Subordinated stochastic processes, also called time deformed stochastic processes, have been proposed in a variety of contexts to describe asset price behavior. They are used when the movement of prices is tied to the number of market transactions, trading volume or the more illusive concept of information arrival. The aim of the paper is to present a comprehensive treatment of the stochastic process theory as well as the statistical inference of subordinated processes. Numerous applications in finance are provided to illustrate the use of the processes to model market behavior and asset returns.