Your strategy made money. But if ignoring the strategy entirely and following a fixed rule made the same money, what you earned is not the strategy's — it is the market's. A null model is that control. It costs almost nothing and eliminates a large class of apparently successful strategies in one pass.
Suppose the market trended one way over some period. Then within it:
| Approach | Result |
|---|---|
| Your strategy | +2.5pp |
| No judgement at all, one fixed side | +2.5pp |
Identical. Your strategy contributed zero. It looks profitable while actually having stood on the favourable side by accident — and that favourable wind will stop, usually shortly after you size up.
A good null has three properties: uses none of your strategy's information, is simple enough to be uncontroversial, and runs on the same sample.
| Type | Tests |
|---|---|
| Fixed direction | whether you are earning a one-way market move |
| Random | whether you can beat noise at all |
| Follow the previous outcome | whether you are earning simple serial inertia |
| Mechanical selection on a public quantile | whether you are earning a structural bias anyone can see |
| Always take the current price | whether you beat "no judgement at all, just trust the price" |
How to read this tableIt is a generic menu, not my list. The three referred to below do not map onto these five rows — this site does not publish what they were.
The line I killed used three nulls, with the criterion frozen as "must beat all three" — losing to any one meant immediate death, under the verdict "the market wearing a costume".
Basisthis site does not publish what those three nulls were, because their specific form is tied to the strategy. The selection principle transfers though: choose rules that require no judgement to execute.
The commoner case is not a strategy losing to a null. It is a null exposing that the whole ruler is broken.
I rescored a full history against real market settlement. The strategy line did not move dramatically. The nulls did:
| Old ruler | Correct ruler | |
|---|---|---|
| A model-free baseline | +2.72pp | −1.23pp |
| Another baseline | −3.82pp | +0.13pp |
A baseline containing no model at all should reflect only the market itself. If changing the basis flips it from clearly positive to clearly negative, the fault cannot be in the strategy — it is in the measurement.
This is nulls' most underrated use: they are both the strategy's control and the instrument's calibration. A strategy moving is attributable to the strategy; a null moving can only be attributed to the ruler.
Full account in the broken ruler.
After fixing the ruler I retrained against the corrected target. One of the checks that the repair had worked was: contemporaneous nulls should all return to approximately zero.
They did (the contemporaneous nulls all landing between −1.27 and +0.18), while the strategy itself returned four negative cells out of four. Together those make a clean kill: it is not that a broken instrument produced ugly readings — the strategy is dead on the repaired instrument too.
The opposite error is common. My final read:
| Criterion | Result |
|---|---|
| Beat three nulls | PASS (all three) |
| Halves agree in sign | PASS |
| Gross excess ≥ 2.25pp | FAIL (+1.56pp) |
| Significance z ≥ 2.0 | FAIL (1.62) |
Beating a null only proves the strategy is not pure noise. It does not prove it covers costs. Between those two sits that line's entire $496.51.
In one simulation the hourly tenor looked positive (+4.31¢/share). Broken out: one board of six contributed +$667; the other five had a median of −$19.
The mean is meaningless. Ask for the median first, then ask what is left after removing the single best case — two questions as cheap as a null model, and they eliminate just as many false findings.
Edge is you minus the null, not you minus zero. And nulls do something extra: if the null itself changes sign, what is broken is the ruler, not the strategy. This is the cheapest check in the whole method — it costs almost nothing and can save an entire line.