Background on the Monte Carlo Method
Although not strictly a ratio the Monte Carlo Method is worthy of discussion in the financial ratio section. The Monte Carlo method is used by investors to value and analyze various investments. Originally the Monte Carlo methods were developed by scientists working on nuclear science projects in the 1940s. The name has been inspired by the Monte Carlo Casino of Monaco. The casino was similar to the Monte Carlo method since it was full of randomness and was of a repetitive nature, similar to gambling. The methods were developed earlier in the Twentieth Century many years before the Monte Carlo name was coined. The application to financial situations appeared to have developed in the mid 1960s; this was illustrated in the Harvard Business Review by Hertz’s article “Risk Analysis in Capital Investment”. After this initial application the finance applications started to grow. For example the paper entitled “Options: A Monte Carlo Approach”. The application of the Monte Carlo method appears to have been particularly successful in the pricing of options and derivatives.
What is the Monte Carlo Method?
The Monte Carlo method consists of computational algorithms which depend on repeated random sampling to calculate the results.
What Can the Monte Carlo Method Be Used For?
The Monte Carlo simulation method is useful for helping to model and analyze data which has a high level of uncertainty and a significant number of inputs. This has usefully been applied to nuclear programmes, physics, complex designs, mathematics, finance and business investor situations.
How Can the Monte Carlo Method be Used by the Investor?
Investors may decide to use the Monte Carlo method to establish a probabilistic financial model to analyze Net Present Value (NPV). This can be useful for investment decisions, such as valuing a potential acquisition. The investor may also use the Monte Carlo as a method of assessing pension portfolio valuations. This is a complex method however and requires professional advice.
How is the Monte Carlo Different from “What If” Analysis?
The “What if” approach is used by providing the simulation model with a specific variable data input. This input is normally a centre point estimate, together with a best and worst case scenario. The Monte Carlo method however considers random sampling of probability distribution functions as model inputs to produce often thousands of different possible results, rather than a small number of discrete scenarios. The Monte Carlo method results give an interpretation of the probability of the results occurring, which therefore gives extra insight to the analyst.
When is the Monte Carlo Method Not Useful to the Investor?
The Monte Carlo method is very complex and needs training to be used properly. The Monte Carlo method may not be appropriate where there are not the requisite numbers of uncertainties and data points. It is best to take independent professional advice before using this method.