Direct answer
A monthly report records the rates a month actually produced, not a forecast: check the data is complete, then report the median, mean, 10th and 90th percentiles, extremes, the share of positive and negative intervals and the longest same-sign run, and convert them into holding costs for a 10,000 USDT position. An exchange with incomplete data keeps its data but gets no comparative conclusion.
Check completeness first
For BTC, ETH and SOL settlement records on Binance and OKX, work out how many settlements the period should contain and compare them with the records retrieved, finding gaps and the longest interval. Do not compare averages when the data is incomplete.
Settlement records come from both exchanges' published funding histories — the rate actually charged at each interval — and each keeps its exchange, contract, settlement time, rate and source address. The predicted rate that moves through an interval is not fit for a monthly report, because nobody actually paid it.
Core metrics
Report median, mean, 10th and 90th percentile, maximum positive, minimum negative, positive/negative interval share and longest same-sign run for each market.
Median describes a typical state while quantiles and extremes reveal tails. A monthly mean can hide a few spikes among many near-zero intervals. Cross-exchange differences require observations from aligned windows.
Report field specification
A monthly review that others can check needs its fields fixed in advance. The table lists what every market and exchange should produce, and what question each field answers. A missing field is worse than an unflattering number, because the reader cannot judge how far the conclusion extends.
The first three rows are data-quality fields and belong above the statistics. When the data is incomplete, every average and percentile below them describes an incomplete sample and cannot carry a cross-exchange comparison.
| Field | Question it answers |
|---|---|
| Settlements expected vs records retrieved | Is the sample complete |
| Longest interval | Are gaps scattered or concentrated |
| Whether the interval changed | Did the exchange change its settlement frequency mid-month |
| Median | The typical state |
| Mean | The overall level once outliers count |
| 10th / 90th percentile | The bounds of the normal range |
| Largest positive / smallest negative | Tail strength |
| Share of positive intervals | Directional skew |
| Longest same-sign run | Whether the skew persists |
The step-by-step procedure
Write the review as a repeatable procedure rather than a one-off analysis. Run these seven steps in the same order each month, and when a step fails, stop there and record why instead of skipping ahead to a conclusion.
The constraint in step seven is the one most often dropped. The review describes observed data, not next month's expectation. The moment it starts saying 'will' or 'is expected to', it has become a forecast, and forecasts need an entirely different standard of validation.
- One: fix the period and time zone, and record when the data was retrieved.
- Two: compare expected and retrieved settlements per market and exchange, marking anything incomplete as not comparable.
- Three: compute median, mean, 10th/90th percentiles and extremes separately.
- Four: count the share of positive and negative intervals and the longest same-sign run.
- Five: convert the median, the 90th percentile and the actual interval series into funding amounts on a fixed 10,000 USDT position.
- Six: list every official source address with the date the data was retrieved.
- Seven: describe only observed data, publish no directional forecast, and link back to the funding calculator so readers can recompute on their own position.
Convert observations to holding scenarios
For a fixed 10,000 USDT position, convert the monthly median, 90th percentile and actual interval series into funding cost. The series is closest to a historical ledger; fixed quantiles support stress testing.
State direction clearly: positive funding means longs pay and shorts receive, with the reverse for negative. When frequency changes, count actual intervals instead of assuming three per day.
Publication rules
Attach the period covered, when the data was retrieved, notes on any gaps and the official sources. If either exchange's data is incomplete, retain it but withhold a comparative conclusion.
Describe observed data only; do not claim next month will rise or a token is best to long. Link back to the calculator so readers can apply their own position.
Read the September 2026 report written this wayOfficial sources and calculation boundary
OKX's funding FAQ defines what the report is counting, and the data are both exchanges' published funding histories, which anyone can recompute for the same period. This article offers a method rather than a conclusion. The thing most worth checking is therefore not any single figure, but whether your data is complete enough to carry a comparison at all.
Open the matching calculatorNext checks in this series
Frequently asked questions
Why not rank annualized funding?
Annualizing extends one period's rates over a whole year, which assumes they persist; it misleads easily. The monthly report shows the actual distribution of intervals first.
Can the monthly average predict next month?
No. It only describes the observed window; market structure and settlement rules can change.
Why emphasise the median over the mean?
Because funding distributions are usually spiky. A handful of extreme intervals can lift a monthly mean while most of the period sits close to zero. The median describes the typical state and the mean describes the level once tails count; both are needed. Reporting only a mean invites readers to misjudge ordinary holding cost.
How complete must the data be for a cross-exchange comparison?
There is no universal threshold, but it should be defined and published in advance. The point is to fix it before seeing the results, otherwise it becomes sample selection. Below the threshold, keep the data, mark it not comparable, and draw no conclusion — which is far more honest than adjusting the threshold afterwards.