Start ups may offer options as part of compensation. These let employees purchase company stock. However, sometimes those shares cannot be sold right away. This means employees may invest their own money for either a loss or a profit realized after some delay.
What might the outcomes for options look like? Maybe data science can help. This tool explores Markov Chains and Monte Carlo methods, looking at distributions of outcomes given beliefs about what might happen to a start up.
Woah buddy. This is a US-focused free and open source community project. That said, we are talking money and can't guarantee accuracy or results. Please agree to the following:
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An example simulation has been loaded to help you get started.
You can design your simulation either through this UI-based wizard (recommended for most users) or through a domain specific language in the code editor.
In addition to the UI editor, you can also program the simulation through a small domain specific language with which you can define more complex simulations.
Whoops! It looks like there's either a code error or you are using a lanugage feature not supported in the UI editor. Please use the code editor instead.
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What's the takeaway?
Post-tax simulation outcomes summarized at a high level.
| Statistic | Value |
|---|---|
| Min | |
| Simulations with profit | |
| Median | |
| Mean | |
| Simulations over 1 million | |
| Max |
How often were different profits seen?
Histogram looking at how often different post-tax profits were seen in simulations.
What were the individual simulation results?
Time and post-tax proft for individual simulations. Click on a dot to see an individual simulation.
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