Algorand perpsALGO

Crypto perp · Binance, OKX, Hyperliquid · #215 by volume

0.08451-3.15% 24h

Binance USDT · 24h 0.08418 – 0.08927

24h volume: $13.1M; #215 of 914
Open interest: $10.3M; −1.3% contracts · 24h
Spread: 1.16 bps; median · 24h
Size at best price: $505; mean · 24h
Net taker flow: −$876.0K; every contract · 24h
Funding: −0.0012%; per period · BIN

Aperiodic metrics · ALGO · 24 h

Are takers buying or selling ALGO?

Takers sold $875.5K more than they bought on Binance, OKX and Hyperliquid over 24 h; the heaviest hour, 14:25 UTC, saw $338.1K.

+$338.1K0−$338.1K

23:25 UTCnow

flow.volume_delta_notionalbusiest contract on each venue · hourly · 24 h

What does it cost to cross ALGO's spread?

L1 liquidity

1.16 bps median on Binance USDT, tighter than 69% of the 200 most traded perps.

#1BTC0.015 bps
#2ETH0.051 bps
#3SOXL1.56 bps
#5SOL1.25 bps
#10AKE3.18 bps
#25XYZ:XYZ1000.35 bps
#50MUU5.64 bps
#100MVLL8.76 bps
#200AIN2.70 bps
#215ALGO1.16 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at ALGO's best price?

L1 liquidity

$505 at the best bid and ask on Binance USDT, on average, thinner than 82% of the 200 most traded perps.

#1BTC$651.7K
#2ETH$269.8K
#3SOXL$86.9K
#5SOL$157.5K
#10AKE$553
#25XYZ:XYZ100$165.1K
#50MUU$22.4K
#100MVLL$13.7K
#200AIN$180
#215ALGO$505

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is ALGO's book leaning?

L2 imbalance

Leaned to the ask in 21 of 24 hours on Binance USDT; 43% bids over the day.

68% bid032% bid

23:25 UTCnow

l2_imbalance.imbalance_ratio_10Binance USDT · top 10 levels · hourly

Where does ALGO trade?

OHLCV

Binance USDT took 77% of $13.1M traded in 24 h.

volume sharespread

Binance USDT77%1.16
OKX USDT20%1.17
Hyperliquid USDC3.7%5.98

ohlcv.volume_notionaleach contract · 24 h

Does ALGO trade away from its index?

Basis

2.65 bps below its index on Binance USDT now; 3.71 bps to 13.5 bps below over 24 h.

+13.5 bps0−13.5 bps

23:25 UTCnow

basis.basis_bpsBinance USDT · hourly

Is leverage building in ALGO?

Open interest

$10.3M open across 3 contracts: −1.3% in contracts, −4.5% in dollars over 24 h.

$10.9M$10.3M

23:25 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on ALGO?

Funding

Longs pay on 0 of 3 contracts; Binance USDT charges −0.0012% a period (Hyperliquid’s are hourly).

Binance USDT−0.0012%
OKX USDT−0.0074%
Hyperliquid USDC−0.0021%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

ALGO's 3 contracts · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Binance USDTperpetual-ALGO-USDT:USDT	0.08451	-3.15%	$10.1M	$5.5M	−0.0012%	1.16	Charts →
OKX USDTperpetual-ALGO-USDT:USDT	0.08452	-3.18%	$2.6M	$2.6M	−0.0074%	1.17	Charts →
Hyperliquid USDCperpetual-ALGO-USDC:USDC	0.08446	-3.24%	$490.1K	$2.2M	−0.0021%	5.98	Charts →

History · a year of 5m bars per series · busiest contract on each venue

Every chart for ALGO →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

# aperiodic.io/markets: ALGO on Binance, OKX and Hyperliquid
# 5m bars, 2025-11-12 to 2026-11-12. Install: pip install "aperiodic[polars]"
# Needs an API key (https://aperiodic.io/home/api) on a plan with flow, basis, open_interest, funding (Pro) and l1_liquidity, l2_imbalance (Prime).
# OKX: okx-perps l1_liquidity and l2_liquidity count contracts, not coins (BTC-USDT-SWAP is 0.01 BTC each). Multiply by the contract size to match the page.
API_KEY = os.environ["APERIODIC_API_KEY"]
# timestamp="true" keys bars on capture time, as on the page; "exchange" keys them on exchange time.
PERIOD = dict(
    interval="5m",
    timestamp="true",
    start_date=date(2025, 11, 12),
    end_date=date(2026, 11, 12),
)
CONTRACTS = [
    ("binance-futures", "perpetual-ALGO-USDT:USDT"),
    ("okx-perps", "perpetual-ALGO-USDT:USDT"),
    ("hyperliquid-perps", "perpetual-ALGO-USDC:USDC"),
]

frames = {}
for exchange, symbol in CONTRACTS:
    frames["flow", exchange, symbol] = get_metrics(
        api_key=API_KEY,
        metric="flow",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["l1_liquidity", exchange, symbol] = get_metrics(
        api_key=API_KEY,
        metric="l1_liquidity",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["l2_imbalance", exchange, symbol] = get_metrics(
        api_key=API_KEY,
        metric="l2_imbalance",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["basis", exchange, symbol] = get_derivative_metrics(
        api_key=API_KEY,
        metric="basis",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["open_interest", exchange, symbol] = get_derivative_metrics(
        api_key=API_KEY,
        metric="open_interest",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["funding", exchange, symbol] = get_derivative_metrics(
        api_key=API_KEY,
        metric="funding",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )

Every number is from Aperiodic's own 5-minute bars, 15 minutes behind.

Contract

Price

24h

Volume 24h

Open interest

Funding

Spread

Binance USDTperpetual-ALGO-USDT:USDT

0.08451

-3.15%

$10.1M

$5.5M

−0.0012%

1.16

Charts →

OKX USDTperpetual-ALGO-USDT:USDT

0.08452

-3.18%

$2.6M

−0.0074%

1.17

Charts →

Hyperliquid USDCperpetual-ALGO-USDC:USDC

0.08446

-3.24%

$490.1K

$2.2M

−0.0021%

5.98

Charts →

import os from datetime import date from aperiodic import get_derivative_metrics, get_metrics # aperiodic.io/markets: ALGO on Binance, OKX and Hyperliquid # 5m bars, 2025-11-12 to 2026-11-12. Install: pip install "aperiodic[polars]" # Needs an API key (https://aperiodic.io/home/api) on a plan with flow, basis, open_interest, funding (Pro) and l1_liquidity, l2_imbalance (Prime). # OKX: okx-perps l1_liquidity and l2_liquidity count contracts, not coins (BTC-USDT-SWAP is 0.01 BTC each). Multiply by the contract size to match the page. API_KEY = os.environ["APERIODIC_API_KEY"] # timestamp="true" keys bars on capture time, as on the page; "exchange" keys them on exchange time. PERIOD = dict( interval="5m", timestamp="true", start_date=date(2025, 11, 12), end_date=date(2026, 11, 12), ) CONTRACTS = [ ("binance-futures", "perpetual-ALGO-USDT:USDT"), ("okx-perps", "perpetual-ALGO-USDT:USDT"), ("hyperliquid-perps", "perpetual-ALGO-USDC:USDC"), ] frames = {} for exchange, symbol in CONTRACTS: frames["flow", exchange, symbol] = get_metrics( api_key=API_KEY, metric="flow", exchange=exchange, symbol=symbol, **PERIOD, ) frames["l1_liquidity", exchange, symbol] = get_metrics( api_key=API_KEY, metric="l1_liquidity", exchange=exchange, symbol=symbol, **PERIOD, ) frames["l2_imbalance", exchange, symbol] = get_metrics( api_key=API_KEY, metric="l2_imbalance", exchange=exchange, symbol=symbol, **PERIOD, ) frames["basis", exchange, symbol] = get_derivative_metrics( api_key=API_KEY, metric="basis", exchange=exchange, symbol=symbol, **PERIOD, ) frames["open_interest", exchange, symbol] = get_derivative_metrics( api_key=API_KEY, metric="open_interest", exchange=exchange, symbol=symbol, **PERIOD, ) frames["funding", exchange, symbol] = get_derivative_metrics( api_key=API_KEY, metric="funding", exchange=exchange, symbol=symbol, **PERIOD, )