Overview
Monte Carlo simulation projects the range of possible future values for a portfolio or a basket of stocks. Instead of producing one guess, it generates thousands of randomized future paths, then reports the typical outcome, the optimistic and pessimistic tails, and the odds of gaining, losing, or reaching a goal across a horizon you choose. This page explains what the tool does, who it is for, and what you receive. The tool is available to Free, Pro Lite, and Pro accounts, with limits that vary by tier.
What it shows
The tool answers a question that a single point forecast cannot: if you hold this mix for a set number of years, what could it be worth, and how likely is each outcome. It models uncertainty directly, so you see a spread of results rather than one number.
Once a run completes, you get a full results report:
- Three headline numbers: Expected Final Value, Median Outcome, and Probability of Loss.
- A projection chart with percentile bands and an outcome histogram.
- A risk-analysis block, risk-adjusted ratios, and outcome-probability thresholds.
- A per-holding breakdown and, when more than one holding is present, a correlation view.
- Deep distribution statistics, and an optional cash-flow and costs block when you configure those.
Every run is saved to your History, so you can reopen it, export it to a spreadsheet, rerun it, or compare several runs side by side.
Who it is for
The tool suits any investor who wants to understand uncertainty rather than a single point forecast. It fits retirement planners modeling withdrawals, savers modeling contributions, and anyone stress-testing a basket against calmer or harsher market regimes.
Tiers and access
The page is available to Free, Pro Lite, and Pro accounts. Free and Pro Lite can run simulations on a custom basket of stocks, with a daily run cap and a smaller ticker limit. Pro can also simulate its own saved portfolios, model portfolios, and combined portfolios, with a larger ticker limit and effectively unlimited daily runs. The literal limits live in the live tier table. For the figures, see Plans and tiers.
How it fits in
Monte Carlo simulation is a forward-looking companion to the Backtester, which tests a strategy against real past history. Use the backtester to ask what would have happened, and use Monte Carlo to ask what could happen next, given the historical behavior of your holdings. To project income rather than total value, use the Dividend forecaster.
Use cases
- Project a portfolio over a long horizon with regular withdrawals and read the chance the balance survives.
- Set a savings goal with monthly contributions and read the probability of reaching it.
- Stress-test a basket by running it under calmer and harsher scenarios, then comparing the downside.
- Compare two baskets or two weighting schemes by median outcome and risk-adjusted return.
- Check whether a basket is genuinely diversified or behaves like one concentrated bet.
Limitations and disclosures
The simulation assumes the future behaves statistically like the historical window you choose. It cannot anticipate regime changes, liquidity gaps, or events outside that window, and the stress scenarios are uniform settings, not forecasts of any specific event. Outcomes are modeled probabilities based on historical data and a chosen scenario, so real markets can move outside the simulated range.
GNG Research provides equity research and educational tools, not investment advice. Nothing on the platform is a recommendation to buy or sell any security. Do your own research and consider your circumstances before making any investment decision.