Monte Carlo simulation chart
Monte Carlo simulation is like running an experiment on your computer—using randomness to explore many possible futures. In this example, we use pricing models to simulate 1000 possible outcomes to get our statistics. The plot above shows all 1000 possibilities. The darker areas are the regions of high probability.

See the odds before you commit capital

We simulated thousands of possible market paths for a common options income trade to answer three business questions:

  1. How often do we hit our profit targets?
  2. How bad can losses get—and how likely are they?

What the simulation says (at a glance)

Target Profit Probability When This Occurs
25% 93% Any time before expiration
50% 86% Any time before expiration
100% 71% At expiration

There’s roughly a 13% chance of a large loss (~2× max profit) if you run the trade without guardrails. That tail risk can be managed with earlier exits and sizing.

What you can do with this

  • Take-profit: Close around 45–50% to lock in the high-probability win while avoiding late-stage risk.
  • Time stop: Exit by a defined day (e.g., a specific number of days before expiration) if target isn’t reached.
  • Position size: Cap unit count so a 2× adverse move stays within your risk budget.