Lump sum vs dollar-cost averaging into Bitcoin
We took $12,000 and put it into Bitcoin two ways. Once as a lump sum, meaning the whole amount on day one. Once as 12 equal monthly buys, which is dollar-cost averaging, or DCA. Then we did it again starting on the first of every month from Sep 2010 to Nov 2025. That is 183 windows, and each shares 11 of its 12 months with the next. The lump sum ended up holding more BTC in 68.3% of them. Across all 183, the middle result was +29.5% BTC for the lump sum against DCA. Taking only windows that share no months leaves 15 to 16, depending on which month the count starts from, and across the 12 ways of choosing them the lump sum held more in between 53.3% and 73.3%. The rest of this page is about what those numbers can and cannot tell you.
Lump sum held more
68.3%
of 183 overlapping start months
Windows sharing no months
53–73%
Lump sum held more, across 15 to 16 windows
Worst lump-sum window
-69.0%
BTC against DCA. Started Jul 2011
Best lump-sum window
+499%
BTC against DCA. Started Oct 2010
Read the question before the answer
This comparison only exists if the money is already sitting there today. Someone investing out of a monthly paycheck has no lump sum to compare against: buying as the money arrives is the only version on offer, and nothing below applies. Everything on this page is about a windfall: an inheritance, a bonus, a sale.
The longer the buys were spread, the more often the lump sum held more
$12,000 deployed either at once, or in equal monthly buys over the period shown. Every start month with a complete deployment period is included. Positive numbers mean the lump sum ended with more BTC.
| Spread over | Lump sum held more | Windows | Median difference | Middle 80% range |
|---|---|---|---|---|
| 3 months$4,000 per month | 60.4%57.8% to 64.1% | 19264 share no months | +5.9% | -17.2% to +33.5% |
| 6 months$2,000 per month | 64.0%58.1% to 71.9% | 18931 to 32 share no months | +9.3% | -27.1% to +85.9% |
| 12 months$1,000 per month | 68.3%53.3% to 73.3% | 18315 to 16 share no months | +29.5% | -40.3% to +156% |
| 24 months$500 per month | 74.3%57.1% to 100% | 1717 to 8 share no months | +80.1% | -40.9% to +290% |
The large figures count every start month, and consecutive start months share all but one month of their period. The small figures under them are the same comparison on windows that share no months: the lowest and highest share the lump sum reached across the ways of choosing them, and how many there are.
In the large figures, the lump sum's share and its median lead both grow with every longer period. The reason is mechanical: money waiting in cash is not in Bitcoin, and across this sample the price in our series went from $0.06 on Sep 1, 2010 to $83,678 on Oct 11, 2026. The middle-80% range widens with every longer period too. Spreading the buys for longer stretched the gap between the two in both directions, not only the middle of it.
Where each side stood when the last buy went in
The same 183 windows of 12 months. Each side's return on the $12,000, at the price on the day of the final DCA purchase. Worst case first.
| Across all windows | Lump sum | 12 monthly buys |
|---|---|---|
| Worst window | -70.0% | -51.5% |
| 10th percentile | -51.7% | -29.5% |
| Median | +86.3% | +37.0% |
| 90th percentile | +889% | +296% |
| Best window | +24,200% | +5,966% |
| Stood below what was paid in | 28.4% | 25.1% |
Both sides are valued on the day the buying finished, so the final DCA purchase counts at exactly what was paid for it. Both columns come from the same overlapping windows as the table above, and at most 16 of those share no months.
By where the price stood on the start date
The same 12-month windows, grouped by how far below its highest daily price so far Bitcoin was on the start date.
| Price on the start date | Lump sum held more | Windows | Median difference | Worst / best |
|---|---|---|---|---|
| Within 10% of the highest price so far | 60.0% | 306 share no months | +11.4% | -51.7% / +262% |
| 10% to 50% below it | 65.6% | 6410 share no months | +36.7% | -69.0% / +364% |
| 50% or more below it | 73.0% | 8911 share no months | +29.8% | -64.5% / +499% |
The lump sum held more in 60.0% of the windows that started within 10% of the highest price so far, and in 73.0% of those that started 50% or more below it. Starting near the high was its weakest case in this sample. Even there it held more than DCA in most windows. Only 6 of those 30 near-the-high windows can be chosen without two of them sharing a month, so that row rests on about 6 separate periods.
What the numbers do and do not mean
Where the difference comes from. Money that is waiting to be spent is not in Bitcoin. Spread a fixed sum over 12 monthly buys and, between the first buy and the last, half of it on average is still in cash. Across this sample the price in our series went from $0.06 on Sep 1, 2010 to $83,678 on Oct 11, 2026, and in 68.3% of windows the monthly buys ended up paying a higher average price than the price on day one. The same pattern has been measured in stock markets. Vanguard's February 2023 study found a lump sum ahead of a three-month split 68% of the time after one year on the MSCI World Index from 1976 to 2022, and gives the same reason: money held in cash misses the market's return while it waits. Source: Vanguard, "Cost averaging: Invest now or temporarily hold your cash?" (February 2023), read Oct 12, 2026. Its split is three months and its asset is a stock index; it is cited for the direction, not as a figure for Bitcoin.
The range each side finished in. Averaging over 12 prices instead of one means no single day sets what was paid. When the last of the 12 buys went in, the worst DCA window stood at -51.5% on the money paid in against -70.0% for the lump sum, and the best at +5,966% against +24,200%. DCA windows stood below what was paid in 25.1% of the time, lump-sum windows 28.4%.
The worst window, in full. The lump sum's worst 12-month window against DCA started in Jul 2011 and finished with 69.0% less Bitcoin than the DCA side. When the last buy went in, that lump sum stood at -70.0% on the money paid in and the DCA side at -3.3%. This page measures prices. It cannot say whether anyone would have held through either.
This is one price history, and the windows overlap. Bitcoin has only ever taken one path, and back-to-back 12-month windows share 11 of their 12 months. So these 183 windows are nowhere near 183 separate tests: at most 16 of them can be chosen without two sharing a month. The whole sample also sits inside one rise, from $0.06 on Sep 1, 2010 to $83,678 on Oct 11, 2026. A percentage on this page describes what happened. It is not a probability of what will happen.
The shorter splits sit in between. Spreading the money over 3 months instead of 12 left a median difference of +5.9% BTC for the lump sum against +29.5%, and a middle-80% range of -17.2% to +33.5% against -40.3% to +156%. In this sample a shorter split gave up less of the lump sum's historical edge and stayed closer to it in both directions; a longer one did the reverse.
How these numbers were computed
Start dates step one calendar month at a time from Sep 1, 2010 to Nov 1, 2025. We keep only the windows that finish inside the price data. For each one, the lump-sum side buys $12,000 of Bitcoin at the price on the start date. The DCA side buys an equal share on the same day of each following month, using the same engine as the main calculator. Fees are zero on both sides. Both end up holding only Bitcoin, so which one holds more does not depend on any later price. The “when the last buy went in” table values both sides at the price on the day of the final DCA purchase. Each window is grouped by the highest daily price in our series up to its own start date, so no later price is involved.
Everything uses one price per UTC day. From Jul 20, 2015 that is Coinbase's daily candle close. Before it, it is blockchain.info's market price, an average across exchanges stamped at 00:00 UTC, which tracks the previous day's close; a purchase dated the 1st in those years is priced at about the close of the day before. If Coinbase's daily closes cannot be loaded the page keeps its last computed figures; it does not switch to another series. Figures refresh once every 24 hours, and the data currently runs to Oct 11, 2026. Price sources, fee math and UTC handling are on the methodology page.
Common questions
Is lump sum or DCA better for Bitcoin?
A lump sum means putting the whole amount in on day one. DCA, or dollar-cost averaging, means splitting it into equal buys spread over time. Across 183 start months since Sep 2010, putting $12,000 in at once ended with more Bitcoin than 12 monthly buys in 68.3% of them. The middle result was +29.5% BTC for the lump sum against DCA, and the worst was -69.0%. Those windows overlap: each shares 11 of its 12 months with the next. Taking only windows that share no months leaves 15 to 16, depending on which month the count starts from, and across the 12 ways of choosing them the lump sum held more in between 53.3% and 73.3%. That is what happened in one price history. Whether it is the better choice for a particular person is a different question, and this page does not answer it.
What explains the difference between the two?
Money that is waiting to be spent is not in Bitcoin. Spread a fixed sum over 12 monthly buys and, between the first buy and the last, half of it on average is still in cash. Across this sample the price in our series went from $0.06 on Sep 1, 2010 to $83,678 on Oct 11, 2026, and in 68.3% of windows the monthly buys ended up paying a higher average price than the price on day one. The same pattern has been measured in stock markets. Vanguard's February 2023 study found a lump sum ahead of a three-month split 68% of the time after one year on the MSCI World Index from 1976 to 2022, and gives the same reason: money held in cash misses the market's return while it waits.
Source: Vanguard, "Cost averaging: Invest now or temporarily hold your cash?" (February 2023)
When does DCA beat lump sum?
When the price falls after the start date, because the later buys are then made at lower prices. In this sample the lump sum held more in 60.0% of the 30 windows that started within 10% of the highest price so far, and in 73.0% of the 89 that started 50% or more below it.
Does DCA reduce risk?
It changes which prices you pay. When the last of the 12 buys went in, the worst DCA window stood at -51.5% on the money paid in against -70.0% for the lump sum, and the best at +5,966% against +24,200%. DCA windows stood below what was paid in 25.1% of the time, lump-sum windows 28.4%. Neither approach does anything about the risk that Bitcoin itself falls and stays down.
I get paid monthly and do not have a lump sum. Does this page apply to me?
No. The comparison only exists if the money is already there as a lump today: an inheritance, a bonus, a house sale. Buying out of income as it arrives is not a choice between a lump sum and DCA, because there is no lump to put in.
How were these numbers calculated?
For each start month, $12,000 goes in both ways with zero fees, using the same engine as the main calculator and one price per UTC day: Coinbase's daily close from Jul 20, 2015, and before that blockchain.info's market price at 00:00 UTC, which tracks the previous day's close. Both sides end up holding only Bitcoin, so which one holds more does not depend on any later price. Returns "when the last buy went in" value both sides at the price on the day of the final DCA purchase. All dates are UTC. Windows overlap and Bitcoin has exactly one price history, so these are descriptions of the past, not probabilities.
Run your own numbers
Your amount, your dates, your fees. The calculator runs a DCA schedule against the same price history and shows the lump-sum version right next to it. You get the trade-off on your own numbers instead of an average.
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Not financial advice. This page is a historical simulation published for educational purposes. Past performance does not guarantee future results, and a win rate measured on overlapping windows of a single price history is not a probability. Bitcoin is volatile and you can lose money.