How to Read Our Charts: Proxy Data, Real Returns, and Heatmaps

Every chart and metric on this site rests on a specific set of data choices and assumptions. Understanding them helps you interpret the numbers honestly and know their limits. This is our methodology in plain English — the same information a careful reader should want before trusting any backtest.

Where the data comes from

Price history is sourced from Yahoo Finance and refreshed once daily at about 06:00 UTC by an automated pipeline that commits updated figures and rebuilds the site. Strategy and ETF metadata — target weights, expense ratios, the index each fund tracks — is maintained in the site's code and checked against primary sources such as fund fact sheets and Portfolio Charts. Backtests use monthly total returns, which include reinvested dividends.

Proxy data and the dashed line

Many ETFs are younger than the 30-year windows we show. Where a fund did not yet exist, we extend its history with a representative index proxy for the same asset class — for example, a gold price index before a gold ETF launched. On every chart, these proxy segments are drawn as a dashed line, and real fund data as a solid line, so you can always see where genuine fund history begins. Proxies approximate an asset class; they will not match the eventual fund exactly, so treat the earliest years as directional rather than precise.

Nominal versus real returns

By default, growth charts show nominal values — actual dollars. The simulator also offers a real toggle that strips out inflation to show purchasing power, using a fixed assumed inflation rate rather than a live CPI series. For any long-term or retirement decision, the real view is the honest one, because a dollar decades from now buys far less than a dollar today.

Reading the returns heatmap

The annual-returns heatmap shows each calendar year as a colored cell — green for gains, red for losses, with deeper color meaning larger moves. Scanning a row reveals how a strategy behaved year by year: which years hurt, how often losses clustered, and how quickly good years followed bad. It makes patterns visible that a single CAGR number hides.

Assumptions and limitations

A few fixed assumptions shape every result: an assumed risk-free rate feeds the Sharpe and Sortino ratios, a fixed inflation rate feeds the real-return toggle, and backtests exclude taxes and trading commissions. Monthly resolution smooths over intra-month extremes. None of this makes the figures useless — it makes them educational illustrations of how allocations behave, not forecasts. Read them alongside our risk metrics guide, and remember that past performance never guarantees future results.