How leveraged are whales compared with shrimp over time?

GET /v1/hl-cohorts/segments/{cohort}/history with include=leverage answers it, one call per cohort. Every hourly row of the cohort's book, summed over every coin, gains three ratios: equity_exposure = (long + short) / equity, the cohort's gross leverage on its own account value; perp_bias = (long - short) / equity, its net lean; and equity_covered_share, the share of the cohort's notional those two describe. Call it for whale and for shrimp and set equity_exposure side by side. The full parameter list is on Cohort history.

Quick answer

The same 90 days for both cohorts; a label with a space goes in the path as its slug, such as 4x_whale.

# the whale cohort's hourly leverage over the last 90 days
curl -H "X-API-Key: $VIKE_API_KEY" \
  "https://data.vike.io/v1/hl-cohorts/segments/whale/history?axis=size&include=leverage&hours=2160"

# the shrimp cohort's hourly leverage over the same 90 days
curl -H "X-API-Key: $VIKE_API_KEY" \
  "https://data.vike.io/v1/hl-cohorts/segments/shrimp/history?axis=size&include=leverage&hours=2160"

Example response

Captured from the live API on 2026-10-24 at 17:19 UTC from the whale call, trimmed to 3 rows of 2,160. At 14:00 whales held 5.5x their equity in notional, net long 0.84x of it, and the ratios covered all of their notional (equity_covered_share 1.0). The shrimp call for the same hour read equity_exposure 6.99 and perp_bias 3.92, but with equity_covered_share 0.36: the shrimp figures describe about a third of that cohort's book. The two newest hours are null, and so is every hour before 2026-08-11 at the far end of the 90 days.

{
  "axis": "size",
  "cohort": "whale",
  "label_basis": "point_in_time",
  "data_from": "2026-04-07T00:00:00+00:00",
  "series": [
    {
      "ts": "2026-10-24T16:00:00+00:00",
      "long_usd": 1143017679.0,
      "short_usd": 857120938.1,
      "bias": 0.142938,
      "position_count": 3652,
      "perp_bias": null,
      "equity_exposure": null,
      "equity_covered_share": null
    },
    {
      "ts": "2026-10-24T15:00:00+00:00",
      "long_usd": 1249898790.0,
      "short_usd": 858615733.3,
      "bias": 0.185573,
      "position_count": 3656,
      "perp_bias": null,
      "equity_exposure": null,
      "equity_covered_share": null
    },
    {
      "ts": "2026-10-24T14:00:00+00:00",
      "long_usd": 1120856833.0,
      "short_usd": 846694223.2,
      "bias": 0.139342,
      "position_count": 3649,
      "perp_bias": 0.8407736521,
      "equity_exposure": 5.540563772,
      "equity_covered_share": 1.0
    }
  ],
  "has_more": false,
  "leverage": {
    "data_from": "2026-08-11T00:00:00+00:00",
    "scope": "native perp account only; main-dex positions of wallets with a known positive native equity",
    "note": "hours rebuilt from fills are null"
  }
}

Variations

The largest accounts. 4x whale is accounts of $10m and up. A capture on 2026-10-24 at 17:13 UTC read its 16:00 hour at 3.72x its equity in positions (equity_exposure) and net short 2.53x its equity (perp_bias).

# hourly leverage of the $10m-and-up accounts beside their long and short notional
curl -H "X-API-Key: $VIKE_API_KEY" \
  "https://data.vike.io/v1/hl-cohorts/segments/4x_whale/history?axis=size&include=leverage"

The next rung up from shrimp. 2x shrimp is accounts of $1,000 to $10,000.

# the 2x shrimp cohort's hourly leverage since leverage data begins
curl -H "X-API-Key: $VIKE_API_KEY" \
  "https://data.vike.io/v1/hl-cohorts/segments/2x_shrimp/history?axis=size&include=leverage&start=2026-08-11T00:00:00Z"

By profitability. axis=pnl works the same way, with each hour's cohort label as it was then.

# a month of hourly leverage for the top 1% by realized PnL
curl -H "X-API-Key: $VIKE_API_KEY" \
  "https://data.vike.io/v1/hl-cohorts/segments/3x_smart/history?axis=pnl&hours=720&include=leverage"

Right now. The cohort summary carries the same three ratios at the newest 5-minute snapshot, plus exposure_ratio, notional over margin used.

# current leverage of the whale cohort
curl -s -H "X-API-Key: $VIKE_API_KEY" \
  "https://data.vike.io/v1/hl-cohorts/segments/whale/summary?axis=size" \
  | jq '{snapshot_ts, equity_exposure, perp_bias, exposure_ratio, equity_covered_share}'

Before you rely on it

Ask your agent

Connected to the Vike MCP server (https://vike.io/mcp) in Claude, ChatGPT or Cursor, ask it in plain words. The hl_segments tool answers (view history), at 1 credit a call.

Plot Hyperliquid whales' and shrimp's notional-to-equity ratio per hour since August 11

Related

• Did cohort leverage rise before the last liquidation cascade?
• Is notional bias or equity-adjusted bias the better signal?
• What one cohort holds right now
• Which Hyperliquid whales are over-leveraged against their own account value?