# A Look at the Monte Carlo Options Method

The Monte Carlo options method is a means to analyze highly volatile or complex investments by running models of various potential outcomes. The method uses inputs of different factors that can affect the profit of a highly unpredictable investment. The investment is so unpredictable that no other means of valuation could properly measure its likely return. With the Monte Carlo method, the option's potential return is considered to be the average of all the various outcomes.

History of the Monte Carlo Method

The method was first introduced in 1964 when economists noted there were some investments with which traditional risk analysis could not be applied. These investments are subject to such a wide array of factors, no single factor or group of factors could be used to generate a consistent measure of risk and reward. The best way to measure this, then, was to simulate different scenarios that could potentially take place. This is called the "Monte Carlo" method because it uses probability models used in gambling to estimate risk and return. The investments are so highly variable they are very much like gambling, so the method seems appropriate for certain options and derivatives.

Practical Application of the Monte Carlo Method

This method is often considered a means of last resort. It applies only in scenarios where other, more consistent measurements of risk and return are not possible. The Monte Carlo uses an average to describe the result of a large series of calculations in which the average result will not likely be attained. For example, the Monte Carlo method could be applied to rolling a set of dice. The various outcomes would be averaged, and the average outcome would be to roll a "10." While this is the average of all the possible outcomes of rolling two dice, there is no higher likelihood a 10 will be rolled than various other combinations.

When to Use the Monte Carlo Method

Because the method is used only in cases of last resort, it is applied to those outliers in the market that cannot be estimated with other models. There are some scenarios where the Monte Carlo method should be applied consistently. For example, it is often used to calculate risk and reward for Asian options. Asian options are actually a wise place to use the Monte Carlo method because they use the average underlying price over a set period of time to determine payoff. Therefore, averages used in the Monte Carlo method work well to measure their probable return.

When to Avoid the Monte Carlo Method

If your investment could be appropriately analyzed using another pricing and rewards method, then the Monte Carlo method should be avoided. Most options contracts can be analyzed with figures such as the volatility skew, and the Monte Carlo method would be less likely to estimate an actual return than this scale. In addition, the Monte Carlo method takes a long time to generate an answer. Since so many simulations must be run, it is less likely to quickly result in a decision than another method of analysis.