An asset-pricing model using historical prices. Volatility of the asset is modeled as the random variable that changes over time and each iteration. For modelling the future price behavior, Monte Carlo simulations were performed.
The method tries to cover all future outcomes based on volatility and with sufficient number of simulations and rows of clean data, a gaussian cumulative distribution curve can be derived for the most likely price range estimate. Note, the following model is based on a lot of assumptions, especially the assumption that the modelled market is efficient.