Python for Finance: Analyze Big Financial Data

numpy.linalg sublibrary, Individual basis functions

numpy.random sublibrary, Random Numbers

universal functions, Basic Analytics

writing/reading arrays, Writing and Reading NumPy Arrays

NUTS algorithm, Introductory Example

O

OANDA online broker, Real-time FX data

object orientation, Object Orientation–Cash Flow Series Class

cash flow series class example, Cash Flow Series Class

definition of, Object Orientation

Python classes, Basics of Python Classes

simple short rate class example, Simple Short Rate Class

observation points, Regression, Unsorted data

OpenPyxl library, Using OpenPyxl

operators, Documentation

optimal decision step, The Valuation Class

optimal stopping problems, American Options, Least-Squares Monte Carlo

optimization

constrained, Constrained Optimization

convex, Convex Optimization–Constrained Optimization

global, Global Optimization

local, Local Optimization

option pricing theory, Normality Tests

ordinary least-squares regression (OLS), Regression Analysis, Multiple dimensions,

Least-Squares Monte Carlo

out-of-memory computations, Out-of-Memory Computations

P

pandas library, pandas Basics–GroupBy Operations

basic analytics, Basic Analytics

benefits of, The Scientific Stack, Technical Analysis

data formats supported, I/O with pandas

data sources supported, Financial Data

DataFrame class, First Steps with DataFrame Class–Second Steps with DataFrame