Python for Finance: Analyze Big Financial Data

Performance Comparison

multiprocessing

Dynamic Compiling

Introductory Example

Binomial Option Pricing

Static Compiling with Cython

Generation of Random Numbers on GPUs

Conclusions

Further Reading

9. Mathematical Tools

Approximation

Regression

Monomials as basis functions

Individual basis functions

Noisy data

Unsorted data

Multiple dimensions

Interpolation

Convex Optimization

Global Optimization

Local Optimization

Constrained Optimization

Integration

Numerical Integration

Integration by Simulation

Symbolic Computation

Basics

Equations

Integration

Differentiation

Conclusions

Further Reading

10. Stochastics

Random Numbers

Simulation

Random Variables

Stochastic Processes

Geometric Brownian motion

Square-root diffusion

Stochastic volatility

Jump diffusion