Own the data.
Vector and Matrix protect their storage and expose explicit .copy() and .validate() operations.
Open-source research software · v2.0.0
Convexfolio gives constrained portfolio experiments a clear boundary: validate the inputs, solve the problem, inspect the diagnostics.
No brokerage connection · no market-data feed · no investment advice
Deterministic arithmetic in your browser. The Python implementation is documented in the guide.
The design stance
The library is shaped around the moments where quantitative software usually becomes difficult to trust.
Vector and Matrix protect their storage and expose explicit .copy() and .validate() operations.
Invalid inputs, infeasible constraints, and failed numerical solves return typed, actionable diagnostics instead of a plausible-looking answer.
See the contractsRisk, optimisation, constraints, data sources, and backtests meet through small ABC interfaces with interchangeable implementations.
See the v2 shapeA transparent workflow
Convexfolio is deliberately inspectable. Each stage has a boundary, a contract, and a testable outcome.
Walk through the exampleShape, finiteness, conditioning, and configuration policy.
Budget, position, sector, and leverage rules as explicit objects.
Closed-form and numerical strategies behind one typed interface.
Diagnostics, feasibility, warnings, and a versioned result shape.
Build with evidence
Start with the guide, inspect the API, and keep the limits visible.
Scope: Convexfolio does not place trades, connect to brokerages, or provide financial advice.
Understand the limits