Build and validate quantitative models using real-time and historical crypto market data
Develop trading models, factor models, and statistical research using normalized market data, historical datasets, market benchmarks, and exchange rates from hundreds of exchanges.
Quantitative research applies statistics, mathematics, and data analysis to understand financial markets and develop systematic investment and trading models.
Researchers analyze price movements, liquidity, volatility, correlations, and trading activity to test hypotheses and evaluate market behavior. Reliable research depends on consistent datasets that can be reproduced over time.
Building quantitative models requires much more than collecting price history.
Researchers need historical trades, order books, market benchmarks, and consistent timestamps across hundreds of exchanges. Preparing, cleaning, and validating these datasets often takes longer than developing and testing the research models themselves.
Use normalized trades, quotes, OHLCV, and Level 1, Level 2, and Level 3 order books across hundreds of exchanges, eliminating the need to reconcile different market data formats.
Combine real-time market data with Historical APIs and Flat Files to study everything from intraday liquidity and order flow to multi-year market cycles.
Compare models against CoinAPI's VWAP, PRIMKT, and CAPIVIX indexes to evaluate returns, market performance, and volatility using established reference benchmarks.
Use the Exchange Rates API to convert asset values into a common reporting currency when comparing assets traded across different markets.
Use CoinAPI's hosted MCP servers to connect AI research assistants and analytical applications directly to market data, historical datasets, indexes, and exchange rates.
| What You Need | Before CoinAPI | After CoinAPI |
|---|---|---|
| Build research datasets | Collect and normalize data from multiple exchanges | Use one standardized market data model across hundreds of exchanges |
| Study market microstructure | Limited historical order book availability | Analyze historical Level 1, Level 2, and Level 3 order books |
| Test quantitative models | Maintain separate historical databases | Access years of historical data through APIs and Flat Files |
| Benchmark research | Build custom benchmark datasets | Compare models using CoinAPI VWAP, PRIMKT, and CAPIVIX indexes |
| Compare global markets | Reconcile prices across currencies manually | Normalize valuations with the Exchange Rates API |
| Integrate research tools | Build custom connections to multiple data sources | Connect through standardized APIs and hosted MCP servers |
