Corporate and Project Finance Modeling

Chapter 20Taking the Mystery out of Applying Time Series Analysis and Monte Carlo Simulation in Financial Models

Some who have studied hard in university or who work with stochastic models and computer programs such as At Risk or Crystal Ball may develop a little arrogance about the superiority of stochastic models. For these people, deterministic models are looked down upon as being intellectually inferior. One of the ideas of this and the next couple of chapters is to show how you can make elegant analysis with stochastic models so you don't have to feel inferior. You will be able to present statistics such as probability of loss, earnings at risk, and many pictures of the distribution of financial ratios that would not be possible with deterministic models. But even if graphs are beautiful and the equations are complicated, the attitude that creating a time series equation and running a simulation somehow produce better risk analysis is naive and dangerous. Attempting to remove judgment from predicting how economic variables will move is simply impossible in modeling most businesses. Analysis of underlying economic and business factors that drive key assumptions in a model cannot be avoided.

Before discussing some of the nuances of time series models, a step-by-step example of how you can easily create risk measures with Monte Carlo simulation is presented in this chapter. The idea of this is to remove any anxiety you may have about applying Monte Carlo simulation and time ...