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"Regularization effect on model calibration" by Mesias Alfeus, Xin Jiang He et al.

As is well known, the centerpiece of model calibration is regularization, which plays an important role in transforming an ill-posed calibration problem into a stable and well-formulated one. This realm of research has not been explored empirically in much detail in the literature. The goal of this paper is to understand and give an answer to a question concerning pricing accuracy using the parameters resulting from a correctly posed calibration problem in comparison with those inferred from a relaxed calibration. Our empirical findings indicate that regularized calibration is only to be recommended when considering out-of-sample pricing for a long time horizon. ....

Global Optimization , Model Calibration , Option Pricing Model , Ut Of Sample Forecast ,