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Free tool
DCA Calculator
Dollar-cost averaging means buying a fixed amount on a fixed schedule and ignoring the price. This backtests that strategy against real weekly closing prices — including the losses you would have had to sit through, and how much of the result came down to when you happened to start.
Money in versus what it was worth
Was this a good start date, or a lucky one?
The result above depends heavily on when you happened to start. Running the identical 262-buy schedule from every other possible start date in Bitcoin's history gives 360 outcomes:
Your 1.48x lands in the 1st percentile — better than 1% of start dates. No start date of this length has ended below break-even yet.
Windows overlap and share price history, so these are not independent samples. They show the range of experiences this asset has actually delivered — not a forecast.
Weekly closing prices, last updated 2026-08-01. Bitcoin history begins 2014-09-15. Figures ignore fees, spreads and tax, all of which reduce real returns. Past performance tells you what happened, not what will happen.
Frequently asked questions
What is dollar-cost averaging?
Buying a fixed amount of an asset on a fixed schedule regardless of its price. Because a fixed sum buys more units when the price is low and fewer when it is high, your average cost per unit ends up below the average price over the period. It removes the need to time the market, at the cost of giving up the upside of buying a bottom perfectly.
Where does the price data come from?
Weekly closing prices from Yahoo Finance, covering up to 15 years depending on the asset. The dataset is built at deploy time and last refreshed on 2026-08-01, so every visitor sees identical figures rather than results that shift with a live API.
Why does the tool show the worst start date as well as mine?
Because a single DCA result is close to meaningless on its own. Pick a start just before a bull run and almost any asset looks like a brilliant decision. The tool reruns the identical schedule from every other possible start date in that asset's history, so you can see whether your chosen window was typical, lucky, or unlucky.
What does the 'worst moment' figure mean?
The largest gap between what you had paid in and what your holdings were worth at that time. It is deliberately harsher than a standard peak-to-trough drawdown: in a crash you keep buying, which lifts portfolio value on paper while you are still deeply down on the money you actually spent. It is the number that tells you whether you could have stuck with the plan.
Do these figures include fees and tax?
No. Exchange fees, spreads, network costs and capital gains tax all reduce real returns, and they vary enormously by platform and jurisdiction. Treat every figure here as an upper bound on what the strategy would have delivered.
Why are the outcome windows described as not independent?
Two schedules starting a week apart share almost all of the same price history, so they are not separate experiments. The spread shows the range of experiences the asset has actually produced, which is useful context, but it is not a statistically independent sample and should not be read as a probability distribution for the future.
Why isn't Polygon in the list?
Its price history is split across a token rename: the old MATIC series stops in March 2025, and the ticker that replaced it does not carry a clean continuous record on the data source used here. Rather than stitch two series together or show a chart that silently stops updating, the asset is left out until the history is reliable.
Is dollar-cost averaging better than investing a lump sum?
Historically, lump-sum investing has beaten DCA more often than not in rising markets, simply because the money is exposed for longer. DCA's advantage is behavioural and practical: it suits people investing from income rather than a windfall, and the smaller drawdowns early on make the strategy easier to stick to. Neither approach protects you from a falling asset.