In the LSM method, I am currently (as they do in the paper) using weighted Laguerre polynomials as basis functions, about 3-5 of them.
If I wish to increase the accuracy of my model, what should I do?
More paths, steps, or basis functions? What will generally have a bigger impact? I could of course increase all three, but then the code may be slowed down considerably. What will give me most bangs for my buck?
If it's the basis functions, should I use more of the "same" basis functions (i.e. more laguerre polynomials) or should I mix the current basis functions with another set of basis functions (e.g. standard polynomials, $X, X^2, X^3$).