I was working on the pricing of complex bermudean swaption when I noticed that the exercise is often (very) subobptimal. It seems that the clients are more sensitive to past growth or drop in rates than to their value at the moment.
I am looking for a way to modelise the suboptimal behaviour and I tought about Machine learning. But I can't find any reference on suboptimal options exercice.
Do you have any broader exemple of Machine learning applied to the replication of human non optimal behaviour ?
edit: Well, I have a little background in ML (Finished Andrew Ng course on Coursera and currently going trough ESLII at a great pace). I know there is a lot of applications (see here for tons of exemple). I have played a bit with some basic algorithm and my data. I have some interesting results but also things to investigate. My question was more about quantitative finance.