ModelRisk runs seamlessly in Excel with any Monte Carlo spreadsheet simulation package. This means that ModelRisk is a complementary to tools such as Crystal Ball, @RISK or Simulacion (the latter being a free MC simulation tool). ModelRisk enables you to build robust, sophisticated, and useful financial tools in Microsoft Excel in a fraction of the time necessary using the current Monte Carlo simulation tools. Crystal Ball, @RISK or Simulacion allow you to run
the model you construct in ModelRisk using Monte Carlo simulation and perform
sensitivity analyses on the results of the ModelRisk models.
- Unique approach to defining and manipulating random variables as objects allowing unprecedented flexibility in modeling insurance and finance issues;
- Time series models like Geometric Brownian Motion, Markov Chain, ARCH, GARCH, Wilkie models and Jump Diffusion (see figure below);
- Various elliptical and Archimedian copulas;
- Intuitive and highly flexible tools for fitting time series, distributions and copulas to data;
- Determination of a portfolio's efficient frontier;
- Density, cumulative probability and generation functions for all univariate distributions and moment calculations so you can quickly and accurately perform complex probability calculations, find custom MLE's. etc;
- Over 70 different distributions, both univariate and multivariate, used in the insurance and finance fields, with shifting and bounding (see figure below);
- Ruin and depletion models;
- Risk event models, allowing you to evaluate the effect of risk events;
- Powerful, unique approach to extreme value modeling allowing you, for example, to directly calculate the probability that the largest of a million claims following a certain distribution will not exceed some value X with 95% confidence;
- Splicing of distributions to, for example, model the bulk of a claim distribution with a Lognormal and splice a Pareto to extend the high-end tail;
- One-click statistical analysis of data, including bootstrapping;
- Stochastic dominance analysis;
- Direct aggregate distribution modeling with recursive and FFT methods (Panjer method screen show in Appendix);
- Direct determination of premiums via known identities and numerical integration;
- Direct determination of moments of aggregate distributions and fitting various distributions to those moments;
- All functions are optimized for both speed and accuracy;
ModelRisk is not only very user-friendly, but also teaches and helps the user employ the methods and techniques available by:
- A specialized version of ModelAssist for Insurance and Finance (an advanced 'help file') shows how to use ModelRisk with explanation of any relevant theory, linked problems and example model solutions, videos, a search engine and much more!;
- Sophisticated graphical interfaces to visualize, explain and insert model components in an intuitive manner;
- All features within ModelRisk return meaningful error messages to guide the user when there has been an input error;
- A unique translation feature means that ModelRisk models can be passed between users using different language versions of Excel.
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