portfolio-optimization

Guide for optimizing Python numerical computations with C extensions. This skill should be used when tasks involve creating C extensions for Python, implementing mathematical algorithms (matrix operations, linear algebra) in C, or optimizing computational bottlenecks to achieve significant speedup. Particularly relevant for portfolio risk/return calculations, scientific computing, and performance-critical code requiring validation against baseline implementations.