DCA calculator
Compare buying at regular intervals against committing the same total on day one, using real historical daily closing prices.
Backtested on real daily closes for BTC from Binance. The window dominates the result — pick a different start and the comparison can invert. Averaging buys a smaller worst case, not a higher return, and a past window tells you nothing about a future one.
How the comparison is made fair
The lump sum commits the same total amount the DCA plan would spend over the whole window, all on the first day. That is the only like-for-like comparison. Comparing a schedule of small buys against a single larger one is comparing two different amounts of money and tells you nothing.
Buys are executed at real daily closes. There is no fee modelling here, so both strategies are flattered equally — in practice DCA incurs more transactions and therefore more fees, which narrows any advantage it shows.
The window dominates the result
This is the most important thing on the page. On a market that rose steadily, the lump sum wins, because every DCA purchase after the first buys at a higher price. On a market that fell and recovered, DCA wins, because the later buys accumulate more units cheaply. Change the start date by a few weeks and the answer can invert entirely.
That is not a flaw in the calculator — it is the actual finding, and it is why any confident claim that one approach beats the other is really a claim about which window was chosen. A backtest tells you what would have happened in one specific past. It does not tell you what will happen next.
What averaging actually buys you
Not higher returns. Spreading purchases reduces the consequence of being wrong about timing: it lowers the variance of your entry price, so the worst realistic outcome is less bad. In exchange, the best outcome is also less good. If you have a lump available and the market rises, you will underperform — and knowing that in advance is the point.
The average cost figure shows the mean price you paid per unit across all purchases. Comparing it against the price at the start and end of the window shows where your entries actually landed.
Frequently asked
Which frequency is best? The differences between weekly, fortnightly and monthly are small and inconsistent across windows. Frequency matters far less than whether you keep going.
Does this include fees? No. Add your exchange’s fee to every purchase, and note that more frequent buying means paying it more often.
Is a good backtest a reason to start? No. Past windows are not predictions, and this tool will happily show you a window that supports whatever you already believed.