Illustration of Chapter 9 of the book.
We cover genetic algorithms as well as Newton based optimizers.
Especially, we provide a SQP method which is a local optimizer that is globally convergent. we can specify a wide range of boundary conditions.
All this is applied to calibration of financial pricing models
I'm currently working with your SQP solver 'modSQP.m'. It is working very well for equality constrtaints. Is there an easy way to extend it to handle inequality constraints? Or do you provide this extended version?
About chapter 9 in the book:
To replicate Heston calibration example (pag501), deopt.m in DeMat folder must be replaced by deopt.m in DeMat folder located at "Pricing and Calibration Framework (Object Oriented)".
"Differential Evolution" subfolder is missing in the "Heston Caliration SQP, DE, SA" folder.
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