I'm building a Monte Carlo option pricing model in Python/SciPy. I want to test the results produced by the Python code by building the model independently in Excel and then comparing the results. Off course the values won't match exactly, but what is close enough?
My idea is to calculate the standard error and then calculate the range on a 95% confidence level where the true mean lies for both implementation. If these two ranges overlap then it is close enough.
I'll also do enough simulations so that the standard error is less than 2% of the estimated mean.
Alternatively I can generate the random numbers in Python and feed that into Excel for a type of quasi Monte Carlo. Or I might be able to to give it the same seed (but I'm not sure if this will work).
Is my approach described above sound or what other options are there?