Hyperliquid Long/Short Ratio: Read Trader Positioning (2026)

The short version: on Hyperliquid, like on any perp exchange, every long is matched by a short, so the market-wide long/short ratio in dollars is always exactly 1. A long/short ratio only tells you something when you measure a group of traders. In our snapshot of 31 October 2026 (08:15 UTC), the 100 wallets with the highest monthly PnL on the Hyperliquid leaderboard held $156.2M of longs against $2,629.5M of shorts, a ratio of 0.06. 61 of the 67 wallets with open perps were net short, and those shorts alone were 25.2% of all BTC open interest.

"Long/short ratio" is one of the most searched trading metrics, and also one of the most misread. Most dashboards publish a single number without saying who was counted, whether they counted accounts or dollars, and whether the positions are bets or hedges. This guide explains what the ratio can and cannot tell you on Hyperliquid, shows how to compute it yourself from public data for any group of wallets, walks through a dated real example, and ends with a Python script that needs no account and no API key.

Why the whole-market ratio is always 1

A perpetual future is a contract between two sides. When someone opens a 1 BTC long, someone else holds a 1 BTC short. Hyperliquid's open interest (OI) is that one-sided total: in our snapshot BTC OI was about $3.18B, which means $3.18B of BTC longs and $3.18B of BTC shorts at the same time. Summed across every account, the dollar long/short ratio can never be anything other than 1.

So any ratio different from 1 comes from one of two choices:

• Counting accounts instead of dollars. If 7,000 small accounts are long and 3,000 larger accounts are short, the "account ratio" is 2.33 even though the dollars are perfectly balanced. This mostly tells you what retail is doing.
• Measuring a subset. The leaderboard's top traders, the biggest accounts, a list of wallets you follow. This is where the ratio becomes useful, because you are asking "which side is this specific group on?"

Before trusting any long/short chart, find out which of the two it is. If the source does not say, treat it as noise.

Three ways to measure positioning on Hyperliquid

Method	What it counts	Good for	Main trap
Account ratio	Number of wallets long vs short	Crowd sentiment	One whale and one $50 account count the same
Notional ratio of a cohort	Dollars long vs short for a chosen group	What large or skilled traders are doing	Two or three wallets can dominate the total
Cohort share of OI	Cohort shorts (or longs) ÷ total OI	How much of the market one group controls	Hedges look like directional bets

Hyperliquid itself does not publish a long/short ratio. Everything below is built from two public endpoints: the leaderboard (to pick the cohort) and clearinghouseState (to read each wallet's open positions). If you are new to OI, read our Hyperliquid open interest guide first.

Real example: what the month's best traders hold (31 October 2026)

We took the Hyperliquid leaderboard at 08:15 UTC on 31 October 2026, sorted it by PnL over the last month, and read the open perp positions of the top 100 wallets. Their monthly PnL ranged from +$1.8M to +$123.5M. 67 of them had open perp positions; the rest were flat or held only spot.

Coin	Longs	Shorts	L/S ratio	Positions (long/short)	Cohort shorts as % of OI
All coins	$156.2M	$2,629.5M	0.06	330 / 1,115	–
BTC	$32.1M	$803.5M	0.04	7 / 36	25.2%
ETH	$32.1M	$636.9M	0.05	13 / 31	28.8%
HYPE	$40.1M	$290.9M	0.14	8 / 36	15.0%
SOL	$1.0M	$170.1M	0.01	5 / 27	33.0%
XRP	$0.5M	$60.7M	0.01	6 / 19	31.3%

Notional is measured at mark price (BTC $77,390, ETH $2,243.6, HYPE $87.61 at the time). At wallet level, 61 wallets were net short and 6 were net long. After a month in which BTC and ETH fell, the traders who made the most money were, unsurprisingly, the ones still short. That is the first lesson: a "top traders" cohort chosen by recent PnL is biased towards whatever worked recently. Their positioning describes the trend that just happened, not necessarily the next one.

Concentration: check who is behind the number

In the same cohort, the three largest wallets by gross exposure accounted for 42.9% of all the dollars. Two of them, 0x5b5d…c060 ($607.8M short, no longs) and 0xb83d…6e36 ($437.5M short, no longs), are also the top two on the monthly PnL board. Remove them and the ratio is still heavily short, but the totals shrink by more than a third.

A second cohort shows the effect even more strongly. Sorting the leaderboard by account value instead of PnL, the 100 largest accounts ranged from $40.9M to $15.1B, yet only 15 of them had any perp position open. Those 15 held $43.9M long and $1,678.0M short (ratio 0.03), and the top three wallets made up 68.9% of the exposure. Most of the biggest accounts on Hyperliquid are holding spot, not trading perps, so "the biggest wallets are short" here really means "a handful of the biggest wallets are short".

Practical rule: always print the top three contributors next to the ratio. If one wallet is half the number, you are tracking one trader, not a group. Tools like our Smart Money view and whale tracking guide help you look at those individual wallets.

Hedge or bet? The question a ratio cannot answer

A short perp can be a bearish bet, or it can be the other half of a hedge: a fund holding spot HYPE or staked HYPE and shorting the perp to lock in value or collect funding, or a market maker offsetting inventory. Both look identical in clearinghouseState. Before reading a cohort's shorts as a forecast, check:

• Spot balances. Call spotClearinghouseState for the same wallet. A large spot HYPE balance next to a HYPE perp short is very likely a hedge.
• Funding. If funding is positive, shorts are being paid. A delta-neutral position earning funding will show up as a large short. Our funding arbitrage guide covers how these trades work.
• Cross-venue positions. A Hyperliquid short may be offset by a long elsewhere, which you cannot see from Hyperliquid data alone.
• Position age and changes. A short opened today says more about current views than one held for months. Compare snapshots over time, or read the wallet's fills.

How to use the long/short ratio well

1. Define the cohort explicitly, for example "top 100 by monthly PnL" or "the 20 wallets I follow", and keep it fixed so the trend over time means something.
2. Use dollars, then check accounts. Dollar ratio shows where the money is; account ratio shows whether it is broad or concentrated.
3. Track change, not level. A cohort that goes from 0.06 to 0.50 in a week is telling you far more than a static 0.06.
4. Compare with OI. If a cohort's shorts are 25% of BTC OI and they start closing, that buying pressure is significant. If they are 1% of OI, it barely matters.
5. Combine with risk metrics. A short-heavy cohort with a high Sharpe ratio is a different signal from one with large drawdowns.
6. Never use it alone as an entry signal. Crowded positioning can stay crowded for a long time.

Python script: long/short ratio for any cohort

The script below picks the top 100 leaderboard wallets (by monthly PnL, or by account value if you change RANK_BY), reads their open perp positions, and prints longs, shorts, the ratio and the cohort's share of open interest. It uses only public endpoints, takes about two to three minutes because it makes one request per wallet, and needs nothing but requests. To measure your own list of wallets, replace wallets with your addresses. For more on the API, see our Hyperliquid API Python guide and rate limits guide.

import time, requests
from collections import defaultdict

API = "https://api.hyperliquid.xyz/info"
LB = "https://stats-data.hyperliquid.xyz/Mainnet/leaderboard"
TOP_N = 100
RANK_BY = "month_pnl"   # or "account_value"
COINS = ["BTC", "ETH", "HYPE", "SOL", "XRP"]

def post(body):
    r = requests.post(API, json=body, timeout=15)
    r.raise_for_status()
    return r.json()

def month_pnl(row):
    return float(dict(row["windowPerformances"])["month"]["pnl"])

rows = requests.get(LB, timeout=60).json()["leaderboardRows"]
key = month_pnl if RANK_BY == "month_pnl" else (lambda r: float(r["accountValue"]))
wallets = [r["ethAddress"] for r in sorted(rows, key=key, reverse=True)[:TOP_N]]

agg = defaultdict(lambda: {"long": 0.0, "short": 0.0, "nl": 0, "ns": 0})
net_long = net_short = 0
for w in wallets:
    st = post({"type": "clearinghouseState", "user": w})
    L = S = 0.0
    for ap in st["assetPositions"]:
        p = ap["position"]
        side = "long" if float(p["szi"]) > 0 else "short"
        ntl = float(p["positionValue"])          # notional at mark price
        for k in (p["coin"], "ALL"):
            agg[k][side] += ntl
            agg[k]["n" + side[0]] += 1
        L, S = (L + ntl, S) if side == "long" else (L, S + ntl)
    net_long += L > S
    net_short += S > L
    time.sleep(0.1)  # be polite to the public API

meta, ctxs = post({"type": "metaAndAssetCtxs"})
oi = {u["name"]: float(c["openInterest"]) * float(c["markPx"])
      for u, c in zip(meta["universe"], ctxs)}

print(f"{net_long} wallets net long, {net_short} net short")
for c in ["ALL"] + COINS:
    a = agg[c]
    ls = a["long"] / a["short"] if a["short"] else float("inf")
    line = (f"{c:5} long ${a['long']/1e6:,.1f}M  short ${a['short']/1e6:,.1f}M  "
            f"L/S {ls:.2f}  positions {a['nl']}L/{a['ns']}S")
    if c in oi:
        line += f"  cohort shorts = {a['short']/oi[c]:.1%} of OI"
    print(line)

Notes: positionValue is notional at mark price; openInterest in metaAndAssetCtxs is in coins, so we multiply by mark price. The script only reads the main perp DEX, not HIP-3 builder markets. Numbers move every second, so always date your snapshot.

Doing this without code

If you would rather not run scripts, Hyperfolio lets you add any public Hyperliquid address in read-only mode, with no wallet connection and no API key, and see its open positions, PnL, funding and history in one place. Add the wallets you care about, check their side and size whenever you want, and follow the leaderboard's Smart Money from your phone as a PWA. See how to track multiple Hyperliquid wallets and our leaderboard guide.

FAQ

Does Hyperliquid show a long/short ratio?

No. Hyperliquid shows open interest and funding, but not a long/short ratio. You build one from public wallet positions, as in the script above.

Why is the overall long/short ratio always 1?

Because every perp contract has a long side and a short side of the same size. Open interest counts one side, and the other side is always equal.

What does a long/short ratio of 0.06 mean?

For every $1 the cohort holds long, it holds about $16.80 short. In our 31 October 2026 snapshot, that was the position of the top 100 wallets by monthly PnL.

Is the account-based ratio useful?

It shows how many traders are on each side, which is a rough sentiment gauge, but it ignores size. Use it together with a dollar-based ratio.

Are big shorts always bearish bets?

No. Many are hedges against spot holdings, delta-neutral funding trades or market-making inventory. Check spot balances and funding before drawing conclusions.

How often should I recalculate it?

Daily is enough for most traders. What matters is comparing the same cohort over time and noticing when its positioning shifts.

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