Financial Simulation Modeling in Excel

CHAPTER 6

Simulating Pools of Assets

Observing relationships among asset prices and then using these relationships to forecast future prices is at the heart of simulation modeling. Generally, investors hope to do in-depth research and analysis on each investment they make and on the risks associated with the idiosyncrasies of each asset. However, as portfolios grow, such analysis is often impractical or even impossible. Certain asset-backed securities, for example, are made up of tens of thousands of loans, each one in an amount of less than $10,000.

In situations involving too many assets for individual analysis, the typical methods of analysis are to implement a simulation of either price movement or of defaults. Typically, “Monte Carlo” simulations are used for this type of analysis. Although we covered Monte Carlo–style simulations previously in this text, they will be at the center of this chapter, and so a quick background on this important method may be helpful.

Monte Carlo simulations were first developed during World War II as part of the Manhattan Project. They take their name from a famous casino located in Monaco. They were named as such not because they were developed for gambling, but because they reminded their creators of the draws in card games, and so a gaming name was chosen to convey their probabilistic nature.

To this day we use similar terminology. These simulations involve repeated random “draws” from a defined set of possible values, so-called because you ...