Set Optimization and Applications in Finance - The State of the Art.
(co-edited with A. Hamel, F. Heyde, Löhne, C. Schrage).
Springer. Forthcoming in 2014.
Published and submitted papers
Z. Feinstein, B. Rudloff:
Multi-portfolio time consistency for set-valued convex and coherent risk measures.[Preprint] at arXiv.
Pending minor revisions at Finance and Stochastics.
Löhne, B. Rudloff:
An algorithm for calculating the set of superhedging portfolios in markets with transaction costs.[Preprint] at arXiv.
Pending minor revisions at International Journal of Theoretical and Applied Finance.
A MatLab implementation of Benson's algorithm (by Löhne) used to solve the linear vector optimization problems arising in the above paper can be downloaded here
B. Rudloff, A. Street, D. Valladao (2013):
Time consistency and risk averse dynamic decision models: Definition, interpretation and practical consequences.[Preprint] at optimization online. European Journal of Operation Research. Forthcoming.
Löhne, B. Rudloff, F. Ulus (2013):
Primal and dual approximation algorithms for convex vector optimization problems.[Preprint] at arXiv. Journal of Global Optimization. Forthcoming.
Z. Feinstein, B. Rudloff (2013):
A comparison of techniques for dynamic risk measures with transaction costs.[Preprint] at arXiv. Set Optimization and Applications in Finance, Springer PROMS series, Forthcoming.
B. Rudloff (2005):
A Generalized Neyman-Pearson Lemma for Hedge Problems in Incomplete Markets.
Proceedings of the Workshop Stochastische Analysis, 241 - 250.
B. Rudloff (2005): Hedging with Convex Risk Measures.
In: N. Kolev, P. Morettin (eds.): Proceedings of the
Second Brazilian Conference on Statistical Modelling in
Insurance and Finance, ISBN 85-88697-07-6.
Valuation of Default Correlations and Application to
Pricing synthetic CDO's.
Master Thesis (Diplomarbeit), Martin-Luther-University Halle-Wittenberg, 2002.
[in german: Ein Modell zur Berechnung von Ausfallkorrelationen
und dessen Anwendung auf die Bewertung synthetischer CDOs
Prof. W. Grecksch.