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Mastering Python for Finance. - Second Edition

You're reading from  Mastering Python for Finance. - Second Edition

Product type Book
Published in Apr 2019
Publisher Packt
ISBN-13 9781789346466
Pages 426 pages
Edition 2nd Edition
Languages
Author (1):
James Ma Weiming James Ma Weiming
Profile icon James Ma Weiming

Table of Contents (16) Chapters

Preface Section 1: Getting Started with Python
Overview of Financial Analysis with Python Section 2: Financial Concepts
The Importance of Linearity in Finance Nonlinearity in Finance Numerical Methods for Pricing Options Modeling Interest Rates and Derivatives Statistical Analysis of Time Series Data Section 3: A Hands-On Approach
Interactive Financial Analytics with the VIX Building an Algorithmic Trading Platform Implementing a Backtesting System Machine Learning for Finance Deep Learning for Finance Other Books You May Enjoy

Root-finding algorithms

In the preceding section, we discussed some nonlinear models commonly used for studying economics and financial time series. From the model data given in continuous time, the intention is therefore to search for the extrema that could possibly infer valuable information. The use of numerical methods, such as root-finding algorithms, can help us find the roots of a continuous function, f, such that f(x)=0, which can either be the maxima or the minima of the function. In general, an equation may either contain a number of roots or none at all.

One example of the use of root-finding methods on nonlinear models is the Black-Scholes implied volatility modeling discussed earlier, in The implied volatility model section. An option trader would be interested in deriving implied prices based on the Black-Scholes model and comparing them with market prices. In the...

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