Profitability

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Monte Carlo Simulation Project

Introduction

A great tool for investigating uncertainty in a complex process is the Monte Carlo simulation. If you’d like, there is plenty of information online that describes what this simulation does and what it is useful for. But in brief, a Monte Carlo simulation aims to simulate the possible pathway of a future endeavor, experiment, or process, given multiple inputs that each have uncertainty. Monte Carlo simulations are oftentimes used by financial planners to try to predict that might happen in the future. Inputs to financial planning processes include probabilities of how the stock market might do, projections for various costs and amount of sales, and many other financial variables. In the sciences, there may be several or many inputs into a future process, and the goal is to understand the likelihood of a scenario going one way or another.

In this project, you will first learn about a Monte Carlo simulation and how to implement it in a VBA user form using an example investigating a cookies recipe, where each of the ingredients has an uncertainty associated with it . You will explore five different typical distributions used in Monte Carlo simulations and implement these into the VBA user form. Finally, you will adapt a profitability analysis example into the main project deliverable, which is a user form that allows the user to simulate a profitability analysis based on net present value (NPV) of a proposed capital project.