Make the Casino Work for You

rouletteNothing is more hair raising than exposure to risk without a sense of the level of that exposure.  This is especially true in capital investment decisions.

Monte Carlo simulations perform risk analysis by building models of possible results by substituting a range of values—a probability distribution—for any factor that has inherent uncertainty and significant impact on the final result.

By using probability distributions, variables can have different probabilities of different outcomes occurring.  Probability distributions are a much more realistic way of describing uncertainty in variables of a risk analysis and improve the quality of sensitivity analysis.

During a Monte Carlo simulation, values are sampled at random from input probability distributions.  This is done hundreds or thousands of times, and results in a probability distribution of possible outcomes.  It provides a much more comprehensive view of what may happen.

Advantages over deterministic, or “single-point estimate” analysis include:

  • Probabilistic Results. Showing how likely each outcome is.
  • Clearer Graphical Results. Visual presentation of probabilities.
  • Improved Sensitivity Analysis. Sharper sensitivity analysis to show what counts.
  • Scenario Analysis: Model repeated variations in combinations of factors to show which scenarios need further investigation.
  • Correlation of Inputs. Represent how, in reality, when some factors goes up, others go up or down accordingly.

Done poorly or with low quality input data, the results can be potentially misleading – producing a level of certainty on the basis of some very uncertain assumptions.

Lytton Advisory holds an @Risk software licence which enable us to provide this type of probabilistic analysis to clients, helping them make better informed decisions. Examples of how we have applied this for clients include:

  • Estimating financial costs of schedule delay on a major metropolitan public transport project.
  • Assessing probability of breaching a cost contingency levels on a +$500 million infrastructure program.
  • Building probabilistic NPV profiles in cost benefit analyses given uncertainty about key economic inputs.

Contact us today to find out how we might be able to help you.

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