Bitcoin DCA calculator | DCA vs lump sum timing

Bitcoin DCA calculator

Last updated: January 23, 2026

Dollar cost averaging (DCA) is a simple way to build a position over time without obsessing over timing. This calculator compares a DCA plan against investing the same total capital as a lump sum — either at the start of the period, or at the midpoint.

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Total invested
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DCA contributions
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How it works

Dollar-cost averaging is often framed as a way to “beat volatility”, but that’s not quite right. What it really does is change how you experience volatility. Instead of making one large, time-sensitive decision, you spread purchases out over a fixed schedule, accepting the market price at each interval.

This calculator backtests a DCA strategy using historical Bitcoin prices. You specify a contribution amount, frequency, and date range, and the tool simulates buying Bitcoin at each interval using the closing price for that period. The result is a cumulative Bitcoin balance and a portfolio value over time.

As with all calculators on Bennet.org, price data is sourced from the CoinDesk composite Bitcoin price index (USD) using daily closing prices. Currency conversions are then performed using European Central Bank (ECB) daily reference exchange rates.

In this calculator, contributions are assumed to execute at the period close, and fees are ignored by default. Returns shown are simple returns relative to total invested, not annualised figures.

For context, the chart also shows two lump sum comparisons. These assume the same total capital you invested via DCA is deployed all at once — either at the start of the period, or at its midpoint. This makes the comparison fair: the only variable that changes is timing, not capital.

You’ll often see lump sum outperform DCA in strong uptrends, particularly when prices rise early in the period. That’s expected. What DCA tends to reduce is timing risk and drawdowns (i.e. the severity of any reduction in your investment’s value, from its peak to its lowpoint). It doesn’t necessarily maximise returns. In other words, it’s a behavioural and risk-management tool first, a performance strategy second.

This is a backtesting tool, not a forecasting one. It doesn’t attempt to predict future returns - it shows what did happen, given a specific set of assumptions, and lets you reason from there.

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