Stock analysis model
Monte Carlo Simulation
Monte Carlo simulation models many possible future stock price paths by combining historical return patterns with random variation. It is a risk and probability tool rather than a single intrinsic value estimate.
When Monte Carlo simulation is useful
- Visualizing a range of possible outcomes instead of relying on one forecast.
- Understanding how volatility affects future price uncertainty.
- Supporting scenario analysis and risk-aware investment decisions.
Limitations to consider
- Results depend on assumptions derived from historical data.
- Real markets can experience regime changes, extreme events and non-normal returns.
- A simulation describes possible outcomes but does not determine fair value on its own.
How the model works
- 1Collect historical stock prices over a suitable observation period.
- 2Calculate periodic logarithmic returns.
- 3Estimate historical drift and volatility from those returns.
- 4Generate random returns for each simulated future period.
- 5Build thousands of possible price paths from the current price.
- 6Summarize the distribution using median, average and percentile outcomes.
How to interpret the result
The result should be read as a distribution of possible outcomes. Percentiles can show downside and upside ranges, while the median represents the middle simulated outcome. A narrow range suggests lower modeled uncertainty; a wide range reflects higher volatility and risk.
Frequently asked questions
Does Monte Carlo simulation predict a stock price?
It does not predict one certain price. It generates a probability distribution of possible outcomes based on the assumptions and historical data used.
How many simulations are enough?
Thousands of runs are commonly used. More simulations generally make the distribution more stable, although better assumptions matter more than an extremely high run count.
Is Monte Carlo simulation a valuation model?
It is primarily a risk and scenario model. It can complement valuation work, but it does not directly estimate intrinsic business value like a DCF or DDM.
Learn the method in context
Go beyond the score with worked explanations, assumptions and common mistakes in the Stock Insights Academy.
Read the related Academy guideApply Monte Carlo simulation to a stock
Use Stock Insights to combine this model with additional valuation and financial health checks.
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