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Ledgerwise

Monte Carlo projection

simulator

What is the range of outcomes, not just the average?

Runs thousands of correlated stock and bond paths and reports the distribution in real terms, including how often the plan fails.

Your plan

Until withdrawals begin.

60 years
33

In today's money.

70%
7.00%
17.00%
0.20%

Holds your purchasing power constant.

1,500 simulated futures

All figures inflation-adjusted, so they mean what they say.

Plans that never ran out
31%
Median final balance
$0
Worst 10% end with
$0
Best 10% end with
$785,237
Median worst fall in balance
−100%

Peak to trough, including the effect of withdrawals — not a market drawdown

Failing plans run out in
year 48

The range of outcomes

The width of this fan is the point. A single projected line would be a fiction.

$0$200k$400k$600k$800kTarget potYr 0Yr 10Yr 20Yr 30Yr 40Yr 50Yr 60
  • Median outcome
  • Middle half of outcomes (25th–75th)
  • 10th–90th percentile
Bands are percentiles across all runs, in today's money.

This plan fails too often to rely on

Roughly 69% of simulated futures run out of money. The effective levers, roughly in order of impact: withdraw less, retire later, cut fees, and keep the ability to reduce spending after a bad year. Changing the equity share moves this number far less than people expect.

Why this matters

Two modelling choices here, both worth knowing about because they cut in opposite directions.

Returns are drawn from a lognormal distribution with correlated stock and bond series. This is the standard approach and it keeps prices positive, but it understates tail risk: real markets have fatter tails than any normal-family distribution, and correlations rise in exactly the crises where diversification is most needed. 2022, when stocks and bonds fell together, is the failure mode a model like this generates too rarely.

Second, everything is reported in real terms. A projection showing a seven-figure nominal pot is not informative when the question is what it buys.

Treat the worst 10% band as optimistic about disasters, and read the sequence risk explorer alongside this one. That tool preserves the actual historical order of returns, including sequences no distribution would have generated.