MONTE CARLO SIMULATION
Rolling the dice on returns.
When someone walks into a casino in Monte Carlo and rolls a pair of dice at the craps table, he or she has a 1 in 36 chance (62=36) of the dice lying face up in any particular combination. He or she knows this because each of the six sides of each die – if the casino is a fair house – has an equal chance of turning face up.
Financial markets and the economy have far more variables than a six sided die. Instead of only six potential outcomes that have an equal chance of happening, investing has a myriad of possibilities and outcomes. Furthermore, each possibility has a wide range of chances of occurring.
To help investors get a better handle on this wide range of possible outcomes the market can give them, statisticians look to the gambling houses of Monte Carlo. They modify their theoretical dice to make them best resemble the real world – full of different outcomes with different possibilities. They add more sides because there are more than just 6 different events that could influence a portfolio’s return. They change the size of each side, because in the real world the probability of each event happening is different. If the statistician believes that a certain market or economic event is more likely to happen, then that side of the die will be bigger. If there’s a small chance that some event might happen, then that side is small. These statisticians then give their theoretical dice thousands of virtual tosses via computer.
After all the “virtual” tosses of their theoretical dice, measurements are made. How many times did each event happen? The total of all these tosses and the potential events that might occur can give investors useful information about potential results for their portfolio.
Monte Carlo simulations are commonly used to estimate potential answers to questions like “