Estimating the parameters of stochastic asset price models using Matlab

Question

I am simulating asset prices using different existing stochastic models, as well as my own proposed stochastic models. I would like to estimate the parameters of each model using the historical spot prices. I believe this can be done via different methods such as MLE, MCMC, etc..

However as I do not know the density function of my models (some can be very complex). I was wondering whether it is correct and/or possible to:

1. Use Matlab's ksdensity function (kernel density estimation) to obtain the empirical pdf of the asset prices up to $T$ days
2. Minimize the difference between this empirical pdf and the kernel density of simulated prices ($N$ paths and up the to the same $T$ days) to obtain the model parameters.

If this is a correct way of thinking, I would also appreciate any hints on how I would go about coding this objective function.