- MONTE CARLO SIMULATION SOFTWARE FREE DOWNLOAD TRIAL
- MONTE CARLO SIMULATION SOFTWARE FREE DOWNLOAD DOWNLOAD
Sensitivity analysis using built-in regression functions Or in 75% of the cases, the portfolio outperformed the market. Then we can look at the results and say in 25% of the cases, the portfolio lost money. For example, we might run a stock portfolio through the simulation process. This is the "simulation" part - we are simulating the real world where values change randomly.įinally, the third part: we analyze the results of the model by looking at the hundreds or thousands of results, and deriving statistics from those results. Once that's done, we do the second step: we recalculate the model hundreds or thousands of times, each time changing the random values. We are adding random variability to the model. First, as described above, we replace fixed values - things like expected stock prices and project costs - with random variables. 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.
MONTE CARLO SIMULATION SOFTWARE FREE DOWNLOAD TRIAL
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.
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MONTE CARLO SIMULATION SOFTWARE FREE DOWNLOAD DOWNLOAD
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