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Lighter Historical Market Data

Download Lighter historical perpetual order books, tick trades, open interest, and funding data in normalized hourly Parquet files.

Perpetuals

Why Lighter on CryptoHFTData?

Research Lighter perpetual markets without first building a historical WebSocket archive. Files retain the venue context needed to reason about market IDs, nonces, funding, and special trade events.

  • L2 book updates, tick trades, and market statistics share an hourly layout
  • Open-interest and funding datasets provide perpetual-market context
  • Normalized files preserve the Lighter market identity for cross-venue joins

Coverage

Lighter historical datasets

Each row is a separate landing page with its own exchange IDs, schema, sample path, caveats, and documented history start. A listed market applies only to that dataset row.

DatasetStored marketsArchive IDHistory startExample object path
Order BookPerpetualslighter2025-12-30lighter/2025-12-31/20/BTC_orderbook.parquetHourly Parquet/Zstd
Tick TradesPerpetualslighter2025-12-30lighter/2025-12-31/20/BTC_trades.parquetHourly Parquet/Zstd
Ticker StatisticsPerpetualslighter2025-12-30lighter/2025-12-31/20/BTC_ticker.parquetHourly Parquet/Zstd
Open InterestPerpetualslighter2025-12-30lighter/2025-12-31/20/BTC_open_interest.parquetHourly Parquet/Zstd
Funding & Mark PricePerpetualslighter2025-12-30lighter/2025-12-31/20/BTC_mark_price.parquetHourly Parquet/Zstd

Before analysis

Lighter conventions that matter

Normalization makes columns consistent; it does not erase contract design, symbol mapping, or limits in the exchange's public feed.

01

Lighter's API addresses books by numeric market index; the archive exposes display symbols but researchers should retain the market mapping used for the requested period.

02

Order book continuity is checked with venue nonces. API-server offsets can change after reconnects and are not a substitute for matching-engine nonce continuity.

03

The venue can publish deleverage trade events with special price semantics. Do not silently treat every trade row as an ordinary buyer-seller match.

Research questions this archive supports

  • Replay nonce-ordered L2 updates and test gap handling
  • Compare market statistics with public trade intensity
  • Align Lighter funding and open interest with another perpetual venue

A safer first analysis

  1. 1. Open the relevant dataset page and confirm the market ID.
  2. 2. Download one known hour and inspect types, timestamps, and units.
  3. 3. Validate gaps and book sequence rules before scaling the date range.
  4. 4. Keep venue-specific contract metadata with every cross-venue join.

Next steps

Start working with Lighter data

Use the dataset pages for exact semantics, then download a small interval and validate it against your research assumptions.

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