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Mastering Python for Finance

You're reading from   Mastering Python for Finance Implement advanced state-of-the-art financial statistical applications using Python

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789346466
Length 426 pages
Edition 2nd Edition
Languages
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Author (1):
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James Ma Weiming James Ma Weiming
Author Profile Icon James Ma Weiming
James Ma Weiming
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Table of Contents (16) Chapters Close

Preface 1. Section 1: Getting Started with Python
2. Overview of Financial Analysis with Python FREE CHAPTER 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

Modeling Interest Rates and Derivatives

Interest rates affect economic activities at all levels. Central banks, including the Federal Reserve (informally known as the Fed), target interest rates as a policy tool to influence economic activity. Interest rate derivatives are popular with investors who require customized cash flow needs or specific views on interest-rate movements.

One of the key challenges that interest-rate derivative traders face is to have a good and robust pricing procedure for these products. This involves understanding the complicated behavior of an individual interest-rate movement. Several interest-rate models have been proposed for financial studies. Some common models studied in finance are the Vasicek, CIR, and Hull-White models. These interest-rate models involve modeling the short-rate and rely on factors (or sources of uncertainty) with most of them...

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