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financial-computing-numpy - Vectorized Financial Computing with NumPy

Implement vectorized numerical pipelines for finance with strict correctness and performance diagnostics

Tags

Updated: 2026-02-13
financial computingNumPyvectorizationquantitative researchnumerical analysis

Capabilities

define array shapes and broadcasting rulesimplement vectorized transforms for returnsimplement vectorized transforms for covariancesvalidate numerical accuracy against scalar implementations

Typical Inputs

input.csvarray shapesbroadcasting rules

Typical Outputs

diagnostics.jsonimplementation memo

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

Source

  • Spec: SKILL.md

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