Deterministic Planning vs. Monte Carlo: What Are You Really Risking?

Monte Carlo is often presented as a more advanced version of deterministic retirement planning. But it is important to understand what changes when you switch from one to the other.

Deterministic planning lets you anchor the plan to something you consider important. You can fix your spending and determine your legacy. You can fix your desired legacy and determine how much you can afford to spend. Or you can fix both and determine how much you need to start with.

Suppose conservative deterministic planning tells you that you can spend $50,000 a year, adjusted for inflation, and still finish with a $3 million legacy.

You then decide to increase spending to $70,000, and Monte Carlo says there is an 85% probability of achieving both $70,000 of spending and the $3 million legacy.

What exactly are you risking?

It is tempting to think that you are simply risking the extra $20,000 of spending or perhaps some of the legacy. But that is not necessarily what happens.

In the other 15% of scenarios, you may not only fail to reach the $3 million legacy—you may also fail to sustain even the $50,000 inflation-adjusted spending level that deterministic planning had already supported.

The portfolio could run out in year 23 instead of lasting 30 years.

That is the crucial point: Monte Carlo is not a risk-free way of building on a deterministic plan. By increasing spending based on an acceptable probability of success, you are potentially putting the original, more secure plan at risk as well.

The usual response is to introduce guardrails: spend more now, and if the portfolio deteriorates, cut spending later.

But that assumes the retiree will actually be able to cut spending later. But is that really doable? What if a health condition develops? What if a child needs financial support later?

The best analogy for Monte Carlo is a gun with several chambers and exactly one bullet.

Choosing the Monte Carlo strategy is not simply choosing the chamber with the best outcome. You are accepting the possibility that you end up in the wrong chamber.

That may be perfectly reasonable for someone with substantial outside assets, guaranteed income, or another financial safety net. They can afford to take that chance.

But for someone whose retirement portfolio is responsible for essential spending, that gamble may be inappropriate.

Monte Carlo is not a bad tool. It answers a different question:

How much additional spending or legacy am I willing to pursue in exchange for accepting the possibility of failure?

Deterministic planning asks:

What outcome am I unwilling to risk, and how much can I spend while protecting it?

For retirees who want certainty around spending or legacy, that distinction matters enormously.

CherishBuckets.com uses deterministic planning together with the bucket approach to help you create a safer, easier-to-live-with portfolio for your clients.