Filtering techniques in the modeling, pricing and hedging of interest rate and credit risk

• Antragsteller: Professor Dr. Rüdiger Frey; Professor Dr. Thorsten Schmidt
• Fachliche Zuordnung: Mathematik
• Förderung: Förderung von 2011 bis 2015
• Projektkennung: Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 196379142

• Erstellungsjahr: 2015

Zusammenfassung der Projektergebnisse

The project was concerned with the analysis of dynamic credit risk models in a setup where key state variables of the model are unobservable, using stochastic filtering techniques. Within this context we studied structural credit risk models with incomplete information, the impact of contagion on counterparty risk and collateralization and certain numerical issues. We obtained a couple of interesting results that open promising avenues for future research. In particular, we plan to work on the statistical analysis of credit risk models under incomplete information, on pricing and hedging of hybrid securities in structural models and on the extension of the methods to sovereign debt risk.

Projektbezogene Publikationen (Auswahl)

• (2013) “On Galerkin Approximations for the Zakai Equation with Diffusive and Point Process Observations”, SIAM Journal of Numerical Analysis 51, pp 2036–2062
  Frey, R. and Schmid, T. and Xu, L.
  (Siehe online unter https://doi.org/10.1137/110837395)
• (2014) “Contagion effects and collateralized credit value adjustments for credit default swaps”, International Journal of Theoretical and Applied Finance, 17 (7): 1450044/1–29
  Frey, R. and Rösler, L.
  (Siehe online unter https://doi.org/10.1142/S0219024914500447)
• “Corporate security prices in structural credit risk models with incomplete information”, Mathematical Finance
  Frey, R., Rösler, L. and Lu, D.
  (Siehe online unter https://doi.org/10.1111/mafi.12176)