Hybrid Calibration for Defaultable Term Structures with Gaussian Random Fields

摘要：

This article proposes a mixture of historical estimation and calibration in markets with credit risk. To this,necessary pricing formulas for credit derivatives in a Gaussian random field model are derived,with include risk-free securities as a special case. The idea of the hybrid calibration is to use principal component analysis on historical data to obtain an empirical shape of the volatility surface and then calibrate this shape to option prices. The implementation suggests that this leads to more stable calibrations. Moreover,this method allows to overcome the difficulty of scarce derivatives data.

关键词： credit risk calibration Gaussian random fields

作者: Thorsten Schmidt

作者单位: Department of Mathematics,University of Leipzig,04081 Leipzig,Germany

会议类型: 国际会议

会议名称: The First International Conference on Management Innovation(ICMI 2007)(管理创新会议)

会议地点: 上海

会议语种:英文

页码: 371-376

在线出版日期: 2007-06-04（万方平台首次上网日期，不代表论文的发表时间）