Essentials of business risk analysis modeling

Discover how to use the Excel add-in model risk for business risk analysis, including downloading, installing, and exploring a free trial, with alternatives like R, Mathematica, and Analytica.

Download and install the model risk Excel add-in, which provides Monte Carlo simulation and probability calculations, then paste your activation code and verify the new model risk ribbon in Excel.

Learn Monte Carlo simulation, a central tool in risk analysis, and explore how it works and its name's history through simple exercises.

Explore Monte Carlo simulation fundamentals through series of practical examples in excel, including pi estimation, cost refurbishments, and interpreting histograms, cumulative distributions, and tornado charts with model risk.

Explore how probability distributions underpin Monte Carlo simulation and risk analysis, focusing on a handful of simple distributions used in business risk modeling and their key properties.

Learn to select and apply core probability distributions for risk analysis, covering discrete and continuous types, including uniform, triangle, Pert, relative, Bernoulli, binomial, and Poisson.

Produce and interpret the graphs that describe risk analysis results, and determine the required sample size based on the desired precision in Monte Carlo simulation.

Run two simulations on the same model to compare decision options apples to apples, using base and $2.4 million development with a 16% larger market, comparing net present value.

Explore common errors in risk analysis modeling, including avoiding multiplying probability by impact, ensuring feasible samples, accounting for correlation with copulas, and using proper aggregation methods.

Develop a defensible, trustworthy, and useful risk analysis model by applying proven tips from decades of audits, avoiding common failures, and establishing good habits through ongoing review.