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One Future vs Many Futures

One Future vs Many Futures: How We Model Your Financial Plan

When we build a financial plan, we’re really answering one big question:

“What are the chances I’ll be okay?”

To answer that properly, we need to talk about how financial projections are created. There are two main ways to model the future:

  • Deterministic modelling

  • Stochastic modelling (Monte Carlo simulation)

They sound technical — but the difference is simple.


The Traditional Approach: Deterministic Modelling

Deterministic modelling assumes a fixed rate of return each year.

For example:

  • Superannuation returns 7% per year.

  • Inflation is 3% per year.

  • Your income grows at 3% per year.

The model then projects one smooth line into the future.

It gives you one answer.

The problem?

Real life doesn’t deliver smooth returns. Markets rise, fall, and sometimes stall for years.

Deterministic modelling shows you one possible future — assuming everything behaves perfectly.

The Real-World Approach: Stochastic Modelling

At Funded Futures Financial Services, we prefer to model uncertainty.

Instead of assuming a steady return, we:

  • Use historical volatility data

  • Apply probability distributions to investment returns

  • Run thousands of different market sequences

This process is called a Monte Carlo simulation.

Rather than showing one future, we simulate thousands of possible futures.

Some are strong.
Some are average.
Some are challenging.

From that, we calculate something far more meaningful:

The probability of achieving your goals.


Why We Only Use Stochastic Modelling From Age 60

Due to software and modelling limitations, we can only apply full stochastic (Monte Carlo) modelling from age 60 onwards.

Before age 60, projections are built using deterministic assumptions.

Why?

Because the modelling engine that runs thousands of randomised retirement income scenarios is specifically designed for the retirement phase — where:

  • Investment returns matter most

  • Withdrawal rates become critical

  • Sequence of returns risk becomes significant

  • Longevity risk needs to be tested

The retirement phase is where variability has the greatest impact on outcomes. That’s where probabilistic modelling adds the most value.

Before age 60, the modelling still provides a structured and realistic projection — but it does not simulate thousands of market paths.

Why This Still Works

Even though stochastic modelling starts at age 60, your overall strategy is still:

  • Built conservatively

  • Reviewed regularly

  • Stress-tested through scenario analysis

  • Adjusted as life changes

Financial planning is not a one-time projection — it’s an ongoing process.

As you approach retirement, we transition fully into probabilistic modelling so we can properly test:

  • Income sustainability

  • Market downturn scenarios

  • Longevity outcomes

  • Spending flexibility

That’s when the detail matters most.


What a Probability Score Actually Means

When we show you something like:

“You have a 78% probability of achieving your retirement objective.”

That means:

  • We ran thousands of possible retirement market scenarios.

  • In 78% of those futures, your plan succeeded.

  • In 22% of those futures, adjustments would likely be required.

It does not mean you will fail 22% of the time.

It means your plan has resilience — but also sensitivity to risk.

That allows us to have practical conversations about:

  • Retiring earlier or later

  • Adjusting savings rates

  • Changing asset allocation

  • Modifying retirement spending

  • Building contingency buffers

It becomes strategy — not guesswork.

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