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Hyperliquid Screener · Crowded Longs

Crowded Longs Screener for Hyperliquid

Crowding has two parts — how much is at stake and which side is paying. This screen combines them: open interest large relative to daily volume, and funding positive enough that longs are paying to stay in. Those are the positions with the least room to exit.

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By Keel Research Team · Updated May 12, 2026
How it works

Crowded Longs methodology

The Crowded Longs screen measures two things and requires both. X-axis: OI turnover — open interest in dollars divided by 24-hour dollar volume, which reads as the number of days of current volume it would take to turn the whole open position over. Because it is a ratio, it is scale-free: unlike raw open interest, it does not simply rank the largest coins first, and a mid-cap carrying a parked book can outrank BTC on it. Top quartile is the filter. Y-axis: funding percentile, top quartile — longs are paying shorts, so the crowd is on the long side and paying for the privilege. Z-axis: last-bar return, mapped to colour at a median marker, a soft read rather than a hard gate. The risk read is the point. A large position sitting on thin turnover has few natural counterparties to exit into, so when it unwinds, price travels further than the size alone suggests. This is a risk screen, not an entry signal: crowding can persist for weeks and says nothing about timing.

Run the screen

Live Crowded Longs cohort

The screen below is pre-loaded with the Crowded Longs preset. Adjust signals, thresholds, and timeframe inline — your changes update the cohort in real time. Share or backtest the resulting state directly from the toolbar.

Automate it

Trade this screen systematically on Keel

Keel is a Strategy OS for AI-assisted systematic trading on Hyperliquid. Backtest a strategy that uses the Crowded Longs signals as entry filters, optimize parameters across thousands of variants, then deploy live with funding-aware execution and full risk controls.

Free to start — connect a Hyperliquid wallet when you’re ready to go live.

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What you can do
  • Backtest any strategy built from the Crowded Longs signals with realistic fees, slippage, and funding modeled.
  • Optimize across parameter grids — Sharpe, drawdown, hit rate, funding regime.
  • Deploy live to Hyperliquid with stop-loss, position limits, and funding-aware execution.
  • Iterate with AI — describe a thesis, let the strategy compiler turn it into a tradeable pipeline.
FAQ

Crowded Longs questions

What does "crowded" mean for a perpetual?

Crowded means a lot of position sits on one side relative to the market’s ability to absorb it leaving. Two numbers say that together: how large the open position is against daily turnover, and which side is paying funding to keep it on. Either alone is incomplete — a big position in a heavily traded name exits easily, and a funding rate tells you the direction of the lean but nothing about its size.

How is OI turnover calculated?

Open interest in dollars divided by 24-hour dollar volume. Hyperliquid reports open interest in coins, so it is multiplied by price to get the dollar figure; the denominator is the same 24-hour dollar volume that defines the top-100 universe. Both sides are dollars, so the ratio is dimensionless and reads as days — a value of 2 means the open position is twice a day’s volume, so at the current pace it would take about two days of trading to turn it over. The axis ranks the percentile rather than the raw ratio, because the raw ratio has a long right tail that a single illiquid name would otherwise own.

Why not just rank by open interest?

Because it would return the same names every hour. Open interest in dollars scales with the size of the market, so BTC and ETH sit permanently at the top of that list and it tells you nothing you did not already know. Turnover divides the size out and asks a different question: how large is the position relative to the flow available to unwind it. That is the question crowding actually turns on, and a mid-cap can rank above BTC on it.

How often does the screen refresh?

Market data refreshes hourly. The screen recomputes percentile rankings, thresholds, and qualifying cohorts on each refresh. Funding rates update on the same hourly cadence as Hyperliquid’s native funding settlement.

Does crowding predict a reversal?

No. Crowding sizes the consequence of an unwind; it does not time it. A perp can carry high turnover and positive funding for weeks while price grinds higher, and the crowd is not wrong until it is. Treat this screen the way you would treat a position-sizing input — it tells you which names will move disproportionately when they do turn — rather than as an entry or exit trigger.

Can I backtest a crowded positioning strategy on Keel?

Yes. Open the screen, click "Backtest in Keel," and the current state — signals, thresholds, universe, timeframe — passes into a Keel workspace. From there, you can run a full backtest with realistic fees, slippage, and funding modeled, then optimize and deploy live.

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