Book Image

Python for Finance - Second Edition

By : Yuxing Yan
5 (1)
Book Image

Python for Finance - Second Edition

5 (1)
By: Yuxing Yan

Overview of this book

This book uses Python as its computational tool. Since Python is free, any school or organization can download and use it. This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance. The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory, options and futures. This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM’s market risk, running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option.
Table of Contents (23 chapters)
Python for Finance Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Index

Exercises


  1. What is the meaning of CAPM? Is it a linear model?

  2. What are the features of a one-factor linear model?

  3. What are the definitions of total risk and market risk and do you measure them?

  4. Explain the similarity and difference between the following two equations:

  5. What is the relationship between total risk and market risk for a stock?

  6. Who should care about CAPM or what are the usages of the model?

  7. If stock A has a higher market risk than stock B, does it mean that A has a higher expected return as well? Explain.

  8. How do you measure different types of risk?

  9. How do you predict the expected market returns?

  10. If we know the expected market risk premium, how do you predict the cost of equity of a firm?

  11. What is the logic behind the following beta adjustment formula?

  12. Construct a portfolio with unequal weight of 20%, 10%, 30%, 10%, 10%, and 20%. The list of stocks are Walmart (WMT), International Business Machine (IBM), Citi Group (C ), Microsoft (MSFT), Google (GOOG), and Dell (DELL). Estimate their monthly...