Optimization Procedures: Discrete Binary Optimization

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  • September 17, 2014
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Many algorithms exist to run optimization and many different procedures exist when optimization is coupled with Monte Carlo simulation. In Risk Simulator, there are three distinct optimization procedures and optimization … Continue Reading →

Optimization Procedures: Continuous Optimization

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  • September 17, 2014
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Many algorithms exist to run optimization and many different procedures exist when optimization is coupled with Monte Carlo simulation. In Risk Simulator, there are three distinct optimization procedures and optimization … Continue Reading →

Decision Tree and Related Analytics

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  • September 10, 2014
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Decision Tree Risk Simulator | Decision Tree runs the Decision Tree module (Figure 1), which is used to create and value decision tree models. Additional advanced methodologies and analytics are … Continue Reading →

Genetic Algorithm, Goal Seek, and Single Variable Optimizer

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  • September 10, 2014
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Genetic Algorithm Optimization Genetic Algorithms belong to the larger class of evolutionary algorithms that generate solutions to optimization and search problems using techniques inspired by natural evolution, such as inheritance, … Continue Reading →

Optimization Procedures: Efficient Frontier

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  • September 10, 2014
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Efficient Frontier and Advanced Optimization Settings Figure 1 shows the efficient frontier constraints for optimization. You can get to this interface by clicking on the Efficient Frontier button after you … Continue Reading →

Box Plot and Box-and-Whisker Plot

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  • September 3, 2014
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The Basics of Box-Whiskers Box plots or box-and-whisker plots graphically depict numerical data using their descriptive statistics: the smallest observation (Minimum, or some variation of interquartile range), First Quartile or … Continue Reading →

Pareto Chart versus Sensitivity Analysis

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  • September 3, 2014
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The Basics of Pareto Charts A Pareto chart contains both a bar chart and a line graph. Individual values are represented in descending order by the bars, and the cumulative … Continue Reading →

The Pitfalls of Forecasting, Part 3

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  • September 3, 2014
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Heteroskedasticity Another common problem encountered in time-series forecasting is heteroskedasticity; that is, the variance of the errors increases over time. Figure 1 illustrates this case, where the width of the … Continue Reading →

The Pitfalls of Forecasting, Part 2

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  • August 27, 2014
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As noted in “The Pitfalls of Forecasting, Part 1,” forecasting is a balance between art and science. Using Risk Simulator can take care of the science, but it is almost … Continue Reading →

The Pitfalls of Forecasting, Part 1

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  • August 27, 2014
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Regression Assumptions The following six assumptions are the requirements for a regression analysis to work: The relationship between the dependent and independent variables is linear. The expected value of the … Continue Reading →