We can immediately say that this method is used precisely because it is simple. But no matter how simple it is, the Monte Carlo method remains a powerful tool, and also boasts some interesting properties that make it very attractive for solving various problems. Monte Carlo method refers to number of statistical methods, which in turn are used to calculate the expected values of functions that cannot be integrated analytically because they do not have a closed form.
It allows us, using one and the same principle, to solve various kinds of problems. Monte Carlo simulations can be used in corporate finance, option pricing, and especially in portfolio management and financial planning. On the other hand, the method is limited in that it cannot account for bear markets, recessions, or other type of financial risk that may affect potential results.
The Monte Carlo method uses different probability distributions to calculate uncertainty factors. The probability distributions correspond to various assumptions. Thus, the different nature of the data has different probabilities for different amounts.
Consider the probability distributions used in financial modeling in the gallery below.
Compared to the standard scenario Monte Carlo method, it shows us the exact combination of values for each variable that contributed to a particular outcome. For example, scripting is often difficult to prepare a complete set of values for all inputs.
The method can be easily represented graphically if required.
More accurate sensitivity analysis.
What is important – the results have probabilities.
Despite the many advantages of the method, it has not become recognizable, since this is not built into standard spreadsheets and the employee has to use certain procedures to achieve the result.
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