Crypto Market Data Types for Research and Backtesting
Summary
This primer surveys real-time and historical cryptocurrency data used in trading, research, and risk analysis. It distinguishes trade records, price feeds, and order-book data, describing tick-by-tick trades, normalized aggressor direction, snapshots, best bid and ask quotes, and standard price and volume summaries. It also gives an example historical price calculation based on high, low, and close values. Reconstructable order-book events and timestamped trades can support market-microstructure analysis and more detailed backtests than candle data alone.
The text lists delivery options for historical and streaming data and describes coverage across spot, futures, perpetuals, and options, including venue-specific examples. It stresses that normalization across exchanges helps make datasets more consistent. These descriptions are useful as a data-selection checklist, but the document is primarily a vendor overview and includes promotional claims. It does not compare providers independently or establish that any stated coverage, latency, completeness, or reliability is suitable for a particular strategy. Researchers still need to check timestamps, missing records, venue conventions, and survivorship or sampling issues before using data in analysis.
Key ideas
- Trade, price, and order-book feeds serve different research and execution needs.
- Tick-level trades with normalized aggressor direction can support more detailed analysis than aggregated candles.
- Historical order-book events and snapshots can help reconstruct market conditions for backtesting.
- Cross-venue normalization can improve consistency, but dataset quality still needs independent validation.
- The primer is a vendor overview and does not compare providers or test a trading strategy.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.