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Python for Finance Cookbook

You're reading from Python for Finance Cookbook Over 50 recipes for applying modern Python libraries to financial data analysis

Product type Paperback

Published in Jan 2020

Publisher Packt

ISBN-13 9781789618518

Length 432 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Data Analysis

Author (1):

Eryk Lewinson

View More author details

Table of Contents (12) Chapters

Preface

1. Financial Data and Preprocessing

2. Technical Analysis in Python FREE CHAPTER

3. Time Series Modeling

4. Multi-Factor Models

5. Modeling Volatility with GARCH Class Models

6. Monte Carlo Simulations in Finance

7. Asset Allocation in Python

8. Identifying Credit Default with Machine Learning

9. Advanced Machine Learning Models in Finance

10. Deep Learning in Finance

11. Other Books You May Enjoy

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Pricing American options using Quantlib

In the previous recipe, we showed how to manually code the Longstaff-Schwartz algorithm. However, we can also use already existing frameworks for valuation of derivatives. One of the most popular ones is QuantLib. It is an open source C++ library that provides tools for the valuation of financial instruments. By using Simplified Wrapper and Interface Generator (SWIG), it is possible to use QuantLib from Python (and some other programming languages, such as R or Julia). In this recipe, we show how to price the same American put option that we priced in the Pricing American options with Least squares Monte Carlo recipe, but the library itself has many more interesting features to explore.

How to do it...

...

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Authors (1)

Eryk Lewinson

Eryk Lewinson

Eryk Lewinson received his master's degree in Quantitative Finance from Erasmus University Rotterdam. In his professional career, he has gained experience in the practical application of data science methods while working in risk management and data science departments of two "big 4" companies, a Dutch neo-broker and most recently the Netherlands' largest online retailer. Outside of work, he has written over a hundred articles about topics related to data science, which have been viewed more than 3 million times. In his free time, he enjoys playing video games, reading books, and traveling with his girlfriend.

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