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

Performance measures


To compare the performance of mutual functions or individual stocks, we need a performance measure. In finance, we know that investors should seek a trade-off between risk and returns. It might not be a good idea to say that portfolio A is better than portfolio B since the former offered us a 30% return last year while the latter offered just 8%. The obvious reason is that we should not ignore risk factors. Because of this, we often hear the phrase "risk-adjusted return". In this section, the Sharpe ratio, Treynor ratio, Sortino ratio, and Jensen's alpha will be discussed. The Sharpe ratio is a widely used performance measure and it is defined as follows:

Here, is the mean return for a portfolio or a stock, is the mean return for a risk-free security, σ is the variance of the excess portfolio (stock) return, and VaR is the variance of the excess portfolio (stock) return. The following code is used to estimate the Sharpe ratio with a hypothetical risk-free rate:

import...