financial-computing-numpy - Vectorized Financial Computing with NumPy
Implement vectorized numerical pipelines for finance with strict correctness and performance diagnostics
Tags
Updated: 2026-02-13Capabilities
Typical Inputs
Typical Outputs
What this skill does
- define array shapes and broadcasting rules
- implement vectorized transforms for returns
- implement vectorized transforms for covariances
- validate numerical accuracy against scalar implementations
- benchmark throughput and memory allocation
- run financial computing numpy diagnostics
Inputs
- input.csv
- array shapes
- broadcasting rules
- memory layout assumptions
Outputs
- diagnostics.json
- implementation memo
Requirements
- NumPy environment
- Python execution capability
- numerical stability checks
