# Does COT positioning predict reversals? > Crowded positioning extremes precede fewer liquidations, not more. The interval excludes zero, p = 0.0066, and the sign is backwards. - Canonical: https://hadalinstruments.com/research/does-cot-positioning-predict-reversals/ - Published: 2026-08-23 - Author: Hadal Research - Answers the question: "does cot positioning predict reversals" - Coins the term: **Wrong-Way Significance** — An effect whose confidence interval excludes zero and whose sign contradicts the hypothesis it was registered to test — statistically real, and evidence against the belief rather than for it. --- No. On my data the relationship runs the other way, and the interesting part is that it runs the other way *significantly*. The AUD leg returned a trigger effect of **−0.0477**, bootstrap interval **[−0.0801, −0.0137]**, **p = 0.0066**. The interval excludes zero. The sign says crowded positioning extremes were followed by liquidation events at **3.1%** against the mid-range controls — less often, not more. I call that shape **Wrong-Way Significance**: an effect that clears every bar a reader checks and points at the opposite of the hypothesis it was registered to test. ## Why this is the first thing I publish with its data attached Every measurement on this site is held to three standards: the methodology is pre-registered before the first tick, the artifacts are content-hashed, and the results are recomputable. This is the first page where all three are true at once, which is why it goes first rather than something with a better headline. **Pre-registered, and the ordering is provable rather than asserted.** The registration records that at the moment it was written the positioning data had never been contacted — the directory did not exist, and the single prior fetch attempt had returned an HTTP 503 and written nothing. The fetch log agrees: every attempt on that date failed. So the hypothesis, its thresholds, its horizon grid and its decision tree were fixed at a point when looking was not possible. That matters more than it sounds. A pre-registration is worth exactly the provability of its ordering, and most are worth nothing on that test. **Content-hashed.** The dataset below carries nineteen input hashes, one per source CSV, and every one of those CSVs is committed. The compute step opens no socket. **Recomputable — and this was measured rather than assumed.** The claim most sites would make here is "you could re-derive this". I re-ran the driver into a clean temporary directory and compared the output field by field against the published artifact: **fourteen of fourteen result keys byte-identical, none differing.** So you can download the file, check its hash against the one published here, and re-derive it from the committed inputs — and I have already done that myself and reported what came back. Nothing in the chain asks you to trust me. ## What was actually measured Seven currency books, **201 aligned weekly release stamps**, latest 2026-06-30, drawn from the CFTC's Traders-in-Financial-Futures report. Leveraged-fund net positioning is joined to each leg's weekly price and keyed to the Friday release stamp, giving **821 release-keyed weekly observations per leg** after the 2010 price join. The frozen defaults: a 156-week percentile window, a 2× range threshold, deciles at 0.9 and 0.1, horizons of 2, 4 and 6 weeks, a 1,000-iteration block-bootstrap surrogate, four folds. The surrogate deserves its own line, because it is where most tests of this kind are weakest. It resamples the weekly *changes* in a stationary block bootstrap, relabels the extremes on the surrogate while holding the real outcomes fixed, and re-runs the test. An independent-and-identically-distributed shuffle would have been easier and would have been anti-conservative — positioning is autocorrelated, and destroying that structure inflates significance. I had learned that on an earlier hypothesis and wrote the harder surrogate into this registration before running it. ## The result, leg by leg **AUD: not live.** Effect −0.0477, interval [−0.0801, −0.0137], p = 0.0066, and it **fails the relabel surrogate**. Windowing is durable. The NZD leg was registered as a uniformity control rather than a target, and the AUD effect survives it — the difference between the two legs is −0.092, so what is being seen is AUD-specific rather than generic antipodean risk flow. **JPY: a preliminary unconditioned null.** Effect +0.0442, interval [−0.0152, +0.1131], p = 0.18. This is the *unconditioned* result, and the registered verdict for JPY requires an intervention-and-rate regime split whose feed does not exist yet. So it is reported as preliminary and not as a finding, which is the state it is actually in. **Verdict, from the tree written in advance:** the single-leg positioning fuel gauge does not carry the crowding-to-liquidation signal. That was the outcome the registration declared it expected, which is the least exciting way for a pre-registered test to resolve and the most credible. ## What this does not establish The null gates rather than kills. The registered thesis is a **conjunction** — crowding *and* dealer positioning *and* thin liquidity — and this measures the first term alone. A null here means Layer 1 does not on its own justify the spend on Layers 2 and 3. It does not mean the conjunction is refuted, and I would have had to say that either way, because the tree deciding it was fixed first. The JPY leg is preliminary for the reason above. The AUD result is one currency on one weekly cadence. And positioning data is a weekly position snapshot, not a price series — the artifact says so on its own face, in the banner it ships with. ## The download The measurement is the file, not this page. Its hash is published beside it; if your copy hashes differently, one of me has a problem worth knowing about. If you recompute it and disagree with me, send the recomputation. A correction with a receipt attached gets published as a correction, with the original left legible beside it. ## The artifact - SHA256: 5dd9ef789a81d9889935189729a666ccdbef7ae4faf6d3d4f264f25bc577760a - Download: https://hadalinstruments.com/data/cot-leveraged-funds.json - Measurement technique: CFTC Traders-in-Financial-Futures Futures-Only leveraged-fund long/short, re-read from committed CSVs with no network access at compute time; seven currency books aligned to 201 weekly release stamps. --- ## Claims examined ### Claim 01 — canonical: https://hadalinstruments.com/refutations/#claim-89e77e34 > "When the leveraged funds are all on one side, the reversal is coming." — our reading: False The AUD leg returned a trigger effect of −0.0477 with a bootstrap interval of [−0.0801, −0.0137] and p = 0.0066. That interval excludes zero, which is normally where a reader stops. The sign is the problem: it is negative, meaning crowded extremes were followed by liquidation at 3.1% against the mid-range controls rather than more often. It then failed the block-bootstrap relabel surrogate that was frozen before the run, so it is not a live signal in either direction. A significant effect pointing the wrong way is not a weak version of the belief. It is evidence against it. **What is true:** Measured against matched controls on eight hundred and twenty-one weekly observations per leg, crowded leveraged-fund extremes are followed by a lower rate of liquidation events than mid-range positioning is, and the effect does not survive its own pre-registered surrogate. Evidence: https://hadalinstruments.com/research/does-cot-positioning-predict-reversals/#claim-89e77e34 ### Claim 02 — canonical: https://hadalinstruments.com/refutations/#claim-393e90f4 > "You just didn't have enough data." — our reading: Unproven The objection is fair against most nulls and weak here, because the parameters could not have been tuned to produce this outcome — they were frozen before the data existed. The defaults were a 156-week percentile, a 2× range threshold, deciles at 0.9 and 0.1, a horizon grid of 2/4/6 weeks, a 1,000-iteration block-bootstrap surrogate and four folds. What the sample size does bound is the JPY leg, whose registered verdict needs an intervention-and-rate regime split that has no feed yet — so JPY is reported as a preliminary unconditioned null rather than as a finding. **What is true:** The run used every release-keyed weekly observation available after the 2010 price join — eight hundred and twenty-one per leg across seven currency books and two hundred and one aligned weeks — with the percentile window, threshold, horizon grid and fold count all fixed before the data was fetched. Evidence: https://hadalinstruments.com/research/does-cot-positioning-predict-reversals/#claim-393e90f4 ### Claim 03 — canonical: https://hadalinstruments.com/refutations/#claim-d6615f4e > "So the whole positioning thesis is dead." — our reading: False The registered thesis is a conjunction — crowding, dealer positioning and thin liquidity together — and this measures the first of those alone. My own verdict language is that it gates rather than kills: Layer 1 on its own does not justify the spend on Layers 2 and 3. Reading a one-layer null as a three-layer refutation would be the same error as reading a one-layer hit as confirmation, and I would have had to say so either way, because the tree that decides it was written down first. **What is true:** This tests one layer of a three-layer claim, and the pre-registered decision tree says so: a null on the single-leg fuel gauge gates further spending on the other two layers rather than refuting the conjunction they are supposed to form. Evidence: https://hadalinstruments.com/research/does-cot-positioning-predict-reversals/#claim-d6615f4e ## Cite This Article APA BibTeX HTML Hadal Research. (2026). Does COT positioning predict reversals?. Hadal Research. https://hadalinstruments.com/research/does-cot-positioning-predict-reversals/ (SHA-256: 5dd9ef789a81d9889935189729a666ccdbef7ae4faf6d3d4f264f25bc577760a) Version 5762f56, 2026-08-29. @misc{hadal_2026_does-cot-positioning-predict-reversals, author = {Hadal Research}, title = {Does COT positioning predict reversals?}, year = {2026}, url = {https://hadalinstruments.com/research/does-cot-positioning-predict-reversals/}, howpublished = {Hadal Research}, version = {5762f56}, note = {Published: 2026-08-23; version dated 2026-08-29, Data Hash (SHA-256): 5dd9ef789a81d9889935189729a666ccdbef7ae4faf6d3d4f264f25bc577760a} } Source: Hadal Research, Does COT positioning predict reversals? (Hash: 5dd9ef789a81d9889935189729a666ccdbef7ae4faf6d3d4f264f25bc577760a). Original Research Copy Citation **Version 5762f56** identifies the commit that last changed this page in Hadal's content repository. That repository is not public, so the identifier does not resolve externally — it is published so a citation pins one specific state rather than a moving page. To obtain the exact version cited, use the [press and research route](https://hadalinstruments.com/press/). ## Explore further ### Instruments - [Epistemic Harness](https://hadalinstruments.com/instruments/epistemic-harness/) - [Overfit Auditor](https://hadalinstruments.com/instruments/overfit-auditor/) - [Positioning / COT Intelligence](https://hadalinstruments.com/instruments/positioning-cot-intelligence/) - [Reproducible Verdict Kernel](https://hadalinstruments.com/instruments/reproducible-verdict-kernel/) ### Concepts - [Data Snooping](https://hadalinstruments.com/glossary/data-snooping/) - [Effective Sample Size](https://hadalinstruments.com/glossary/effective-sample-size/) - [Kill Ledger](https://hadalinstruments.com/glossary/kill-ledger/) - [Pre-Registration](https://hadalinstruments.com/glossary/pre-registration/) - [Regime Shift](https://hadalinstruments.com/glossary/regime-shift/) ### Research - [The break that cleared neither bar](https://hadalinstruments.com/research/the-break-that-cleared-neither-bar/) Asked as: how do you know a detected regime change is real - [Is my volatility regime just telling me the time?](https://hadalinstruments.com/research/is-my-volatility-regime-just-telling-me-the-time/) Asked as: is my volatility indicator just measuring time of day - [How do you verify a trading track record?](https://hadalinstruments.com/research/how-do-you-verify-a-trading-track-record/) Asked as: how do you verify a trading track record [All Hadal research](https://hadalinstruments.com/research/)[This article as plain markdown](https://hadalinstruments.com/research/does-cot-positioning-predict-reversals.md) --- ## Raw artifact — PUBLISHED The figures on this page recompute from the file below. It is the measurement's own output, content-hashed, so you can verify that what you downloaded is what was measured — and that it has not changed since. sha256 5dd9ef789a81d9889935189729a666ccdbef7ae4faf6d3d4f264f25bc577760a [Download the artifact](https://hadalinstruments.com/data/cot-leveraged-funds.json)