Client Deliverables
All at once,
or spread out?
When a large sum is ready to invest, the instinct is to ease it in slowly to avoid buying at a peak. The historical record is less sentimental: across nearly three decades of U.S. large-cap data, deploying all at once beat spreading it out roughly 70% of the time. But that statistic isn't the whole story — and a simple hybrid splits the difference.
The question we actually answer
Three deployment methods, one historical dataset: invest the whole sum on day one (lump sum), spread it across twelve monthly buys (dollar-cost averaging), or do half on day one and average the rest over six months (a 50/50 hybrid). Each is run over every rolling start window across the same period, so the comparison rests on history rather than a single anecdote. The examination reports how often each method won, by how much, and — most usefully — what each method actually buys the saver.
Lump-sum deployment outperformed twelve-month averaging in roughly 70% of historical start windows, largely because markets rose in about seven of every ten calendar years — so cash held back missed upside more often than it dodged a drawdown. Averaging's wins were rarer but, in crash years, larger.
| Measure | Lump sum | 12-month averaging |
|---|---|---|
| Share of windows won | ~70% | ~30% |
| Avg. entry-price effect | — | ~+2.3% to +2.8% (paid more) |
| Avg. year-end value of $2M | ~$2.13M | ~$2.07M |
| Avg. lump-sum edge | ~$68,000 on a $2M deployment | |
| Method | What it optimizes |
|---|---|
| Lump sum | Expected return — wins most often, gives up drawdown cushion |
| 12-month averaging | Worst-case comfort — drawdown insurance, not optimization |
| 50/50 hybrid | Most of the expected-return edge, ~half the worst-case drawdown |
Historical study. S&P 500 month-start values, ~1999–2025, total return excluding dividends; averaging modeled as twelve equal monthly buys. Past patterns do not predict future results. Not a recommendation of any deployment method.
"Averaging isn't a return optimizer. It's drawdown insurance — and it has a premium."
How the examination is built
- Define the methods precisely. Lump sum, twelve equal monthly buys, and a half-now / average-the-rest hybrid — no ambiguity.
- Run every start window. Each method is tested across all rolling start dates in the period, not a single lucky or unlucky year.
- Measure win rate and magnitude. How often each method won, and by how much — because a method can win often and small, or rarely and large.
- Separate return from comfort. We distinguish what improves expected outcome from what reduces worst-case pain; they are different goals.
- Price the insurance. Averaging's drawdown protection comes at an average entry-price premium, which we state rather than hide.
What this examination is — and is not
This is a historical study of deployment methods. It is not a recommendation of any method and not a prediction of future markets. It reframes the choice from "which wins" to "which goal you are buying" — expected return or worst-case comfort — and leaves the decision with the household.
Want this checked against your actual account?
This examination shows one way money can quietly leave a portfolio. If you want us to examine what may be happening in your actual accounts, request a confidential fee review.
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