Funding Rate Dataset

Historical Crypto Funding Rate Data

Funding rates, mark prices, and index prices from major perpetual and futures venues, packaged as hourly Parquet/Zstd files.

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No credit card · The sample is one real hourly Parquet file and needs no API key

Sample

See the data before you sign up

The first rows of one real hour: BTCUSDT on Binance Futures, 2026-09-02 at 12:00 UTC. One row per mark price update.

binance_futures/2026-09-02/12/BTCUSDT_mark_price.parquetDownload full file
received_timeevent_timesymbolmark_priceindex_priceestimated_settle_pricefunding_ratenext_funding_time
17883504002371884171788350400000BTCUSDT76799.0090289976830.0400000076652.432894810.000057451788364800000
17883504012183704511788350401000BTCUSDT76798.5368550776829.5678260976652.622303740.000057421788364800000
17883504022089565081788350402000BTCUSDT76796.3996811676827.4306521776652.810524150.000057421788364800000
17883504032145073061788350403000BTCUSDT76791.5483768176822.5793478376653.090941260.000057421788364800000
17883504042121439141788350404002BTCUSDT76789.7242463876820.7552173976653.274232550.000057421788364800000
17883504052121715311788350405000BTCUSDT76787.0618478376820.7552173976653.363247340.000057421788364800000
Showing 6 of 3,527 rows in this hourTimestamps are raw integers; units are in the schema below

Wire format

From exchange message to Parquet row

Every row starts as a message on the exchange's WebSocket or REST API. Point at a line or a column to see where each value comes from and how we convert it. Our test suite replays these messages through the production pipeline, so the rows shown are the rows you download.

Exchange sends

WebSocket message · !markPrice@arr@1sreceived 2026-10-05 19:01:42.216687 UTC

{
  "stream": "!markPrice@arr@1s",
  "data": [
    {
      "e": "markPriceUpdate",
      "E": 1791226902000,
      "s": "BTCUSDT",
      "p": "85583.30000000",
      "ap": "85583.30000000",
      "P": "85612.13024722",
      "i": "85633.04043478",
      "r": "0.00000563",
      "T": 1791244800000,
      "st": 1
    }
  ]
}

Shortened: The all-market frame contained 745 symbols. This example shows only BTCUSDT. Each entry becomes its own row.

You download

Parquet row · mark_price

Point at a line in the message or a column in the row to trace where each value comes from. Click a column to pin it.

Our tests replay this message through the production pipeline

All Binance Futures mapping rules →

Conventions for every exchange are in the wire formats overview. Column types and units for funding rate data are in the schema below.

Use cases

What you can build with funding rate data

Funding carry and basis
Measure what it cost to hold a perpetual position over time and compare it with spot or dated futures.
Cross-exchange funding spreads
Find persistent funding differences for the same asset across venues for relative-value research.
Mark vs. index dislocation
Track the gap between mark and index price to study premium, sentiment, and liquidation risk.

Coverage

Funding rate coverage

Every venue is stored under its own exchange ID, so spot and derivatives never mix. Bars show each venue's history from its first hourly file to today, or to its last file for a venue that is no longer collected. Symbol counts are live from the symbols API.

Funding rate coverage by venue, exchange ID, market, history start, and live symbol count
VenueExchange IDMarketHistoryMark price symbols
Binance Futuresbinance_futuresFutures
2025-06-2816 mo
988
Bybit FuturesbybitFutures
2025-06-2816 mo
1,526
OKX Futuresokx_futuresFutures
2025-06-2816 mo
641
Bitget Futuresbitget_futuresFutures
2025-07-1515 mo
1,210
Kraken Futureskraken_derivativesFutures
2025-06-2816 mo
680
Hyperliquid Futureshyperliquid_futuresPerpetuals
2025-09-2913 mo
451
Aster Futuresaster_futuresFutures
2025-09-2913 mo
798
BitMEXbitmexFutures
2025-09-29 to 2026-09-2212 mo
156
LighterlighterPerpetuals & Spot
2025-12-3010 mo
239

By exchange

Funding & Mark Price data by exchange

Each exchange page covers its markets, verified history start, and a sample from that venue.

Binance Historical Funding Rate Datasince 2025-06-28Bybit Historical Funding Rate Datasince 2025-06-28OKX Historical Funding Rate Datasince 2025-06-28Bitget Historical Funding Rate Datasince 2025-07-15Kraken Historical Funding Rate Datasince 2025-06-28Hyperliquid Historical Funding Rate Datasince 2025-09-29Aster Historical Funding Rate Datasince 2025-09-29BitMEX Historical Funding Rate Datasince 2025-09-29Lighter Historical Funding Rate Datasince 2025-12-30

Schema · 8 columns

Normalized mark price schema

Every mark price row carries mark, index, and estimated settle prices plus the current funding rate (a fraction per funding period) and next funding time for perpetual contracts, where the venue publishes them.

Columns in every funding rate Parquet file
ColumnTypeDescription
received_timeINT64Unix timestamp (nanoseconds) when our system received the mark price event
event_timeINT64Unix timestamp when the exchange generated the event (the time unit changes with the exchange)
symbolSTRINGTrading pair symbol (for example, 'BTCUSDT')
mark_priceSTRINGnullableMark price that the exchange uses to calculate liquidations (stored as string for precision)
index_priceSTRINGnullableIndex price from the underlying spot exchanges (stored as string for precision)
estimated_settle_priceSTRINGnullableEstimated settlement price at contract expiration (stored as string for precision)
funding_rateSTRINGnullableCurrent funding rate for perpetual contracts, as a fraction for each funding period (0.0001 = 0.01 %; stored as string for precision). Kraken Futures and Lighter history before the 2026-09 data-integrity release use other units (refer to the venue notes)
next_funding_timeINT64nullableUnix timestamp when the next funding payment will occur. Lighter history before the 2026-09 data-integrity release contains the last funding time instead

Quickstart

From pip install to DataFrame in a minute

The example loads BTCUSDT from Binance Futures for 2026-09-02. Change the symbol, exchange, or dates to pull any other slice of the archive.

  1. Install the Python SDK

    pip install cryptohftdata

  2. Create a free API key

    Sign up with email or Google, then generate a key from your dashboard. No credit card.

    Create account

  3. Call get_mark_price()

    Paste the snippet, replace YOUR_API_KEY, and you get a pandas DataFrame with the columns listed above.

Read mark price docsExplore in the browser
crypto_funding_rate_data.py
import cryptohftdata as chd

client = chd.CryptoHFTDataClient(api_key="YOUR_API_KEY")

df = client.get_mark_price(
    symbol="BTCUSDT",
    exchange=chd.exchanges.BINANCE_FUTURES,
    start_date="2026-09-02",
    end_date="2026-09-02",
)

print(df.head())
print(f"Mark price updates: {len(df):,}")
REST · no API key needed for single files
curl --fail --location \
  "https://api.cryptohftdata.com/download?file=binance_futures/2026-09-02/12/BTCUSDT_mark_price.parquet" \
  -o BTCUSDT_mark_price_12.parquet

Caveats

Know this before you backtest

Exchange feeds differ in subtle ways. These are the details that matter for accurate backtests, replay pipelines, and features. Missing hours and pending corrections for every venue are listed on Known Gaps & Corrections.

  1. Funding rate and next funding time ship inside the mark price files ({symbol}_mark_price.parquet) alongside mark, index, and estimated settle prices.

  2. Funding applies to perpetual contracts; rows for other instruments carry mark and index prices without funding fields.

  3. funding_rate is a fraction per funding period. Kraken Futures history before the 2026-09 data-integrity release holds Kraken's absolute funding rate, and Lighter history holds percent; corrections are planned.

  4. OKX funding rows before the release are timestamped with the next settlement time, which introduces look-ahead if you join on event_time; use received_time for that history.

  5. This page starts on 2025-06-28 based on the earliest stored hourly files for its covered exchange IDs and grows as new hourly files are published.

  6. BitMEX (bitmex) is historical only: the exchange has closed and its files end on 2026-09-22.

FAQ

Frequently asked questions

Is this funding rate data free to download?

Yes. A free CryptoHFTData account with no credit card gives API access to this funding rate data and every other dataset. Individual hourly files can also be downloaded without an API key on the rate-limited free tier.

How far back does this funding rate data go?

The earliest hourly files start on 2025-06-28, and new files are added every hour. Start dates differ by venue; the coverage table on this page lists each one.

What format are the files in?

Each file holds one symbol for one UTC hour, stored as Zstd-compressed Parquet under {exchange_id}/{YYYY-MM-DD}/{HH}/{SYMBOL}_mark_price.parquet. Parquet reads directly into pandas, Polars, DuckDB, and Arrow.

How do I load this funding rate data in Python?

Install the SDK with pip install cryptohftdata, create a client with your API key, and call client.get_mark_price() with a symbol, exchange, and date range. It returns a pandas DataFrame.

Where is the funding rate stored?

Funding rate and next funding time ship inside the mark price files ({symbol}_mark_price.parquet), next to the mark, index, and estimated settle prices.

Start using funding rate data today.

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