• Monte Carlo simulation is a computerized mathematical technique used to analyse risk.
• Monte Carlo simulation performs risk analysis by building computer models of possible results by substituting a range of values – a probability distribution – for any factor that has uncertainty. It then calculates results over and over, each time using a different set of random values from the specified probability function.
• Monte Carlo simulation furnishes the decision-maker with a range of possible outcomes and the probability they will occur for any action – it shows the extreme possibilltiies.
• Results show not only what could happen, but how likely each outcome is.
• Probability distributions are a much more realistic way of describing uncertainty in variables than deterministic or “single-point estimate” analysis.
• It is possible to model how, in reality, when some factors go up, others factors go up or down accordingly. (Correlation of input).
