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Ex Tax: £1,395.00
  • Stock: In Stock
  • Model: @Risk
  • Weight: 0.00kg
  • MPN: Palisade Europe

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Risk analysis tools that uses Monte Carlo simulation and displays the possible outcomes in Microsoft Excel spreadsheets with indications of how likely they are to occur. It is fully compatible with 64-bit Excel 2010.

@RISK performs risk analysis using Monte Carlo simulation to show you many possible outcomes in your spreadsheet modeland tells you how likely they are to occur. It mathematically and objectively computes and tracks many different possible future scenarios, then tells you the probabilities and risks associated with each different one. This means you can judge which risks to take and which ones to avoid, allowing for the best decision making under uncertainty. @RISK is available in the following editions:

  • Standard Edition: Advanced Simulation Engine, over 65 Built-in Distribution Functions, integrated Distribution Gallery, @RISK Function Swap and Thumbnail Graphs are some of the feautures included in this version.
  • Professional Edition: Designed for professional-grade problems in any industry, it is for most commercial uses. It provides a balance of advanced analysis and point-and-click ease of use.
  • Industrial Edition: Designed for your largest, most complex models, @RISK Industrial includes everything in @RISK Professional, plus the following:
    • RISKOptimiser: Combines Monte Carlo simulation with sophisticated optimisation techniques to find the best combination of factors that lead to a desired result under uncertain conditions.
    • Simulation of Time-series Forecasts: @RISK offers a set of functions for simulating time series processes, or values that change over time.
    • Full Multi-CPU support: Speed up simulations with parallel processing by using all multi-core processors and available CPUs within a single machine.

Key Features:

  • New and Improved Tornado Graphs: Tornado graphs have long been used to identify the critical variables affecting a risk analysis. Version 7.5 adds a new graph type called Contribution to Variance which shows the amount of the variance in the output attributable to each input variable. In addition, you can now overlay tornado graphs from multiple simulations to compare the effects of model changes. Lastly, Palisadeve added shading options on the graph bars to indicate whether inputs are high or low when the output increases or decreases.
  • Faster Optimisation with RISKOptimiser: RISKOptimiser, available in @RISK Industrial, is a powerful tool that allows you to optimise linear and nonlinear problems in uncertain situations. It combines optimisation with Monte Carlo simulation and is very computationally intensive. New version 7.5 now runs at least four times faster than previous versions!
  • Over 20 New @RISK Functions: Sixteen new distribution functions have been added to @RISK, along with six new statistical functions. The new functions are important for accurate, insightful modeling of uncertainty in finance, insurance, reliability and other applications.
  • Run Optimisations During Simulation Without Coding: If you need to run Excel Solver during an @RISK simulation, you can now do so without writing any VBA code, saving you time. Version 7.5 makes this easy to set up via dialog box and it works for Excel Goals Seek and Palisade's Evolver as well.
  • Graphing and Reporting Improvements: All @RISK graphs and reports now feature an updated, more streamlined interface, as well as support for Excels built-in themes and colors. Now you can apply your companys standard Excel themes to your @RISK reports! In addition, graphical displays have been improved for ultra-high resolution monitors.
  • And More: You can now control the number of CPUs @RISK uses to run simulations. Palisadeve also added easy access to @RISK statistics functions in the Model and Summary Results windows, saving you time in modeling.

@Risk - Features

Risk Analysis with @RISK Risk Analysis in @RISK is a quantitative method that seeks to determine the outcomes of a decision as a probability distribution. In general, Risk Analysis with @RISK encompasses four steps:
  • Develop a Model - First, define your problem or situation in an Excel worksheet format.
  • Identifying Uncertainty - Next, determine which inputs in your model are uncertain, and represent those using ranges of values with @RISK probability distribution functions. Identify which result or output of your model you want to analyse.
  • Analysing the Model with Simulation - Run your simulation to determine the range and probabilities of all possible outcomes for the outputs you've identified.
  • Make a Decision - Armed with complete information from your analysis, and your personal preferences, make your decision.
  • Multiple Simulations: @RISK features the RiskSimTable function, which allows multiple simulations to be run back-to-back. This lets you change only select inputs in your model from simulation to simulation, so you can compare the effect of a variable or variables on your outcome. For example, you may with to see what impact charging different prices has on your profits. You can even graph the results from multiple simulations on one chart!
  • Multiple Simulations: Correlate your inputs in the @RISK Model Window. Correlate Your Inputs for More Accurate Models. In real life, inputs are seldom independent. When interest rates are high, mortgages are low, for example. If you don't take these relationships into account when building your model, you risk dangerously inaccurate results. The @RISK Model Window provides an easy way to correlate inputs in your model using a simple matrix format. Click a button to get a blank matrix, then drag inputs onto it from the Explorer list. Enter in correlation coefficients, click Apply, and the correlations are automatically written to your spreadsheet model.
  • Statistics and Graphing Functions: @RISK 4.5 for Excel adds a set of statistics functions that return a desired statistic on simulation results anywhere in your spreadsheet. These functions include all standard statistics plus percentiles and target probabilities, and can be used just like any other Excel or @RISK function. You can watch the statistics update real-time as the simulation runs too.

    The statistics described by these functions are the following:

  • Kurtosis Min Range Target Value
  • Max Mode Skewness Variance
  • Mean Percentile Standard Deviation @RISK 4.5 also includes a powerful graph placement function that places any graph of simulation results directly in your spreadsheet. Place this new RiskResultsGraph function anywhere in your spreadsheet and automatically, after a simulation, the desired graph will be appear directly in Excel. As with all @RISK graphs, you can choose to generate a graph in metafile or standard Excel chart format. Enhanced VBA Support for Custom Applications @RISK 4.5 lets you write your own custom applications in Excel that can perform virtually any @RISK function. Harness the power of @RISK's Monte Carlo simulation engine for your company's specific needs. Utilise @RISK's extensive reporting options, Sensitivity analysis, Scenario analysis, distribution fitting, and more, all in your own custom Excel program! Example files are included demonstrating how to use these commands. Plus, you can run macros before, during, or after a simulation run. Click here for more information about @RISK VBA macro functions. @RISK Professional @RISK 4.5 is available in three editions to meet your risk analysis needs: Standard, Professional, and Industrial. @RISK Professional adds a host of analytical power features to your arsenal. Integrated BestFit Fit distributions to your data. See above. @RISK Goal Seek @RISK Goal Seek lets you find the value of an input that leads to a desired simulation result. You set the target value or the goal - say, a simulated mean of $1000 - and then tell Goal Seek which input to adjust in order to achieve your goal. Goal Seek will then use multiple simulations - not deterministic spreadsheet recalculations like Excel's Goal Seek - to find the input value that achieves the goal. This lets you take all possible outcomes into account when determining input values that achieve your goals! Stress Analysis @RISK lets you control the range that is sampled within an input distribution; that is, you can stress the distributions. By specifying extreme ranges of a give input, you can see how different situations would affect your bottom line. Instantly test various scenarios without changing your model! Results include Box-Whisker plots, comparison graphs, cumulative charts and histograms. See the effects of multiple inputs with Advanced Sensitivity Analysis. Advanced Sensitivity Analysis @RISK 4.5 lets you see how changes in input values affect your simulated results. With Advanced Sensitivity Analysis, inputs can be any value or distribution in your model. Using a wide variety of options, you can control how these inputs are varied. @RISK then runs any number of simulations (hundreds or thousands if necessary!) - one at each possible input value - and tracks how your output statistics change. Results graphs include Box-Whisker plots, Spider graphs, cumulative curves, line graphs and Tornado charts to show you the critical factors in your model. @RISK Industrial @RISK 4.5 Industrial is well-suited to the power risk analyst. @RISK Industrial builds upon @RISK Professional by adding: RISKOptimizer to Optimise Your Simulation Results @RISK 4.5 Industrial for Excel comes with RISKOptimizer, the simulation optimisation add-in for Excel. RISKOptimizer is an innovative tool which allows you to optimise the results of an @RISK simulation, finding the best combination of inputs to maximise or minimise your bottom line. @RISK alone uses Monte Carlo simulation to account for uncertainty in models and view the probabilities of various outcomes occurring. But Monte Carlo simulation cannot deal with input or decision variables whose values you can control. It views all possible outcomes at a single state of those controllable variables. RISKOptimizer combines simulation with optimisation to solve the most complex problems. RISKOptimizer changes all that. With RISKOptimizer, many different combinations of controllable inputs (called adjustable cells) are tried in order to maximise or minimise your output. This process of trying different inputs is called optimisation. But unlike other optimisers, RISKOptimizer performs Monte Carlo simulation while it is optimising, allowing uncertainty to be taken into account. For each different combination of inputs - or trial solution - RISKOptimizer runs a Monte Carlo simulation. In this way, RISKOptimizer looks at all possible outcomes in many different states. This is an extremely powerful technique that can solve problems not previously solvable by traditional linear or nonlinear optimisation packages. For example, say you run an @RISK simulation on a potential product launch to see the range of possible outcomes for profit. But your model is based on using specific vendors to supply the raw materials for your product. There may be other vendors who can offer cheaper materials, quicker turnaround, or more attractive shipping. With @RISK alone, you could run multiple simulations for different vendors, but did you try every possible combination of inputs? RISKOptimizer will try many different combinations until it maximises the simulation results for profit. RISKOptimizer uses the same genetic-algorithm based optimisation engine as Evolver. With genetic algorithms, favorable trial solutions are combined to produce more and more effective "offspring" solutions. "Mutations," or randomly generated new trial solutions, occur to make sure that all possible solutions are explored. In this way, RISKOptimizer achieves true "global," or overall, solutions and avoids settling on a less effective "local" solution as many traditional hill-climbing optimisers do. @RISKAccelerator for Your Largest Simulations Speed up large simulations by using all CPUs in a multi-CPU machine. If your PC has two processors, your simulations will run nearly twice as fast! With integrated @RISKAccelerator, @RISK Industrial lets you take full advantage of the additional processing speed available with increasingly popular multi-processor machines. Using innovative parallel-processing technology, @RISKAccelerator "splits up" a simulation for available CPUs to work on simultaneously. @RISKAccelerator is invaluable for users with large, complex models or users who run simulations frequently. For example, in the securities industry, the risk and return of portfolios comprised of thousands of stocks - each with a different possible future price path - are often calculated using Monte Carlo simulation. This is a lengthy simulation that is constantly re-run as market conditions, current prices, and portfolio components change. Also available separately, @RISKAccelerator can be configured to utilise available CPUs over a network.
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