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Nvidia 2x ETF (NVDL) perps on Binance and OKX, from Aperiodic's own 5-minute bars, free and 15 minutes behind. Every perp, A–Z →

Every number here is 15 minutes behind

5m bar 23:20–23:25 UTC

Free, from Aperiodic's own data. The hatched end of each chart marks the 15 minutes left out.

5m bars, 15 minutes behind. The newest runs 23:20–23:25 UTC; the next lands around 23:45 UTC, and the line under this bar fills until it does. Bars are labelled by their open and keyed on capture time: when Aperiodic received each trade, quote and update.

Every metric moves every 15 seconds, just as delayed, each a rolling window over the last 5 minutes, not a 15-second bar; funding, open interest and basis every minute, the finest they are measured at. The day's medians and means roll on with the 5m bars.

1664 perpetuals on Binance, OKX and Hyperliquid.

5m bars received in the last 24h: Binance 99.3% · OKX 99.7%.

Plans with live data and more history →
23:25:00 UTC
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Markets/All perps/NVDL

Nvidia 2x ETF perpsNVDL

ETF perp · Binance, OKX · #185 by volume

17.430-7.78% 24h

Binance USDT · 24h 16.890 – 19.800

24h volume
$17.9M
#185 of 914
Open interest
$2.0M
−10.9% contracts · 24h
Spread
5.72 bps
median · 24h
Size at best price
$4.8K
mean · 24h
Net taker flow
+$196.9K
every contract · 24h
Funding
+0.0000%
per period · BIN

Aperiodic metrics · NVDL · 24 h

Every metric on NVDL, bar by bar →

Are takers buying or selling NVDL?

Flow

Takers bought $197.0K more than they sold on Binance and OKX over 24 h; the heaviest hour, 13:25 UTC, saw $126.2K.

+$177.3K0−$177.3K
23:25 UTCnow

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

What does it cost to cross NVDL's spread?

L1 liquidity

5.72 bps median on Binance USDT, wider than 86% 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
  • #185NVDL5.72 bps
  • #200AIN2.70 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at NVDL's best price?

L1 liquidity

$4.8K at the best bid and ask on Binance USDT, on average, deeper than 63% 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
  • #185NVDL$4.8K
  • #200AIN$180

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is NVDL's book leaning?

L2 imbalance

Leaned to the ask in 13 of 24 hours on Binance USDT; 49% bids over the day.

61% bid039% bid
23:25 UTCnow

l2_imbalance.imbalance_ratio_10Binance USDT · top 10 levels · hourly

Where does NVDL trade?

OHLCV

Binance USDT took 89% of $17.9M traded in 24 h.

volume sharespread

  • Binance USDT89%5.72
  • OKX USDT11%10.7

ohlcv.volume_notionaleach contract · 24 h

Does NVDL trade away from its index?

Basis

12.0 bps above its index on Binance USDT now; 4.72 bps to 15.8 bps above over 24 h.

+15.8 bps0−15.8 bps
23:25 UTCnow

basis.basis_bpsBinance USDT · hourly

Is leverage building in NVDL?

Open interest

$2.0M open across 2 contracts: −10.9% in contracts, −17.8% in dollars over 24 h.

$2.5M$2.0M
23:25 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on NVDL?

Funding

Longs pay on 0 of 2 contracts; Binance USDT charges +0.0000% a period.

  • Binance USDT+0.0000%
  • OKX USDT+0.0000%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

NVDL's 2 contracts · now

Named by Atlas →
ContractPrice24hVolume 24hOpen interestFundingSpreadCharts
Binance USDTperpetual-NVDL-USDT:USDT17.430-7.78%$15.9M$1.5M+0.0000%5.72Charts →
OKX USDTperpetual-NVDL-USDT:USDT17.400-7.94%$1.9M$512.3K+0.0000%10.7Charts →

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

Every chart for NVDL →
Python
import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

# aperiodic.io/markets: NVDL on Binance and OKX
# 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-NVDL-USDT:USDT"),
    ("okx-perps", "perpetual-NVDL-USDT:USDT"),
]

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,
    )

Next by volume

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

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Built from hundreds of terabytes of raw data and distilled into point-in-time metrics you can pull as parquet files. Plus the raw trades, quotes and derivatives data behind them.

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