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Python for Finance

You're reading from Python for Finance Apply powerful finance models and quantitative analysis with Python

Product type Paperback

Published in Jun 2017

Publisher

ISBN-13 9781787125698

Length 586 pages

Edition 2nd Edition

Languages

Python

Tools

Matplotlib

Concepts

Data Analysis

Table of Contents (17) Chapters

Preface

1. Python Basics FREE CHAPTER

2. Introduction to Python Modules

3. Time Value of Money

4. Sources of Data

Diving into deeper concepts

5. Bond and Stock Valuation

6. Capital Asset Pricing Model

7. Multifactor Models and Performance Measures

8. Time-Series Analysis

9. Portfolio Theory

10. Options and Futures

11. Value at Risk

12. Monte Carlo Simulation

13. Credit Risk Analysis

14. Exotic Options

15. Volatility, Implied Volatility, ARCH, and GARCH

Index

Python modules related to finance

Since this book is applying Python to finance, the modules (packages) related to finance will be our first priority.

The following table presents about a dozen Python modules or submodules related to finance:

Name	Description
`Numpy.lib.financial`	Many functions for corporate finance and financial management.
`pandas_datareader`	Retrieves data from Google, Yahoo! Finance, FRED, Fama-French factors.
`googlefinance`	Python module to get real-time (no delay) stock data from Google Finance API.
`yahoo-finance`	Python module to get stock data from Yahoo! Finance.
`Python_finance`	Download and analyze Yahoo! Finance data and develop trading strategies.
`tstockquote`	Retrieves stock quote data from Yahoo! Finance.
`finance`	Financial risk calculations. Optimized for ease of use through class construction and operator overload.
`quant`	Enterprise architecture for quantitative analysis in finance.
`tradingmachine`	A backtester for financial...

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