I would like advice on how to correctly set the parameters (loc and scale) for the student T distribution that best fits my data of daily stock returns.
I'm pulling random numbers from a student T distribution using python's scipy stats package. I use the
number of samples - 1 for the degrees of freedom.
Is it best to use the geometrical mean for the loc parameter and standard deviation or mean absolute deviation for the scale parameter?
I'm using this to run 50,000 simulations on expected portfolio returns in the form of:
return = starting investment + (1-random student T distribution) + annual investment