Free during alpha
Generates ETF mixes. Tested. Ranked. With Rigour.
Mathematical optimization, historical validation, simulations and analysis for hypothetical allocations. Uses published academic research,‡ FRED research and data documentation§, and CFA Institute model-validation guidance**.
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Free Steady Otter vs. ~$250k to ask AI to do this
| Steady Otter | Do it yourself with AI |
|---|---|
| Free† | ~$250k* for a single run |
|
GPU calculations with CPU preparation Work and runtime depend on run settings Historical checks and conditional simulations. |
Without code execution Lacks our executable validation checks. An equivalent, trusted, deterministic result is not guaranteed. |
† Alpha pricing [click to expand] [click to collapse]
† Free during Alpha. Suggested pricing afterwards: $10 for a quick run, up to $100 for a maximally thorough run, on a sliding scale.
* AI cost estimate [click to expand] [click to collapse]
* AI cost estimate: OpenAI Astra Max with access to source code, based on published rates as of Oct 10, 2026.
‡ Academic research [click to expand] [click to collapse]
Published research informs the methods and their limitations. It does not calibrate the engine’s policy thresholds or establish future performance. Linked methodology notes identify each source and its scope.
§ FRED research references [click to expand] [click to collapse]
FRED Blog, FRED and ALFRED documentation supply research context. Their inclusion in the reference library does not mean economic-series observations enter portfolio calculations; those use captured market returns, prices and volume.
** CFA Institute guidance [click to expand] [click to collapse]
Joseph Simonian (2024), Investment Model Validation: A Guide for Practitioners, CFA Institute Research Foundation. The methodology notes link the source and explain its applicability.