Derivatives Analytics with Python & Numpy
summary
Claim: Python plus NumPy and pandas implements Monte Carlo derivatives pricing with Longstaff‑Schwartz least‑squares regression, variance reduction and Excel/web integration, delivering practical performance rather than just prototypes. Examples include antithetic paths and moment‑matching variance reduction, a run with 25 time steps × 35,000 paths completing in 1.5 seconds (50 steps × 100,000 paths in ~8.5s), cited as roughly a 480x speedup versus a MATLAB baseline. A web‑based valuation service is built and running, with on‑premise deployment available.
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chapters (12)
- 0:00Introduction
- 3:40What derivatives are
- 9:17Python for analytics
- 16:43Option pricing theory
- 22:25Simulate European options
- 26:23Value American options
- 34:10Optimize simulations
- 40:46Python vs MATLAB speed
- 43:43Full analytics suite
- 47:16Web platform
- 50:19Licensing & deployment
- 55:15Q&A
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