Why We Built This Feature
We created this feature after discussions with our subscribers, who raised an important point: most market assumptions are provided as arithmetic averages, but these don’t always give the most realistic projections.
Before explaining our approach, here’s a quick recap of the two types of averages:
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Arithmetic mean – the simple average most of us know: add up the values and divide by the number of inputs.
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Geometric mean – accounts for compounding over time, providing a more realistic picture of long-term growth.
If you’d like a deeper dive into the difference, the following resources explain it well:
What We Learned from Advisers
In conversations with other advisers, we came to two main conclusions:
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Standard projections – Using geometric averages leads to better, more realistic results. Arithmetic averages tend to skew projections upward.
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Monte Carlo simulations – Arithmetic averages are more appropriate here.
Since most of the market data our subscribers provide is likely arithmetic averages, we decided to add an option that approximates the geometric mean from arithmetic inputs. This improves the realism of our standard cash-flow projections while leaving Monte Carlo simulations unchanged.
A Simple Analogy
Imagine you invest $100 in a stock that grows 20% one year but loses 10% the next year.
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Arithmetic average: (20% - 10%) ÷ 2 = 5%
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Geometric average: Accounts for compounding: $100 × 1.2 × 0.9 = $108 → an effective annual growth of ~3.9%
Even though the arithmetic average says 5%, the real growth over time is closer to 3.9%. This is why geometric averages give a more realistic picture for projections.
Why It Matters
From our discussions with other advisers, we learned:
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For standard cash-flow projections, geometric averages give a more accurate view. Arithmetic averages tend to skew results upward.
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For Monte Carlo simulations, arithmetic averages remain appropriate.
Since most subscriber data is likely arithmetic-based, this feature allows standard projections to reflect more realistic growth while leaving Monte Carlo simulations unchanged.
Recommendation
When updating your market assumptions, we generally recommend enabling this feature. Unless you have reason to believe otherwise, your assumptions are most likely arithmetic mean values, and this adjustment will give your projections a more realistic basis.