# Monte Carlo Simulation Essay

‘The problems of Monte Carlo Simulation’ by David Nawrocki

This article describes the problems associated with using the Monte Carlo Simulation Model as a tool for determining future investment outcomes for investors. The tool is widely used by Financial Advisors as a means of showing investors future returns on investments. The article discusses why the use of Monte Carlo Simulation in financial planning is difficult and can lead to incorrect decisions which can have a detrimental impact on investors’ expectations of expected returns. The article tells us that Monte Carlo Simulation uses assumptions based on normal distributions and correlation coefficients of zero, neither of which are real in the financial

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The article then goes on to discuss nonlinear relationships. Non linear relationships according to the author are more likely with stock market data. The author shows by use of graphs the difference between linear and nonlinear serial correlation.

The article highlights work by White (1994) and Perez-Quiros and Timmerman (2000) explaining that means and deviations are different throughout business cycles, making non stationary distributions difficult to model for Monte Carlo Simulation.

The article introduces an alternative model to Monte Carlo Simulation: Exploratory Simulation using historical data. The data is the model and it is not necessary to model all this data as with Monte Carlo Simulation.

The article compares Exploratory Simulation and Monte Carlo Simulation by using results from a demonstration study using an investment fund equally invested in timber and stocks. The Monte Carlo