Risk Solver Engine - Statistics and Risk MeasuresStatistics and Risk MeasuresRisk Solver Engine provides a wide range of statistics and risk measures, computed for each output of interest across the trials of a Monte Carlo simulation. You can use measures of central tendency, measures of variation or dispersion, and quantile measures, to assess almost any output in your model.
Measures of Central TendencyRisk Solver Engine provides several measures of central tendency:
Measures of VariationRisk Solver Engine provides several standard measures of variation:
Risk MeasuresRisk Solver Engine also provides several risk measure functions that are most often used in quantitative finance applications, but may be used in any model:
PsiSemiVar and PsiSemiDev are useful in situations where 'upward' variation -- for example, higher stock prices or increased profits -- is desirable, but 'downward' variation -- lower prices or losses -- is undesirable. Quantile MeasuresTo get a complete grasp of the range of outcomes, it's essential to look at quantile measures, such as percentiles and Value at Risk, in addition to measures of central tendency and variation. Quantile measures allow you to answer questions such as 'How much money might we lose, with 5% or 10% probability?' or 'What is the probability that we'll make at least $100,000?' based on your simulation model. Risk Solver Engine provides:
Confidence IntervalsEvery Monte Carlo simulation uses a sample of the possible values of your uncertain variables; hence any statistic resulting from the simulation involves some degree of sampling error. For the mean and standard deviation of an output value, Risk Solver Engine provides functions that help you assess this error, and estimate the range or interval in which you can be confident that the true mean or standard deviation lies, at a confidence level that you specify:
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