Fartcoin perpsFARTCOIN

Crypto perp · Binance, OKX, Hyperliquid · #145 by volume

0.10630-2.74% 24h

Binance USDT · 24h 0.10300 – 0.11070

24h volume: $31.4M; #145 of 914
Open interest: $31.8M; +1.0% contracts · 24h
Spread: 9.26 bps; median · 24h
Size at best price: $17.0K; mean · 24h
Net taker flow: −$32.1K; every contract · 24h
Funding: +0.0050%; per period · BIN

Aperiodic metrics · FARTCOIN · 24 h

Every metric on FARTCOIN, bar by bar →

What does it cost to cross FARTCOIN's spread?

L1 liquidity

9.26 bps median on Binance USDT, wider than 96% 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
#145FARTCOIN9.26 bps
#200AIN2.70 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at FARTCOIN's best price?

L1 liquidity

$17.0K at the best bid and ask on Binance USDT, on average, deeper than 81% 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
#145FARTCOIN$17.0K
#200AIN$180

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Where does FARTCOIN trade?

OHLCV

Binance USDT took 74% of $31.4M traded in 24 h; the tightest spread is Hyperliquid USDC's, 6.50 bps.

volume sharespread

Binance USDT74%9.26
OKX USDT13%9.27
Hyperliquid USDC12%6.50

ohlcv.volume_notionaleach contract · 24 h

Who pays funding on FARTCOIN?

Funding

Longs pay on 3 of 3 contracts; Binance USDT charges +0.0050% a period (Hyperliquid’s are hourly).

Binance USDT+0.0050%
OKX USDT+0.0050%
Hyperliquid USDC+0.0013%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

The hour-by-hour charts are not on the tape right now; they return with the next bar.

FARTCOIN's 3 contracts · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Binance USDTperpetual-FARTCOIN-USDT:USDT	0.10630	-2.74%	$23.3M	$12.2M	+0.0050%	9.26	Charts →
OKX USDTperpetual-FARTCOIN-USDT:USDT	0.10630	-2.74%	$4.2M	$1.8M	+0.0050%	9.27	Charts →
Hyperliquid USDCperpetual-FARTCOIN-USDC:USDC	0.10626	-2.75%	$3.8M	$17.9M	+0.0013%	6.50	Charts →

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

Every chart for FARTCOIN →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

# aperiodic.io/markets: FARTCOIN 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-FARTCOIN-USDT:USDT"),
    ("okx-perps", "perpetual-FARTCOIN-USDT:USDT"),
    ("hyperliquid-perps", "perpetual-FARTCOIN-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-FARTCOIN-USDT:USDT

0.10630

-2.74%

$23.3M

$12.2M

+0.0050%

9.26

Charts →

OKX USDTperpetual-FARTCOIN-USDT:USDT

0.10630

-2.74%

$4.2M

$1.8M

+0.0050%

9.27

Charts →

Hyperliquid USDCperpetual-FARTCOIN-USDC:USDC

0.10626

-2.75%

$3.8M

$17.9M

+0.0013%

6.50

Charts →

import os from datetime import date from aperiodic import get_derivative_metrics, get_metrics # aperiodic.io/markets: FARTCOIN 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-FARTCOIN-USDT:USDT"), ("okx-perps", "perpetual-FARTCOIN-USDT:USDT"), ("hyperliquid-perps", "perpetual-FARTCOIN-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, )