Dollar-cost averaging: how to smooth out US stock purchases in a volatile market
In March 2026 the S&P 500 fell 5% and the VIX finished the month near 25, having broken above 30 on several days. Five months later the same index was setting records and the VIX had closed at 14.25, its lowest reading of the year. An investor sitting on cash in March, waiting for things to settle down, spent the recovery watching from the outside.
Dollar-cost averaging is one response to that problem. An investor commits a fixed sum on a fixed schedule and buys whatever that sum buys on the day, without forming a view on whether the day is a good one to be buying. Share counts vary month to month as prices move around.
The research does not treat this as a way to make more money, and neither does this article. What a schedule changes is how many separate judgement calls an investor has to get through in a year.
What dollar-cost averaging does to the price you pay
Fixed-amount purchases buy more shares when prices are low and fewer when prices are high. The cheap months account for more of the total share count, which pulls the average cost per share below the simple average of the prices paid.
The arithmetic on a hypothetical $500 monthly purchase over six months:
Month | Share price | Shares bought with $500 |
1 | $100 | 5.00 |
2 | $88 | 5.68 |
3 | $92 | 5.43 |
4 | $105 | 4.76 |
5 | $80 | 6.25 |
6 | $96 | 5.21 |
Total | Average price $93.50 | 32.34 shares |
Total invested is $3,000 for 32.34 shares, an average cost of $92.77 against an average share price of $93.50. Seventy-three cents, across six months that included a 20% drop. The whole gap comes from months two and five, when the fixed $500 stretched further than usual.
This example is illustrative only. It uses invented prices to show how the mechanic works, and it does not reflect the past or expected performance of any security or of any CUSP Wealth product.
Run the same six months with prices that only rise and the average cost lands above the opening price, where a single purchase in month one would have beaten it. Spreading purchases across a price range helps when the range includes cheap months, and there is no way to know in advance whether it will.
Why the US stock market keeps producing uncomfortable months
Since 1980 the S&P 500 has seen an average intra-year drop of about 14,2% while ending the year positive in 35 of 46 years, according to J.P. Morgan Asset Management. Double-digit falls at some point during the year are closer to routine than to exceptional, including in years that finish well.
2026 has added a wrinkle. Index-level volatility spent much of the summer unusually low while individual stocks swung hard. On 9 July the gap between the VIX and Cboe's single-stock volatility measure reached a record 34.14 points, with the single-stock index in the 98th percentile of readings since 2014. Correlations between constituents were low enough that individual moves cancelled each other out at index level, leaving a calm-looking benchmark sitting on top of a lot of movement.
The distinction matters for anyone buying individual US names rather than broad exposure, since a benchmark's volatility says very little about what a concentrated holding did over the same stretch.
Market timing risk: the cost of waiting for a better entry point
Waiting for a clearer entry point has a price, and the price can be measured. Wells Fargo Investment Institute looked at S&P 500 daily returns from July 1995 to June 2025 and found that missing the 30 best days took the average annual return from 8.4% down to 2.1%, below the 2.5% average inflation rate over the same span. Missing the 50 best days produced a negative annual average.
That statistic has a mirror image, and the fuller version is more honest. Morningstar reran the exercise in March 2026 and found that avoiding the ten worst days would have gained an investor more than missing the ten best days cost them, because losses weigh more heavily once compounded. The obstacle is that both sets of days sit in the same stretches of market history. Jack Manley of J.P. Morgan Asset Management told CNBC in April 2026 that six of the market's ten best days over the past two decades landed within two weeks of its ten worst days, which leaves very little room to capture one while dodging the other.
A standing purchase schedule keeps buying through those weeks without anyone having to form a view on them.
Lump sum vs DCA: what the research actually shows
Vanguard's work on this is the most cited, and it does not favour dollar-cost averaging on returns. Comparing the two approaches over rolling one-year periods between 1976 and 2022 across several markets, Vanguard found that investing a lump sum immediately beat cost averaging between 61.6% and 73.7% of the time, with the lump-sum advantage widening the longer the averaging window ran.
The reason is unglamorous. Markets have historically drifted upward, so cash held back during the averaging window spends that time out of the market. Vanguard's own framing is that cost averaging trades expected return for a smoother deployment period, a risk decision an investor is entitled to make.
The comparison only applies when there is a lump sum to deploy in the first place. Someone investing part of a monthly salary has no pile of cash waiting; they are buying with money that did not exist last month, and the question of deploying it all at once never comes up. Regular fixed-amount investing is the shape that situation naturally takes.
Where a lump sum does exist, the trade-off is worth naming honestly. Deploying $60,000 at once and holding through whatever follows has history on its side. An investor who deploys $60,000 and then sells out in the first bad quarter has measured themselves against a strategy they were never going to run.
Behavioural finance: why DCA investing holds up when markets fall
Morningstar's Mind the Gap study puts a number on that second case. Over the decade to the end of 2025, the average dollar invested in US funds and ETFs earned 8.7% a year against the funds' 9.9% aggregate return, a shortfall of 1.2 percentage points, or roughly 12% of what those funds produced. Morningstar attributes it to the timing and size of investors' own purchases and sales rather than to fund performance. Across the $13.6 trillion asset base in the study, that came to roughly $3.8 trillion in foregone wealth.
The volatility split inside the finding is the useful part here. The gap was 0.4 percentage points for the least volatile funds and 2.1 points for the most volatile ones. Rockier holdings produced more self-inflicted damage through the timing of trades.
US stock fund investors came out well, capturing 12.8% a year against a 13.3% fund return, which Morningstar attributed partly to comparatively steady flows into the category.
Behavioural finance reads this in a fairly ordinary way. Loss aversion makes a 20% drawdown feel considerably worse than a 20% gain feels good, and the instinctive response to that feeling is to stop buying until things look calmer. A purchase that executes on a set date never reaches the point where the feeling gets a vote.
Volatility management: what dollar-cost averaging cannot do
Averaging into a falling market lowers the average cost of a position while the position itself keeps losing value. An investor buying through a two-year decline ends up holding a growing pile of shares worth less than what was paid for them, which is uncomfortable in a way that no amount of arithmetic fixes.
Diversification is a separate question. Averaging into one company at monthly intervals leaves an investor fully exposed to that company, and volatility management across a portfolio comes from what is held and in what proportions.
Some mechanics repay a check before a schedule starts. Frequent small purchases make the cost of each transaction more relevant than it would be for one annual purchase, so a platform's pricing schedule is worth reading closely. Fractional share dealing matters too, since $500 will not buy a whole share of a stock trading above that price, and the fixed-amount mechanic breaks down without it.
Protection is worth understanding as well, since averaging in means money sits in cash for months before it reaches the market. Investments are not bank deposits and are not covered by a deposit protection scheme. Where a US broker holds the assets, SIPC coverage may apply if the broker fails, up to $500,000 in total including a $250,000 sublimit for cash. No scheme covers losses caused by market movements. The value of investments can fall as well as rise, and an investor may get back less than they put in.
Setting up an automated recurring investment
An automated recurring investment is a standing instruction the investor writes: an amount, a date, and what to buy. The investor sets each element and can change or cancel the instruction whenever they want.
Where those variables land has some bearing on whether a schedule survives a full market cycle.
Choosing an amount
Some investors size the contribution so that it survives a bad month rather than stretching to the maximum they could afford in a good one, on the view that a schedule abandoned in month four leaves them worse off than a smaller one still running in year five.
Choosing a date
Purchases anchored close to payday may be less likely to compete with other uses of the money. Beyond that, the specific calendar date appears to have very little bearing on long-run outcomes, provided the purchase recurs without being renegotiated each month.
Deciding what gets bought
Broad US equity exposure behaves differently under a fixed-amount schedule than a single stock does. Investors building positions in individual names could look at how concentrated the portfolio becomes after a year of purchases.
Reviewing the schedule
A periodic look at whether the amount still fits the household budget is a different exercise from monitoring the position itself, and an investor may want to keep the two apart.
Where dollar-cost averaging fits in a US stock portfolio
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Dollar-cost averaging is a modest tool with modest claims attached. Its usefulness sits in the stretches where investing feels wrong and the schedule carries on anyway. Morningstar's 1.2-point gap is one measure of what goes missing when it does not. A well-timed lump sum will still beat it in a rising market, and no schedule protects a portfolio from a sustained decline.
Dollar-cost averaging FAQ
Is dollar-cost averaging better than investing a lump sum?
How often should DCA purchases be made?
Does dollar-cost averaging work for individual US stocks?
What happens to a DCA plan when the market keeps falling?
Can DCA investing be set up automatically?
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The information in this article is current as of September 2026 and is subject to change.
