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Python for Finance

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

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787125698
Length 586 pages
Edition 2nd Edition
Languages
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Author (1):
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Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Table of Contents (17) Chapters Close

Preface 1. Python Basics FREE CHAPTER 2. Introduction to Python Modules 3. Time Value of Money 4. Sources of Data 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

What is a Python module?

A module is a package or group of programs that is written by an expert, user, or even a beginner who is usually very good in a specific area, to serve a specific purpose.

For example, a Python module called quant is for quantitative financial analysis. quant combines two modules of SciPy and DomainModel. The module contains a domain model that has exchanges, symbols, markets, and historical prices, among other things. Modules are very important in Python. In this book, we will discuss about a dozen modules implicitly or explicitly. In particular, we will explain five modules in detail: NumPy, SciPy, matplotlib, statsmodels, and Pandas.

Note

As of November 16, 2016, there are 92,872 Python modules (packages) with different areas available according to the Python Package Index.

For the financial and insurance industries, there are 384 modules currently available.

Assume that we want to estimate the square root of 3 by using the sqrt() function. However, after issuing...

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