Python for Finance Illustrated Edition
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About This Book
- Estimate market risk, form various portfolios, and estimate their variance-covariance matrixes using real-world data
- Explains many financial concepts and trading strategies with the help of graphs
- A step-by-step tutorial with many Python programs that will help you learn how to apply Python to finance
Who This Book Is For
Python for Finance is perfect for graduate students, practitioners, and application developers who wish to learn how to utilize Python to handle their financial needs. Basic programming knowledge is helpful, but not necessary.
What You Will Learn
- Build a financial calculator based on Python
- Learn how to price various types of options such as European, American, average, lookback, and barrier options
- Write Python programs to download data from Yahoo! Finance
- Estimate returns and convert daily returns into monthly or annual returns
- Form an n-stock portfolio and estimate its variance-covariance matrix
- Estimate VaR (Value at Risk) for a stock or portfolio
- Run CAPM (Capital Asset Pricing Model) and the Fama-French 3-factor model
- Learn how to optimize a portfolio and draw an efficient frontier
- Conduct various statistic tests such as T-tests, F-tests, and normality tests
In Detail
Python is a free and powerful tool that can be used to build a financial calculator and price options, and can also explain many trading strategies and test various hypotheses. This book details the steps needed to retrieve time series data from different public data sources.
Python for Finance explores the basics of programming in Python. It is a step-by-step tutorial that will teach you, with the help of concise, practical programs, how to run various statistic tests. This book introduces you to the basic concepts and operations related to Python. You will also learn how to estimate illiquidity, Amihud (2002), liquidity measure, Pastor and Stambaugh (2003), Roll spread (1984), spread based on high-frequency data, beta (rolling beta), draw volatility smile and skewness, and construct a binomial tree to price American options.
This book is a hands-on guide with easy-to-follow examples to help you learn about option theory, quantitative finance, financial modeling, and time series using Python.
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Product details
- Publisher : Packt Publishing; Illustrated edition (April 25, 2014)
- Language : English
- Paperback : 408 pages
- ISBN-10 : 1783284374
- ISBN-13 : 978-1783284375
- Item Weight : 1.54 pounds
- Dimensions : 7.5 x 0.92 x 9.25 inches
- Best Sellers Rank: #3,668,903 in Books (See Top 100 in Books)
- #409 in Business Accounting Software Computer
- #419 in Personal Finance Software (Books)
- #1,551 in Mathematical & Statistical Software
- Customer Reviews:
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Learn more how customers reviews work on AmazonReviewed in the United States on February 5, 2020
Top reviews from the United States
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It is, however, a great read if you are familiar with doing a lot of finance in another language like R and want to transition to python. With bloomberg providing a python API and C++ still being a real pain the rear this is a good way for more "analyst" types to become much more fluent and competent using a vastly more flexible language. It is not mega detailed - basically a "crash through" approach to doing a bit of python and doing it quickly. This is by no means a standalone solution to anything.
The best use of this book is in conjunction with something more rigorous for finance and python. Aside from that it could be put to good use in an undergrad finance class so that instead of messing around in excel people actually learn a bit of code that they can build on later.
Nevertheless, I am working through the book at my own pace as time allows. In spite of its shortcomings, I could give the book a cautiously lukewarm recommendation.
I picked up this book on a whim after reading about Quant Finance and figured it would be fun to play around with some of the basic tools of the trade.
I would say this book is suitable for Masters students in Finance, Financial Engineering or similar. It covers some interesting subjects such as Monte Carlo simulators and options.
The book could have done with a bit better editing. Some of the topics are repeated unnecessarily. I don't blame the author here, but more poor editing.
Pros:
Fun introduction to the subject
Cons:
Some of the information seems to be repeated
that a book is published and the program samples have herrors and dont run ....
Reviewed in the United States on February 5, 2020
that a book is published and the program samples have herrors and dont run ....
Top reviews from other countries
Easy to follow.









