Methodology & Help

What Is the Percentile?

The futures market is not one monolithic crowd — it's a colosseum of distinct players, each with completely different motivations, time horizons, and risk tolerances. Every week, the CFTC forces them to show their cards. That disclosure is the Commitments of Traders (COT) report — and learning to read it is like being handed a map of where the armies are positioned before the battle begins.

Where the Data Comes From

Every Tuesday at close of business, large institutional traders are required to report their futures positions to the CFTC — but only if they breach a minimum size threshold. Small traders don't make the cut. The CFTC then verifies and publishes this data every Friday at 3:30 PM ET, giving the world a weekly X-ray of exactly how many contracts each category of player holds net long or net short. By the time you read it Friday afternoon, the data is already 3 days old — a known quirk professionals simply factor in.

The Four Players in the Colosseum

The COT report breaks down the market into four main categories of traders:

• Commercials: These are the hedgers — the real-world businesses with actual physical exposure to the commodity. Gold miners, oil refineries, wheat farmers, airline companies. They use futures not to speculate but to lock in prices and protect their business. A gold miner selling futures is saying: "I don't care where gold goes — I just need to guarantee my production price." Commercials are almost always net short in commodity markets, because they're selling forward production. They are considered the "smart money" on fundamentals — they know their industry better than anyone.
• Managed Money: (also called Non-Commercial or Speculators) is the category that traders care about most. These are the hedge funds, CTAs (computer-driven trend-following algorithms), and large asset managers who have zero physical exposure to the commodity. They own no gold mine, no oil refinery, no wheat field. They are purely in the market to profit from price movement. They chase trends, pile into momentum, and capitulate in herds — which is exactly what makes their positioning data so powerful as a contrarian signal. When they're at the 90th percentile long, the trade is crowded. When they're at the 2nd percentile, they've given up — and the spring is coiled.
• Non-Reportables: are the small traders — retail participants and small funds whose positions fall below the CFTC's minimum reporting threshold. The CFTC simply calculates their aggregate position by subtracting Commercials and Managed Money from the total open interest. They're the background noise of the market — relevant in aggregate, invisible individually. Professionals largely ignore this category for signal purposes.
• Swap Dealers: (in the disaggregated COT report) are large financial institutions — investment banks, JPMorgan, Goldman Sachs — that act as intermediaries. They sell commodity exposure to their clients (pension funds, endowments) via swaps and then hedge that exposure in the futures market. Their positioning reflects client demand rather than their own directional view, making them a complex and often misread category.

What the Percentile Tells You

The percentile is what you build from this data over time. Take 105 consecutive Tuesday snapshots (~2 years), calculate the net position for Managed Money each week (longs minus shorts), and sort all 105 readings from smallest to largest. Where today's reading lands in that sorted list — that's your percentile. Hit the 2nd percentile? Speculators are nearly as bearish as they've been in 2 years. Hit the 90th? They're nearly as bullish as they've been in 2 years. Simple, powerful, and endlessly useful.

What Does “Washed Out” Mean?

When a percentile is very low (roughly below the 10th percentile), traders say positioning is washed out. It means Managed Money have exited almost all of their long positions — the trade is abandoned, the crowd has given up. This is a contrarian signal: historically, when everyone has already sold, there is very little selling pressure left. The path of least resistance flips to the upside. A washed-out reading doesn’t guarantee a rally, but it tells you the crowding risk is minimal and the asymmetry favours the long side.

105-Week vs 52-Week Percentile

Why 105 Weeks (2 Years) Is the Standard

The 2-year window is the most common COT lookback for one core reason: it captures a full macro cycle — typically one tightening phase and one easing phase, one risk-on and one risk-off period. It gives you enough data points (105 observations) for the statistics to be meaningful. A Z-score and percentile calculated on fewer than ~52 points becomes statistically fragile.

The Case FOR Adding a 1-Year (52-Week) Column

1. Regime Sensitivity

Markets change regimes. The 2-year window might include a completely different macro environment that distorts the reference point. If 2024 was a dollar bull market and 2025–2026 is a dollar bear market, including 2024 COT data in your percentile calculation anchors your baseline to a regime that no longer exists.

2. Momentum Context

A 1-year percentile tells you something the 2-year doesn’t: where positioning stands within the current trending environment. If speculators have been building gold longs all year and are at the 80th percentile of the last 52 weeks, but only the 60th percentile of 2 years — the 1-year number better reflects how stretched the current crowd is.

3. A Tale of Two Signals

When the two percentiles agree → very high conviction signal. When they diverge → a regime shift is likely underway, and you need to investigate which baseline is more relevant.

The Case AGAINST Replacing 2 Years With 1 Year

1. Statistical Fragility

52 data points is the bare minimum for a meaningful percentile distribution. Small sample sizes mean one or two outlier weeks can dramatically distort the percentile. With 105 weeks, a single extreme reading smooths out. With 52 weeks, it dominates.

2. Loses the Full-Cycle Anchor

The whole point of a COT percentile is to know when positioning is historically extreme. If your window is only 52 weeks, you might miss that today’s “extreme” is actually quite normal in a longer context. Gold at the 2nd percentile of 105 weeks is a much stronger signal than the 2nd percentile of just 52 weeks — because the longer window has seen more full market cycles.

3. Recency Bias Trap

A 1-year window tends to normalize recent extremes. If the last 12 months were unusually bullish (like gold in 2025), the 1-year percentile recalibrates its “normal” upward — making current levels look moderate when they’re actually stretched on a full-cycle basis. This is exactly the kind of recency bias that causes traders to be bullish at tops.

The Professional Solution: Use Both as a “Percentile Pair”

The institutional standard is not to replace 2 years with 1 year — it’s to run both and compare them. The divergence between the two is itself a signal.

The last two rows are the most interesting and most actionable, because they reveal transition states that a single window would completely miss.

What Is the Z-Score?

What It Measures

The Z-Score is a statistical measure that tells you how many standard deviations the current reading is away from the historical average. It answers a simple question: how unusual is this reading relative to the last 105 weeks?

How to Read the Scale

• Z = 0: Normal, right at the average.
• Z = +1 or -1: Unusual but not rare (about 16 percent of readings).
• Z = +2 or -2: Very rare (about 2.5 percent of readings).
• Z = +3 or -3: Extreme outlier, historically almost never happens.

Why Z-Score Beats Raw Numbers

Raw contract counts are meaningless without context. If funds hold 160,000 contracts, you do not know if that is high or low. The Z-Score tells you instantly how extreme that reading is relative to a full cycle of history.

What Is Crowd Risk?

What It Measures

Crowd Risk is the trading risk that emerges from everyone being on the same side of a trade. It answers the question: if the market moves against the crowd, how violent will the exit be? It is derived from the percentile and Z-Score together. High percentile plus high Z-Score means a crowded trade. Low percentile plus negative Z-Score means the crowd has already left.

The Washed-Out Trade

Now imagine Gold at the 2nd percentile. The crowd has already left. If positive news hits, funds rush back in, but there is little overhead supply. The price can rip higher because the crowd has to buy back from almost nothing. That is a washout reversal and is why extremely low crowding can be asymmetrically bullish.

Summary Table

The key insight: percentile and Z-Score measure the size of the crowd. Crowd Risk measures the consequence of the crowd being wrong. High percentile plus high Z-Score means the trade is fragile, not strong.