The recent blog positing on best practices in Excel modelling could be thought of as providing a reasonable and robust set of principles for building static Excel models. When building simulation models for risk analysis in Excel (for instance, with @RISK Monte Carlo...
Calum Turvey, W.I. Myers Professor of Agricultural Finance, uses @RISK in his Risk Simulation and Optimization course. Offered by the Charles H. Dyson School of Applied Economics and Management at Cornell University, Risk Simulation and Optimization attracts over 50...
This blog briefly posts some fairly standard “best practice principles” in Excel modeling. The following principles are generally to be applied to Excel models (in fact, in practice, many of these may need to be varied or interpreted in a slightly different way than...
Global risk management consulting company DNV specializes in helping companies in the energy, maritime, healthcare and other industries identify, assess, and manage risks of all kinds. DNV uses probabilistic Monte Carlo modeling with @RISK to illustrate factors...
Just for fun, here we talk about using Monte Carlo simulation to estimate the value of π (3.14159…). A circle of radius one will have area equal to π, and a square drawn around that circle will have area 4. When centered at the origin the circle has the equation...
