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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 1. Section 1: Getting Started with Python
2. Overview of Financial Analysis with Python 3. Section 2: Financial Concepts
4. The Importance of Linearity in Finance 5. Nonlinearity in Finance 6. Numerical Methods for Pricing Options 7. Modeling Interest Rates and Derivatives 8. Statistical Analysis of Time Series Data 9. Section 3: A Hands-On Approach
10. Interactive Financial Analytics with the VIX 11. Building an Algorithmic Trading Platform 12. Implementing a Backtesting System 13. Machine Learning for Finance 14. Deep Learning for Finance 15. Other Books You May Enjoy

The Importance of Linearity in Finance

Nonlinear dynamics play a vital role in our world. Linear models are often employed in economics due to being easier to study and their easier modeling capabilities. In finance, linear models are widely used to help price securities and perform optimal portfolio allocation, among other useful things. One significant aspect of linearity in financial modeling is its assurance that a problem terminates at a globally-optimal solution.

In order to perform prediction and forecasting, regression analysis is widely used in the field of statistics to estimate relationships among variables. With an extensive mathematics library being one of Python’s greatest strength, Python is frequently used as a scientific scripting language to aid in these problems. Modules such as the SciPy and NumPy packages contain a variety of linear regression functions...

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