Validated OKX market data

Validated OKX market data for cross-venue research and production workflows.

Request OKX historical datasets and replay-ready packages with explicit completeness, timing provenance, order-book validation, and transparent confidence states.

Historical Replay Order book Manifests Pilot Live on request

Often requested for multi-venue strategy research, market-data QA, and replayable exchange-specific historical slices.

Timing model in progress
  • orderTimeexchange-side event time
  • receiveTimeclient-side packet receive time
  • crossConnectExchangeNameReceiveTimecross-connect timing layer

Keep timing provenance visible. Low-latency language matters only when the time chain is explicit and observable.

What to send us
  • Exchange, symbols, and channels
  • Historical range or replay window
  • Research, trading, analytics, or data-product use case
  • Whether you need a sample file, manifest example, or pilot conversation

Why this landing page exists

Quick demand check, not generic product theater.

These pages are meant to qualify real demand for OKX datasets quickly. The point is to get a precise request for symbols, channels, date range, and use case - then scope the right sample, manifest, or pilot discussion.

Explicit completeness

Datasets are scoped by exchange, symbols, channels, and time range - with visible coverage, gap markers, and manifest-level truth.

Timing provenance

Keep exchange time, receive time, and normalized time distinct so timing-sensitive workflows are grounded in observable provenance.

Validated book states

Book reconstruction is treated as a product surface, not a hidden internal calculation. Confidence and degradation states stay visible.

Deterministic replay

Use the same historical slice for simulation, QA, post-trade analysis, and research without losing the event structure that matters.

Who usually asks

OKX demand tends to start with one of these workflows.

The more specific you are about symbols, channels, and date range, the faster we can qualify the demand and send a useful sample.

  • Research teams comparing OKX with other venues across the same market regime.
  • Infra and QA teams that want exchange-specific validation signals and clearer lineage.
  • Product teams that need an upstream dataset they can build on.

Historical data framework

Width, depth, correctness.

The older project vision still works well as a landing-page frame: demand is rarely about access alone. Buyers usually care about scope, usable depth, and whether the dataset can actually be trusted.

Width

  • Symbols and channels
  • Venue coverage
  • Sample datasets on request
  • Historical plus live-scope discussion

Depth

  • History window
  • Trades and books
  • Replay-ready delivery
  • Raw and curated layers

Correctness

  • Gaps and recoveries
  • Timestamp provenance
  • Validation signals
  • Manifests and confidence states

Python example

Give the buyer a concrete request shape.

Show a direct replay example, then point to the full docs. For non-Binance scopes, buyers can swap the exchange and symbols after the first conversation.

See full docs at https://docs.marketdata.trade/api/python

Example request
# see full docs at https://docs.marketdata.trade/api/python

# pip install marketdata.trade

import asyncio
from marketdata.trade import MarketDataClient, Stream

marketdata_client = MarketDataClient(api_key="<YOUR_API_KEY>")

async def replay():
    events = marketdata_client.replay(
        exchange="binance",
        from_date="2024-02-29",
        to_date="2024-03-30",
        filters=[Stream(name="book", symbols=["BTC-USDT"])]
    )

    async for receive_binance_timestamp, message in events:
        print(message)


asyncio.run(replay())

Request OKX data

Ask for a sample dataset, manifest example, or pilot discussion.

No long generic demo call needed. Send the exact scope you care about and the next step can stay concrete.

Open Python docs

This static prototype opens a prepared email to the configured inbox. Replace the email or connect a form endpoint before production launch.