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Mastering Python for Finance

You're reading from   Mastering Python for Finance Understand, design, and implement state-of-the-art mathematical and statistical applications used in finance with Python

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Product type Paperback
Published in Apr 2015
Publisher Packt
ISBN-13 9781784394516
Length 340 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (12) Chapters Close

Preface 1. Python for Financial Applications FREE CHAPTER 2. The Importance of Linearity in Finance 3. Nonlinearity in Finance 4. Numerical Procedures 5. Interest Rates and Derivatives 6. Interactive Financial Analytics with Python and VSTOXX 7. Big Data with Python 8. Algorithmic Trading 9. Backtesting 10. Excel with Python Index

Newton's method


Newton's method, also known as the Newton-Raphson method, uses an iterative procedure to solve for a root using information about the derivative of a function. The derivative is treated as a linear problem to be solved. The first-order derivation of the function represents the tangent line. The approximation to the next value of , given as , is as follows:

Here, the tangent line intersects the axis at , which produces . This also represents the first-order Taylor expansion about such that that the new point solves the following equation:

This process is repeated with taking the value of until the maximum number of iterations is reached, or the absolute difference between and is within an acceptable accuracy level.

An initial guess value is required to compute the values of and . The rate of convergence is quadratic, which is considered to be extremely fast in obtaining the solution with high levels of accuracy.

The drawback to Newton's method is that it does not guarantee...

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