Advantages and Disadvantages of Monte Carlo Simulation

1. Advantages and Disadvantages of Monte Carlo Simulation Monte Carlo Simulation is used to solve statistical problems by random sampling of inputs. Through simulation, problems can be represented virtually. It is an influential tool allowing us to obtain an array of outcomes for any statistical problem with various inputs sampled repeatedly. It is a widely used tool in corporate finance, options pricing, personal finance planning and portfolio management. Advantages 1) It can model various types of probability distributions 2) It involves intuition and is comparably an easy method to implement time to results reasonably short 3) It is widely used and accepted 4) It is very simple and straightforward to use 5) With the use of a computer, it provides statistical sampling for a numerical experiment 6) It helps overcome local extreme and reach global optimum 7) This method is useful for both types of problems involving probability or without probability Disadvantages 1) It is a time-consuming method, as it requires generating a large number of samples to reach desired results 2) To get the results no single sample can be generated and used, one needs to generate many samples and get the average of it 3) The results provided are not specific and exact however, they are only an approximation of the true value 4) There are chances of large variance that can be produced by the simulation

2. 5) Data and parameters have no interactive link between them 6) To build and conduct a simulation model can be expensive 7) The results are sometimes difficult to interpret