This simulator is designed for investors who want a more realistic planning range than a single compound-growth line. It turns historical behavior into thousands of possible future paths, then summarizes the outcomes in plain portfolio terms: final value, drawdown, dividend income, taxable drag, and the probability of reaching specific goals.
The model starts by fetching historical monthly prices for each ticker. For reinvested-dividend scenarios, it uses adjusted price history as the return input. For no-DRIP scenarios, it uses regular closing prices so the growth path is not quietly assuming dividend reinvestment.
- Each asset receives its own return estimate, volatility estimate, dividend yield, and dividend-growth estimate from the lookback window.
- Portfolio paths use overlapping monthly covariance so holdings can move together or apart instead of being treated as isolated positions.
- Rebalancing, expense drag, tax drag, contribution timing, withdrawals, and dividend reinvestment settings are applied inside each path.
The percentile chart shows a distribution of possible outcomes, not a promise. A P10 result means 10% of simulated paths finished below that value and 90% finished above it. The median is the middle path, while the mean can be pulled higher by unusually strong upside outcomes.
- Use P10 and P25 to understand downside planning ranges.
- Use P50 to compare the middle result between portfolios.
- Use P75, P90, and P95 to understand upside potential and how wide the range of outcomes may be.
Dividends are modeled separately from price return so the simulator can estimate income, dividend taxes, and the difference between reinvesting dividends and taking them as cash. The final-year dividend section estimates the annual income run-rate in the final simulated year.
- Dividend tax reduces reinvested or cash dividends based on the selected tax rate.
- Annual tax drag lowers portfolio growth to approximate recurring taxable friction, fund turnover, or advisory drag.
- Positive cash flow adds money to the portfolio, while negative cash flow models withdrawals in either monthly-dollar or annual-percentage terms.
Historical data is useful, but future markets do not have to repeat the same pattern. The model does not know future inflation, tax law, investor behavior, fund policy changes, business fundamentals, interest-rate regimes, or valuation changes. Treat the results as a planning lens, not investment advice.
- Short histories can make individual-stock assumptions unstable.
- Large drawdowns may be worse than the estimate if future crises differ from the historical sample.
- Tax estimates are simplified and do not replace advice from a qualified tax professional.
The examples page shows sample ways to compare diversified portfolios, dividend-income portfolios, withdrawal plans, and concentrated growth sleeves. Each example is written around the question the simulation can answer.
- Compare DRIP and no-DRIP assumptions with the same tickers.
- Test fixed monthly withdrawals against percentage withdrawals.
- Study how P10, median, P90, and drawdown shift when allocations change.
The glossary explains the terms used in the simulator, including CAGR, covariance, volatility, P10, P90, maximum drawdown, dividend growth, DRIP, tax drag, starting basis, and liquidation tax.
- Use it when an output label is unfamiliar.
- Review it before comparing portfolios with different risk profiles.
- Pair it with the methodology page to understand how inputs become outputs.
Is this investment advice?
No. Portfolio Modeler is an educational simulator. It can help compare assumptions, but it does not know a visitor's full financial situation and should not be treated as personalized investment, tax, legal, or accounting advice.
Why use Monte Carlo instead of a fixed return?
A fixed return creates one smooth line. Monte Carlo paths show how outcomes can spread out when monthly returns, volatility, correlations, dividends, taxes, contributions, and withdrawals interact over time.
Why do results change when the lookback changes?
The historical window changes the return, volatility, covariance, dividend yield, and dividend growth estimates available to the model. A different window can represent a different market regime.
How should portfolios be compared?
Compare the whole range. A higher median is helpful, but downside percentiles, max drawdowns, goal odds, and final-year dividend income can be more important for real planning decisions.