Jan Henrik Wosnitza
University of Applied Sciences Stralsund
Jan Henrik Wosnitza works as a quantitative on-site inspector in the field of banking supervision for Deutsche Bundesbank. In addition, he teaches mathematical finance, credit portfo-lio risk modelling, counterparty credit risk modelling and credit risk modelling based on machine learning techniques at the University of Applied Sciences of the Deutsche Bundes-bank and at the Technische Hochschule Mittelhessen. He holds a diploma in physics and a doctorate degree in natural sciences from the University of Muenster. His research interests include the modelling of financial risks and, more specifically, credit default prediction, econophysics and household finance.
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Articles by Jan Henrik Wosnitza
Variance estimation for the quantification of the margin of conservatism category C
This paper discusses a new estimator for probability of default and compare its performance against two alternative approaches, demonstrating the novel method to have a lower bias and variance.
Calibration alternatives to logistic regression and their potential for transferring the statistical dispersion of discriminatory power into uncertainties in probabilities of default
This paper compares four calibration approaches to linear logistic regression in credit risk estimation and proposes two new single-parameter families of differentiable functions as candidates for this regression.