How the projection engine works

Ironlake's retirement and what-if projection is deterministic. It does not run a Monte Carlo simulation and report a "probability of success." Instead it computes three explicit scenarios from assumptions you can inspect and change, and shows the full year-by-year path of each. The goal is a defensible answer to one question: does the plan cover what you need to spend, under each set of assumptions?

The three scenarios

Every projection produces three traces from your model's per-class assumptions:

• Base - your assumptions exactly as entered.
• Conservative - expected returns reduced by a fixed amount and inflation raised, holding income yields constant.
• Stressed - a one-time equity-sleeve drawdown (default -30%) in an early "stress year" (default year 3); every subsequent year uses base returns. There is no modeled recovery curve - the portfolio recovers only through ordinary compounding afterward, not a special bounce.

Each trace is a year-by-year series: portfolio value, contributions and withdrawals, and the effect of any lump-sum events you add. Where a trace runs the portfolio to zero, the year of depletion is recorded as a failure marker so you can see not just whether but when a plan breaks under that scenario.

What the inputs are

The projection reads the return-related per-class assumptions on your Asset Allocation Model - the expected return, inflation expectation, and income yield - plus your scenario inputs (retirement year, spending, lump sums). Other model fields (the volatility band, tax character, and benchmark) are recorded for other surfaces and do not feed the projection, so changing them will not move the traces. Every input that does drive a result is visible on the model and the scenario, and changing one re-renders the traces.

Why deterministic, not Monte Carlo

A single "87% success" number invites false precision and a dual-trust failure mode - the user trusts a probability that is itself only as good as the return distribution assumed. Three transparent scenarios are easier to defend, easier to reason about, and align with the product's constructive, decision-support stance. If a probabilistic stress view is added later, it would be a supplementary lens, not the planning answer.

Limitations (read these)

• It is illustrative, from your inputs - not a forecast and not a guarantee. Garbage in, garbage out: the traces are only as good as the assumptions you set.
• Returns within a trace are applied as smoothed assumptions, not a path of real historical sequences (the stressed trace adds one explicit drawdown, not a full sequence-of-returns simulation).
• It is not advice. Ironlake shows the math so you can decide; it does not tell you whether to retire, save more, or change your allocation.
• Taxes on withdrawals are modeled at the planning level, not as a line-by-line return; for the precise after-tax treatment of income, see tax-character and after-tax math.

See it on your own model