The financial technology community is actively discussing a new Python library called Finstruments, which aims to challenge the established QuantLib framework with a more streamlined approach to modeling financial instruments. The discussion reveals both enthusiasm for its simplicity and questions about its practical applications.
The QuantLib Alternative Debate
One of the most notable discussions centers around Finstruments' positioning against QuantLib. Developer Kyle Loomis argues that while QuantLib is the reference in this domain, it suffers from being a bloated C++ library ported to Python, with unintuitive design and lack of modularity. Finstruments aims to provide a more intuitive, simple, and modular alternative for developers who prioritize coding experience over comprehensive functionality.
Current Capabilities and Limitations
The library currently focuses on:
- Basic instrument definitions and specifications
- JSON serialization and deserialization
- Support for options, forwards, and custom instrument extensions
- Portfolio and trade management capabilities
However, community feedback highlights several limitations:
- Limited instrument coverage (no bonds, currencies, interest rates, or swaps yet)
- Early stage of development
- Need for more practical examples and use cases
Data Storage Considerations
An interesting tangent in the discussion revolves around financial data storage solutions. The developer suggests multiple approaches depending on scale and requirements:
- Flat files (organized by date, instrument, ticker)
- Time series databases (ClickHouse, Kdb+)
- The choice largely depends on budget, overhead requirements, and data volume
Future Development
The project is actively evolving, with several features in the pipeline:
- Addition of convertible bonds (requested by community)
- Expansion of instrument types
- Enhanced documentation and usage examples
Integration Potential
The community has noted potential applications including:
- Backtesting systems
- Option payoff calculations
- Portfolio P&L tracking
- Risk management
- API integration
- Document storage solutions
While some developers express enthusiasm about the project's potential, others question its value proposition against existing solutions. The developer maintains that the focus on simplicity and modern design principles will provide a better alternative for specific use cases where QuantLib might be overwhelming.