I couldn't find good resources on how to simulate a stock price data sequence including some basic effects. The basis might be a Brownian motion model; but in real stock prices, there are additional effects like support and resistances etc.
I found the book by Paul Glassermann 'Monte Carlo Methods in financial engineering'. But it couldn't find e.g. something about resistance in it.
Edit: The work by Lo and MacKinlay made me belive that there could be some work on modelling the non-random effects apparently present in stock data: Lo, Andrew W., and A. Craig MacKinlay. "Stock market prices do not follow random walks: Evidence from a simple specification test." Review of financial studies 1.1 (1988): 41-66.