Lump sum invests earlier (more time in the market). Dollar-cost averaging spreads timing risk. Use the calculator to model both.
Model both strategiesStudies consistently show that lump sum investing beats dollar-cost averaging (DCA) roughly two-thirds of the time over a 12-month deployment period. The reason is simple: markets go up more often than they go down, so money invested immediately tends to outperform money held in cash waiting to be deployed. Vanguard's research on US, UK and Australian markets found lump sum investing outperformed DCA by an average of 2-3% over 12 months. However, "on average" hides a lot — in the one-third of cases where markets fell, DCA came out ahead.
How it works: you invest the full amount immediately, then it grows from day one.
Best for: windfalls, inheritance, proceeds from selling property, or anyone comfortable with short-term volatility.
How it works: you split the amount into equal portions and invest at regular intervals (weekly, monthly).
Best for: regular salary investors, people with high loss aversion, or anyone deploying a large sum who would panic-sell after a drop.
For most Australians, DCA is simply how investing works in practice — you invest from your salary each month into ETFs like VAS or VGS. The lump sum vs DCA question mainly arises when you have a windfall (inheritance, property sale, redundancy payout). In that case, a short DCA period of 3-6 months is a reasonable middle ground — you capture most of the lump sum advantage while reducing the emotional risk of a bad entry point. Superannuation contributions are by nature DCA — your employer contributes monthly, smoothing your entry price automatically over decades.
Often it wins mathematically because money is invested sooner, but timing risk and behaviour matter.
It can feel safer because you spread entry points over time, but it can reduce returns if markets rise.
A reasonable compromise is a short DCA period (e.g. 3–6 months), then commit to the plan.
Yes. Use a smaller lump sum plus monthly contributions.
No. It uses an average return assumption for education and scenario testing.