STOCHASTIC MODELLING AND PROGNOSIS OF AN UNDERLYING ASSET PRICING
The aim of this paper is to obtain a stochastic model for an underlying asset pricing. Several stochastic models using time series are presented, such as stationary stochastic processes AR and MA or ARMA, and ARCH processes with conditional volatility as a stochastic process. Numerical data were used in order to compare the models.