Financial model calibration using consistency hints

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Financial model calibration using consistency hints

We introduce a technique for forcing the calibration of a financial model to produce valid parameters. The technique is based on learning from hints. It converts simple curve fitting into genuine calibration, where broad conclusions can be inferred from parameter values. The technique augments the error function of curve fitting with consistency hint error functions based on the Kullback-Leible...

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ژورنال

عنوان ژورنال: IEEE Transactions on Neural Networks

سال: 2001

ISSN: 1045-9227

DOI: 10.1109/72.935092