Open interest is building fastest in these markets
Where leverage is entering quickest, by 24h open-interest change.
- •0G leads with n/a 24h open-interest change.
- •BABYDOGE follows at n/a.
- •8 markets covered · data as of Jun 14, 2026.
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What the Data Can and Cannot Tell Us
The dataset captured on 2026-06-14 covers eight perpetual futures markets spanning a wide range of market capitalizations and liquidity profiles. For every symbol in the set, the 24-hour and 7-day open-interest change fields return "n/a," which means a direct ranking of fastest-growing OI is not possible from this snapshot alone. What the data does provide is a clear picture of absolute open-interest levels alongside aggregated funding rates, and reading those two dimensions together still yields meaningful signals about where leveraged positioning currently stands and what directional bias the market is expressing.
This matters because the intended analytical framework — comparing OI change against funding to distinguish new longs from new shorts — requires both inputs. When OI rises alongside positive funding, the incremental leverage is typically long-side; when OI rises with negative funding, shorts are the more likely driver. With change figures unavailable here, the analysis focuses on the existing stock of open interest and the funding environment surrounding it, which remain informative in their own right.
The Scale Divide Between Major and Minor Markets
The contrast in absolute open interest across these eight symbols is striking. BTC carries $13.9B in open interest, making it the dominant market in the set by a considerable margin. ETH follows at $7.7B, and BCH registers $72.5M — already a sharp step down. Below that, the figures drop rapidly: OKB stands at $15.5M, 0G at $1.2M, MOG at $913,198, COST at $629,079, and BABYDOGE at $323,021. The gap between BTC and the smallest market in the set is several orders of magnitude.
This scale difference is relevant for interpreting leverage risk. BTC carries a leverage risk score of 35 against its $13.9B of open interest, while ETH carries a score of just 7 against $7.7B. The remaining six symbols either lack a score or show "n/a," limiting systematic comparison. What is clear is that the two largest markets by OI have quantified risk scores, and ETH's score of 7 is notably lower than BTC's 35 despite ETH carrying a substantial absolute position base.
Funding as a Directional Signal
Funding rates vary considerably across the dataset. ETH posts an aggregated funding APR of 3.23%, and its 90-day funding percentile sits at 54, meaning the current rate is near the historical midpoint for that market over the prior 90 days — not stretched in either direction. BCH shows an APR of 5.26% without a 90-day percentile for context, and both MOG and BABYDOGE register 5.47%, the highest positive rates in the set. Positive funding of this magnitude indicates that perpetual contracts are trading at a premium to the index, and long holders are paying shorts to maintain their positions — a structural condition more consistent with net long leverage than net short.
On the other side, BTC's aggregated funding APR is -0.67%, placing it at the 24th percentile of its 90-day range. A negative funding rate means shorts are paying longs, and a 24th-percentile reading suggests this is a relatively unusual condition for BTC relative to recent history. OKB also carries negative funding at -0.38%, and 0G sits at -0.25%. COST registers exactly 0.00%. Negative or flat rates, particularly at low historical percentiles, can indicate that short positioning is elevated or that bullish momentum has faded in those markets.
BTC Funding Context and the Percentile Framework
The 90-day percentile data is only available for BTC and ETH, which limits how precisely the funding environment can be contextualized for the remaining six symbols. For BTC, a funding APR of -0.67% at the 24th percentile is a meaningful observation: three-quarters of daily observations over the prior 90 days recorded a higher (more positive) funding rate than the current reading. This suggests that the current funding environment for BTC is on the bearish end of its recent distribution, which when read alongside the $13.9B in open interest implies a sizable stock of leveraged positions in a market where short or hedged positioning appears to be relatively elevated.
ETH's 54th-percentile reading at 3.23% APR sits almost exactly at the median of its 90-day range, offering a more neutral reading. The $7.7B in open interest combined with a leverage risk score of 7 and a mid-range funding rate suggests that ETH's current positioning is neither particularly stretched to the long side nor under obvious short pressure by recent standards.
Liquidation Imbalance Across the Set
Every symbol in the dataset records a liquidation imbalance of +0.00. This uniform reading means that, at the time of the snapshot, there is no measurable skew between long and short liquidations pending in any of these markets. A perfectly neutral liquidation imbalance does not imply an absence of risk, but it does indicate that neither side carries a disproportionate cluster of liquidation levels that could amplify price moves in one direction. Combined with the funding and OI data, it rounds out a picture where the primary differentiation between these markets lies in size, funding polarity, and the limited risk scores available for BTC and ETH rather than in any acute liquidation overhang.
How to read this
| Funding APR | Annualized, OI-weighted funding. Positive = longs pay shorts (crowded longs). |
| Percentile 90d | Where current funding sits within the coin's own last 90 days (0–100). |
| Open interest | Total USD value of outstanding perpetual contracts. |
| OI change 24h / 7d | How fast leverage is entering (+) or unwinding (−) over the period. |
| Liquidation skew | Imbalance of forced closures (−1…1): + = more longs liquidated, − = more shorts. |
| Leverage risk | 0–100 composite of funding extremity, OI momentum, liquidations and volatility. |
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Get the brief on Telegram →This report is generated from Quantority's database; the figures are read from the data and the commentary is automated. Descriptive, not predictive, and not financial advice.