The structural framework and technological systems designed for the acquisition, processing, storage, distribution, and consumption of real-time and historical market data across various digital asset venues. It forms the foundation for informed trading and investment decisions.
Mechanism
This architecture typically comprises several layers: data ingestion from multiple sources (e.g., exchange APIs, OTC feeds), data normalization and enrichment components to ensure consistency, high-performance data storage (e.g., time-series databases), and low-latency distribution mechanisms (e.g., message queues, websockets) to consuming applications like algorithmic trading systems, risk engines, and analytics platforms. Redundancy and fault tolerance are integral to its design.
Methodology
Effective market data architecture employs strategies such as data compression, intelligent filtering (Signal Filtering), and optimized network topology to minimize latency and maximize throughput. It prioritizes data integrity and availability, often implementing reconciliation processes to validate data quality. This systematic approach ensures that all downstream systems receive accurate, timely, and complete market information, which is critical for price construction, execution, and risk management in the volatile crypto market.
A federated governance model enhances CAT data accuracy by distributing validation responsibility to the source, creating a scalable and accountable system.
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