This spreadsheet illustrates general uses of the RiskAMP Add-in in modeling investment returns and project planning.
This spreadsheet demonstrates a simple retirement portfolio, with an analysis of the portfolio risk based on a fixed annual withdrawal.
This spreadsheet models a retirement plan prior to retirement, with a period of fixed contribution to the portfolio followed by a retirement period with a constant annual withdrawal amount.
This example demonstrates the use of bivariate correlated normal values using the CorrelatedNormalValue function.
These examples demonstrate the use of multivariate correlated normal values. The examples differ in complexity, but each uses a correlation table to generate a multivariate distribution.
This spreadsheet demonstrates the practical application of the multivariate normal function to create a 10-year portfolio model containing a weighted mix of correlated asset classes.
This is an example of modeling interest rates. The spreadsheet uses the Cox-Ingersoll-Ross model to sample interest rates over multiple discrete periods. See Cox-Ingersoll-Ross for more information.
This spreadsheet illustrates estimating value at risk (VaR) with the RiskAMP add-in. Based on the gain or loss from a spreadsheet model, VaR can be estimated easily with the SimulationPercentile function.
This is an example of using VBA to run Goalseek within a Monte Carlo simulation. Please select the version that matches your version of Excel. Also note the spreadsheet contains macros, which will generate a warning when you open the spreadsheet.
This article walks through the process of adding Monte Carlo simulation analysis to an Excel spreadsheet with the RiskAMP Add-in.
This article walks through using Monte Carlo simulation in project planning, with a worked example.
This article describes the beta-PERT distribution, used to model expert data (such as estimates from a project manager) in probability simulations.
This article discusses running simulations from VBA, the VBA function library, and how to execute VBA code at each trial of a simulation.
This article describes a technique and provides a tool for solving linear optimization problems where the dependent value is the result of a simulation.
This whitepaper is an overview of Monte Carlo simulations, and discusses the situations that can take advantage of risk management.
The RiskAMP help manual is installed with the RiskAMP Add-in and is accessible from Excel to provide online help.
The user guide is an overview of the functions and concepts used in the RiskAMP Add-in.
The reference guide includes detailed information about the probability distributions provided with the RiskAMP Add-in.