a ...
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2010-06-08DiskussionspapierLearning Machines Supporting Bankruptcy Prediction Härdle, Wolfgang Karl; Moro, Rouslan; Hoffmann, LindaIn 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 ...
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2005-03-01DiskussionspapierPredicting Bankruptcy with Support Vector Machines Härdle, Wolfgang Karl; Moro, Rouslan; Schäfer, DorotheaThe purpose of this work is to introduce one of the most promising among recently developed statistical techniques – the support vector machine (SVM) – to corporate bankruptcy analysis. An SVM is implemented for analysing ...