Python for Finance: Analyze Big Financial Data

conda package manager, Anaconda

configure_traits method, Short Rate Class with GUI

constant short rate, Constant Short Rate

constrained optimization, Constrained Optimization

contingent claims, valuation of, Valuation–American Options

American options, American Options

European options, European Options

continuation value, American Options, Least-Squares Monte Carlo

control structures, Excursion: Control Structures

convenience methods, Basic Analytics

convex optimization, Convex Optimization–Constrained Optimization

constrained, Constrained Optimization

functions for, Calibration Procedure

global, Global Optimization

local, Local Optimization

covariance matrix, The Data

covariances, Normality Tests

Cox-Ingersoll-Ross SDE, Square-root diffusion

Cox-Ross-Rubinstein binomial model, Least-Squares Monte Carlo

credit value adjustment (CVA), Credit Value Adjustments

credit value-at-risk (CVaR), Credit Value Adjustments

CSS (Cascading Style Sheets), Styling

cubic splines, Interpolation

Cython library, Basic Data Types, Static Compiling with Cython

D

data

basic data structures, Basic Data Structures–Sets

basic data types, Basic Data Types–Strings

big data, The Rise of Real-Time Analytics, Input/Output Operations

formats supported by pandas library, I/O with pandas

high frequency, High-Frequency Data

high-frequency, Real-time stock price quotes

missing data, First Steps with DataFrame Class, Basic Analytics