Understanding Crypto Market Data: From Tick Trades to OHLCV and Order Books

Navigating crypto market data is like choosing the right lens for a camera. Each type - tick-level trades, quotes, order books, or OHLCV - offers a different resolution of market behavior. Choose wrong, and you might miss the signal. This guide breaks down the most essential types of crypto market data, shows when to use each, and helps you align your data stack with your trading, research, or infrastructure needs.

1. Tick-Level Trades: The Most Granular Crypto Market Data

What it is:

Every individual trade that happens on an exchange captures price, size, and timestamp.

Use it when:

• You’re building a high-frequency trading (HFT) system
• You want to analyze slippage or VWAP fills
• You need to simulate execution timing or market impact

Example Snapshot:

Good for:

Microstructure analysis, volume-weighted strategies, and execution testing.

Want to go deeper into execution modeling and market depth?
Read next: Tick Data vs Order Book Snapshots: Complete Guide for Crypto Trading Systems

2. Quotes: The Fastest View of Crypto Market Liquidity

What it is:

Best bid and ask prices over time, without showing what filled.

Use it when:

• You want to model spread behavior or market stability
• You’re tracking liquidity changes without diving into full order books
• You’re building quote-driven features like fair price estimators

Example Snapshot:

Good for:

Liquidity modeling, latency-sensitive quoting engines, or understanding bid-ask dynamics.

Quotes are just the surface - to see the full picture, you need to look at market depth. Explore: Level 1 vs Level 2 vs Level 3 market data: How to read the crypto order book

3. Order Books: Depth of Crypto Market Data Explained

What it is:

Full depth of resting orders at multiple price levels on both the bid and ask sides.

Use it when:

• You’re simulating passive fills
• You want to analyze depth imbalance or spoofing
• You need to model slippage or build liquidity-aware strategies

Example Snapshot:

Good for:

Execution strategy modeling, stress testing, and book pressure analysis.

Order books show the crowd at the gate - but only if your data is clean and normalized.
Learn more: Why is it critical to normalize cryptocurrency trade data?

4. OHLCV: Aggregated Crypto Market Data for Backtesting

What it is:

Open, High, Low, Close, and Volume aggregated over fixed intervals (e.g., 1-minute bars).

Use it when:

• You’re building a charting dashboard or price model
• You want to train ML models on clean time series
• You need a reliable input for volatility, momentum, or trend detection

Example (1-minute bar):

Good for:

Indicators, trend-following models, and dashboards.

Candlesticks tell a story - if you know how to read them.
Guide: How to read crypto candlestick charts using OHLCV data

Crypto Market Data Selection: Quick Reference Guide

Who Should Use What Crypto Market Data: Recommendations by Role

Understanding which crypto market data type fits your role isn't always obvious. Here's a breakdown to help you choose smarter:

Quant Developers & Execution Engineers

Use: Tick data, L2 order books, WebSocket feeds

Why: Strategy backtesting, execution simulation, latency-sensitive pipelines

APIs: Market Data API, Exchange Link, EMS Trading API

Crypto Fund Managers

Use: OHLCV, L2 books, quotes

Why: NAV calculations, liquidity modeling, alpha decay prevention

APIs: Market Data API, Indexes API, Exchange Rates API

ML Engineers & Data Scientists

Use: Tick-level trades, OHLCV, index benchmarks

Why: Model training, feature engineering, clean historical datasets

APIs: Flat Files, Market Data API

Academic Researchers

Use: OHLCV, quotes, trades, indexes

Why: Reproducibility, cross-market studies, publication-ready analysis

APIs: Market Data API, Flat Files, Indexes API

Arbitrage Traders

Use: Quotes, L2 order books, tick data

Why: Detecting mispricing, modeling depth across venues

APIs: EMS Trading API, Market Data API, Exchange Link

Trading Bot Developers

Use: Quotes, trades, order book data

Why: Real-time strategy input, fill simulation, bot calibration

APIs: EMS Trading API, Market Data API

Portfolio Valuation & Tax Teams

Use: OHLCV, indexes, FX rates

Why: Reliable pricing snapshots, cross-venue consistency, audit tracking

APIs: Indexes API, Exchange Rates API

Infrastructure & Backend Teams

Use: Flat files, normalized APIs

Why: Bulk ingestion, schema consistency, rate limit tolerance

APIs: Exchange Link, EMS Trading API

Choosing the Right Crypto Market Data Architecture

When selecting your crypto market data infrastructure, consider these key factors:

Latency Requirements:

• Millisecond precision = Tick data or L2 orderbooks
• Second-level updates = Quotes
• Minute-level analysis = OHLCV

Volume Handling:

• High-frequency trading = Optimized tick feeds
• Research applications = Flat file formats
• Real-time monitoring = WebSocket streams

Cost Optimization:

• Start with OHLCV and quotes for basic functionality
• Add orderbook data only when strategy demands it
• Use flat files for historical analysis to reduce API costs

Final Recommendations for Crypto Market Data Success

Whether you're building fast, backtesting deep, or pricing accurately, start by choosing the right crypto market data layer. The key is matching your data granularity to your actual business requirements, not just collecting everything available.

Next Step:

→ Explore the Market Data API

→ Need sample data? Request it here