The success of trading algorithms depends first and foremost on overcoming data challenges. Machine learning requires clean, normalized historical data showing relationships across assets, exchanges, and time periods. Data flaws like survivorship bias or inconsistent taxonomies produce misleading predictions. The advantage in today's algorithmic markets goes to models supported by reliable data infrastructure.
Poor data quality leading to unreliable models
Survivorship bias
Inconsistent data formats
Temporal mismatches
Incomplete features
Limited historical data for rare events
We've served billions of crypto API requests. Now we're bringing that same reliability and simplicity to stock market and currency exchange data. One clean API. All the data you need. Nothing you don't.
Great tool for any market sector
Use case: Trading platforms
Trading platforms need comprehensive reference data beyond price feeds, but developers struggle with fragmented sources and complex APIs, forcing them to either integrate costly enterprise solutions or build custom infrastructure from scratch.