Monte Carlo vs. compound interest
Why a single smooth growth rate can hide volatility, sequence risk, diversification, and downside planning ranges.
Monte Carlo portfolio simulator
Portfolio Modeler is a calculator, but the numbers only become useful when the assumptions are understandable. This library explains the concepts behind the simulator in plain language so visitors can interpret results with more context and less false precision.
These articles focus on the questions that come up when people compare stock and ETF portfolios: why the future is modeled as a distribution, how to read percentile bands, what changes when dividends are reinvested, why drawdowns matter, and how taxes or withdrawals can change the planning picture.
A normal compound-interest calculator answers a narrow question: what happens if a portfolio earns the same return every year? A Monte Carlo simulator asks a different question: what range of outcomes could happen if returns, dividend growth, volatility, and correlations vary over time?
The articles below are written to support responsible use of the simulator. They are educational, not personalized investment advice. They are also intentionally cautious: historical returns can be useful, but they are not a guarantee, and the hardest parts of investing often come from behavior, taxes, cash-flow timing, and market stress.
Why a single smooth growth rate can hide volatility, sequence risk, diversification, and downside planning ranges.
What P10, P25, median, mean, P75, and P90 outcomes mean, and how to compare portfolios by range instead of one number.
How reinvested dividends differ from cash dividends and why adjusted-price history matters when modeling total return.
How peak-to-trough losses affect investor behavior, withdrawals, and the realism of a long-term projection.
Why dividend yield and dividend growth are separate assumptions, and how the model treats changing final-year income.
How recurring tax drag, dividend taxes, liquidation taxes, and cash-flow choices can shift portfolio outcomes.