Python for Finance: Analyze Big Financial Data

full vectorization with log Euler scheme, Full Vectorization with Log Euler Scheme

graphical analysis of, Graphical Analysis

importance of, Simulation

integration by simulation, Integration by Simulation

Least-Squares Monte Carlo (LSM) algorithm, American Options, Derivatives

Valuation

pure Python approach, Pure Python

valuation of contingent claims, Valuation–American Options

vectorization with NumPy, Vectorization with NumPy

moving averages, Financial Data

multiple dimensions, Multiple dimensions

multiprocessing module, multiprocessing

mutability, Lists

N

ndarray class, Vectorization with NumPy

Newton scheme, Implied Volatilities

noisy data, Noisy data

normality tests, Normality Tests–Real-World Data

benchmark case, Benchmark Case

importance of, Normality Tests

normality assumption, Benchmark Case

overview of, Statistics, Conclusions

real-world data, Real-World Data

Numba library, Dynamic Compiling–Binomial Option Pricing

NumbaPro library, Generation of Random Numbers on GPUs

numexpr library, Python Paradigms and Performance

NumPy

benefits of, The Scientific Stack

concatenate function, Variance Reduction

data structures, NumPy Data Structures–Structured Arrays

date-time information support in, NumPy

importing, Approximation

Monte Carlo simulation with, Vectorization with NumPy