Portfolio Lab

A portfolio backtest is a simulation that runs a hypothetical investment strategy through real historical market data to show how it would have performed. By applying your chosen assets, allocation percentages, contribution schedule, and rebalancing rules to actual past price and dividend history, backtesting reveals how a strategy would have grown, how deeply it would have fallen during market crashes, how long recovery took, and what dividend income it would have generated. It is an educational tool that helps investors understand the historical risk and return characteristics of different strategies before committing real money.

Portfolio Lab uses a month-by-month simulation engine. You define one or more portfolios by selecting securities (ETFs, stocks, or CASH) and assigning allocation percentages that sum to 100%. You choose a date range, initial investment, contribution amount and frequency, rebalancing schedule, and how dividends are handled. The engine downloads historical adjusted closing prices and dividend data for each security, simulates monthly changes — including contributions, dividend events, and rebalancing — and computes metrics such as CAGR, maximum drawdown, recovery periods, and total dividend income. Results are compared against benchmark indexes you select.

Yes, Portfolio Lab is completely free to use with no sign-up required. You can build and compare multiple portfolios, run backtests across any historical date range with available data, and view all charts, metrics, and tables at no cost. An optional account lets you save and reload your portfolio configurations across sessions, but the backtesting engine itself is fully accessible to all visitors.

Yes. Portfolio Lab uses historical adjusted closing prices and dividend event data sourced from financial data providers. Adjusted close prices account for stock splits and other corporate actions, ensuring that long-run return calculations are accurate. Dividend data reflects actual cash distributions per share paid by each security and is refreshed alongside the price history; where the provider has no dividend event for a period a backtest reaches into, the engine estimates it from the dividend-adjusted vs. raw closing-price relationship, and a real provider event always takes precedence. The data is cached server-side and refreshed periodically. Because market data providers may have gaps or corrections over time, results should be treated as estimates rather than audited figures. For a small number of securities with limited price history, an earlier period may instead use estimated returns from an approved substitute security — this is always clearly disclosed in your results. See our Methodology page for details.

Yes. You can build and backtest multiple portfolios simultaneously in Portfolio Lab. Each portfolio gets its own name, set of holdings, and allocation. All portfolios run through the same date range, contribution schedule, and rebalancing rules, so you can make a fair apples-to-apples comparison. Results are displayed side by side in the metrics grid, growth chart, drawdown chart, and strategy comparison table. This makes it easy to compare, for example, a 100% equity portfolio against a 60/40 blend, or a dividend-focused strategy against a total market index.

Yes. Portfolio Lab tracks dividends per security throughout the backtest period. You can choose between two dividend handling modes: Reinvest (dividends automatically purchase additional shares at the month-end price, compounding growth over time) or Cash (dividends accumulate in a separate cash balance). The results panel shows total dividends received, a year-by-year dividend income chart, and an annualized dividend yield for comparing portfolios. This makes Portfolio Lab useful for evaluating dividend growth strategies such as SCHD, VYM, or other dividend-focused ETFs.

Yes. Portfolio Lab includes benchmark comparison against the S&P 500 (SPY), Nasdaq-100 (QQQ), and Dow Jones Industrial Average (DIA) by default. You can enable or disable any of these benchmarks, or add a custom ticker as an additional benchmark. Benchmark performance is shown on the same growth chart as your portfolios, and the strategy comparison table includes a side-by-side CAGR, drawdown, and final value comparison so you can see clearly how your strategy performed relative to major indexes over the same period.

Portfolio Lab includes three default benchmarks: SPY (SPDR S&P 500 ETF), QQQ (Invesco Nasdaq-100 ETF), and DIA (SPDR Dow Jones Industrial Average ETF). You can also type any valid ticker symbol into the custom benchmark field to add additional comparisons — for example, BND for bonds, SCHD for dividend stocks, or GLD for gold. All benchmarks use the same date range and represent a simple buy-and-hold baseline with no contributions or rebalancing applied.

Portfolio Lab shares the core concept with Portfolio Visualizer — both allow you to backtest investment strategies with real market data. Portfolio Lab is designed to be fast, free, and no sign-up required. Key features include multi-portfolio comparison, dividend income analysis, rebalancing simulation, drawdown and recovery tracking, and benchmark comparison. It is designed as a free educational alternative for investors who want to validate strategies using historical evidence, and integrates with the broader SmartRetireCalc retirement planning toolkit so you can move seamlessly from backtesting to full retirement projection.

Yes. Portfolio Lab supports individual stocks (AAPL, MSFT, JNJ), ETFs (VOO, QQQ, SCHD, BND, GLD) — including bond and sector ETFs — mutual funds (for example Fidelity or Vanguard index funds), and the special CASH ticker which represents a 0% cash allocation, for any symbol with historical price and dividend data available. You can mix stocks, ETFs, and mutual funds freely within a single portfolio. Options, futures, cryptocurrencies, currencies, and individual bonds are not supported as portfolio holdings; a market index (such as ^GSPC) can be added as a benchmark but not held as a position. The engine fetches historical data for each supported symbol and simulates the blended performance.

No. Past performance does not guarantee future results. Portfolio Lab is an educational simulation tool that shows how strategies would have performed in historical market conditions. Those conditions — interest rate environments, economic cycles, geopolitical events, and sector dynamics — may not repeat in the same way. A strategy that outperformed over the past 15 years may underperform over the next 15. Backtesting also does not account for taxes, trading costs, emotional decision-making, or liquidity constraints. Use Portfolio Lab to understand historical risk and return patterns, not to predict future performance.

Maximum drawdown (MDD) is the largest peak-to-trough decline in portfolio value during the backtest period, expressed as a percentage. For example, if a portfolio grew to $150,000 and then fell to $90,000 before recovering, the maximum drawdown is 40%. It measures the worst-case loss an investor would have experienced if they bought at the peak and held through the bottom. Maximum drawdown is a critical risk metric because it reflects emotional stress — a strategy with a 50% drawdown may be mathematically sound but psychologically very hard to hold through. Portfolio Lab displays MDD alongside CAGR so you can evaluate return-per-unit-of-risk for each strategy.

Portfolio recovery time is the number of months it took for the portfolio to climb back to its previous peak after a drawdown, measured on the same cash-flow-neutral basis as maximum drawdown — so ongoing contributions, which add nominal dollars without reflecting investment performance, never make a recovery look faster than it really was. A portfolio that fell 40% during the 2008 financial crisis might have taken 4–5 years to fully recover. Recovery time matters because it defines how long an investor must wait before they are "whole" again — especially important for retirees who may be withdrawing during the recovery period. Portfolio Lab displays the longest and average recovery across the drawdowns that closed within your backtest window.

Market data in Portfolio Lab is cached server-side and refreshed periodically. Price history and dividend data for each security is downloaded from financial data providers when first requested and stored with a time-to-live expiry. Historical data rarely changes (adjustments for corporate actions are uncommon), so the cached data is generally accurate for backtesting purposes. Very recent months may have a short lag depending on when the cache was last refreshed. Portfolio Lab is intended for medium-to-long-term historical analysis (1–20+ years) rather than real-time or short-term research.