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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

Author (1):

Yuxing Yan

View More author details

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

Summary

In this chapter, we have discussed one of the most important properties of Python: modules. A module is a package written by an expert or any individual to serve a special purpose. The knowledge related to modules is essential in our understanding of Python and its application to finance. In particular, we have introduced and discussed the most important modules, such as NumPy, SciPy, matplotlib, statsmodels, pandas, and pandas_reader. In addition, we have briefly mentioned module dependency and other issues. Two financial calculators written in Python were also presented. In Chapter 3, Time Value of Money, we will discuss many basic concepts associated with finance, such as the present value of one future cash flow, present value of perpetuity, present value of growing perpetuity, present value of annuity, and formulas related to future values. In addition, we will discuss definitions of Net Present Value (NPV), Internal Rate of Return (IRR), and Payback period. After that, several...

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