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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

References

Please refer to the following articles:

Carhart, Mark M., 1997, On Persistence in Mutual Fund Performance, Journal of Finance 52, 57-82.
Fama, Eugene and Kenneth R. French, 1993, Common risk factors in the returns on stocks and bonds, Journal of Financial Economics 33, 3056.
Fama, Eugene and Kenneth R. French, 1992, The cross-section of expected stock returns, Journal of Finance 47, 427-465.
String manipulation: http://www.pythonforbeginners.com/basics/string-manipulation-in-python

Appendix A – data case #3 - beta estimation

Objective: hands-on experience to estimate the market risk for a given set of companies:

What are alpha and beta for those companies?
Comment on your results.
Based on your monthly returns, what are the means of annual returns for S&P500 and risk-free rate?
If the expected market return is 12.5% per year and the expected risk-free rate is 0.25% per year, what are the costs of equity for those companies?
What is the portfolio beta?
Computational tool: Python...

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