New answers tagged quantlib
Neither the additionalResults nor the result method are exported to Python via SWIG. This is unlikely to change in the future: result is a template method, and it can't be exported to Python as such, whereas additionalResults would require a sensible way to export boost::any to Python and to convert it to a given data type. If you can recompile the QuantLib ...
I would tend to do the following: If, under your working modelling assumptions, there exist closed form formulas, then compare your results to them. "The Complete Guide to Option Pricing Formulas" in @Student T is indeed a nice reference for that. Beware of true formulas vs. approximations though. Now if it's not the case: Compare different pricers' ...
1: Follow the calculations in The Complete Guide to Option Pricing Formulas. The book has many formulas, sample values and outputs. Highly recommended for validating your results. Apparently, this is one of most popular books used by real-world quants (simple and fast). 2: You can still use QuantLib to price with year fractions. I have an example: ...
two things I would try...and this is really off the top of my head... is 1). to use put-call parity to check that your work makes financial sense. Call = Spot + Put - (strike price)/(1+risk_free_rate)^Time 2). see if you can recreate anything close to present/past market (Yahoo finance?) data prices, i.e. testing your model against reality. good luck
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