There are three key parts to a Monte Carlo simulation. What is the probability that the project will run more than a year late?
What is the likelihood that you will lose money? Once you have that variability in your model, you can start to understand the risk in your model. Instead of saying this stock will return X% every year, you can say things like this stock will return between X% and Y% and then figure out what that means to your portfolio. Monte Carlo simulation is a way to build this variability into your models. You pick some values for your expected stock returns, for example, and project them into the future.īut the real world doesn't work that way. When you build a model of something in the real world - a stock portfolio, a project plan, a clinical trial - you have to build in assumptions about the future. Try our new browser-based risk platform, RiskAMP webĬonditional risk model from our sample spreadsheets
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