Many economists work on problems where they cannot be sure how different factors affect each other. In the context of physics, the Ising model is used to study the interactions between bodies that make up complex systems. A number of internal and external factors influence the way these bodies interact with each other to affect the whole system. There are several ways to solve Ising models, but one of the most pragmatic is the Monte Carlo method, which calculates the probability of certain factors occurring over and over again at varying probabilities until the system reaches an optimal level.  Adam Warner and I would like study the ways these techniques aid problems done by economists. First, we will use MatLab to model a simple Ising system in the context of a physics problem relating either to magnetism or phase transition. From there, we will each look at different ways that Monte Carlo methods and Ising Models apply to financial models. This analysis will include a survey of utility-based decision making, market booms and crashes, and the volatility of stock pricing. We hope to compare the results we obtain through our MatLab programs to established studies done by financial institutions.