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Parameter Estimation in Credit Models Under Incomplete Information
Authors:Alexander Herbertsson  Rüdiger Frey
Institution:1. Centre For Finance, Department of Economics, School of Business, Economics and Law , University of Gothenburg , G?teborg , Sweden Alexander.Herbertsson@economics.gu.se;3. Institute for Statistics and Mathematics, Vienna University of Economics and Business , Vienna , Austria
Abstract:We consider the filtering model of Frey and Schmidt (2012 Frey , R. , Schmidt , T. ( 2012 ). Pricing and hedging of credit derivatives via the innovations approach to nonlinear filtering . Fin. Stocha. 16 ( 1 ): 105133 .Crossref], Web of Science ®] Google Scholar]) stated under the real probability measure and develop a method for estimating the parameters in this framework by using time-series data of CDS index spreads and classical maximum-likelihood algorithms. The estimation-approach incorporates the Kushner-Stratonovich SDE for the dynamics of the filtering probabilities. The convenient formula for the survival probability is a prerequisite for our estimation algorithm. We apply the developed maximum-likelihood algorithms on market data for historical CDS index spreads (iTraxx Europe Main Series) in order to estimate the parameters in the nonlinear filtering model for an exchangeable credit portfolio. Several such estimations are performed as well as accompanying statistical and numerical computations.
Keywords:CDS index  Credit risk  Filtering  Maximum-likelihood
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