Mastering Python for Finance

by James Ma Weiming

Understand, design, and implement state-of-the-art mathematical and statistical applications used in finance with PythonAbout This BookExplore financial models used by the industry and ways of solving them with this guideDiscover the various features that Python provides for scientific computing and harness them to enhance your financial applicationsBuild state-of-the-art infrastructure for critical aspects such as modeling, trading, pricing, and analyticsWho This Book Is ForIf you are an undergraduate or graduate student, a beginner to algorithmic development and research, or a software developer in the financial industry who is interested in using Python for quantitative methods in finance, this is the book for you. It would be helpful to have a bit of familiarity with basic Python usage, but no prior experience is required.

What You Will LearnPerform interactive computing with IPython NotebookSolve linear equations of financial models and perform ordinary least squares regressionExplore nonlinear modeling and solutions for optimum points using root-finding algorithms and solversDiscover different types of numerical procedures used in pricing optionsModel fixed-income instruments with bonds and interest ratesManage big data with NoSQL and perform analytics with HadoopBuild a high-frequency algorithmic trading platform with PythonCreate an event-driven backtesting tool and measure your strategiesIn DetailBuilt initially for scientific computing, Python quickly found its place in finance. Its flexibility and robustness can be easily incorporated into applications for mathematical studies, research, and software development.

With this book, you will learn about all the tools you need to successfully perform research studies and modeling, improve your trading strategies, and effectively manage risks. You will explore the various tools and techniques used in solving complex problems commonly faced in finance.

You will learn how to price financial instruments such as stocks, options, interest rate derivatives, and futures using computational methods. Also, you will learn how you can perform data analytics on market indexes and use NoSQL to store tick data.

Genres: Programming

342 pages, Kindle Edition

First published April 29, 2015

Reviews

[Tadas Talaikis · Rating 2 out of 5]

Little Python, somewhat fragmented and I don't see anything deep from experience or mastery. For example, it has one shallow chapter about MongoDB, but in reality tells nothing. Few months ago I've done experiments trying to find best database for 100+ million rows that need to be written and read in shortest period possible. of financial data.

Guess what, MongoDB is above MySQL, but below Postgres when writing data. First, this book mentions nothing about Postgres, but anyway, how's that related to mastering Python for finance, I don't know, that's just basics.

Second, I've decided over none of databases as the above mentioned task took hours and hours of time. Now this experimental project uses flat pickled files that are processed just by pandas, and task is taking 6 minutes (not just reading and writing, but *everything* from gathering data to start of sending of the signals) vs a day for SQL or NoSQL databases.

And the biggest disadvantage of MongoDB, why I've dropped it, is extremely poor performance with complex queries, 50x worse without some aggregation that some simple Postgres/ MySQL query. So, this long talk was for this point - I suspect this book has no "mastery" in it. There are too much introductory books without intermediary or "mastery", hoped this to be much better.

As for financial parts of the book I mostly didn't understood most of the things, nor I need to, probably.

[Hosein Ramezanpoor · Rating 4 out of 5]

The book contains some good shallow details for people whom like to enter financial analyses.
In my idea one big requirement for readers is strong knowledge in python programming and databases (totally technical side)
The book solved many significant problem about financial definitions and expressions for me overall.