A ‘Derivatives Data Model’ defines the structured representation of financial derivative instruments and their associated attributes within an information system. In crypto, this encompasses the data schema for perpetual swaps, futures, options, and other synthetic assets traded on centralized exchanges or decentralized finance (DeFi) platforms. Its purpose is to standardize, store, and process complex derivative contract information for accurate pricing, risk management, and regulatory compliance.
Mechanism
This model typically includes entities for contract specifications, underlying asset references, strike prices, expiration dates, collateral requirements, margin rules, and funding rates. It dictates how data is captured from market feeds, stored in databases, and transmitted across various system components, including calculation engines, order books, and user interfaces. Relationships between different data points ensure logical consistency and referential integrity.
Methodology
The strategic approach for constructing a derivatives data model prioritizes data integrity, scalability, and computational efficiency to support high-volume, low-latency trading and real-time risk assessments. Design principles account for the dynamic nature of derivative products, allowing for extensibility to accommodate new instruments and evolving market conventions while maintaining data accuracy. It provides the foundational structure for advanced financial engineering in crypto.
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