首页Python for Finance - Second Edition
Understand the fundamentals of Python data structures and work with time-series data Implement key concepts in quantitative finance using popular Python libraries such as NumPy, SciPy, and matplotlib A step-by-step tutorial packed with many Python programs that will help you learn how to apply Python to finance
Python for Finance
Apply powerful finance models and quantitative analysis
BIRMINGHAM - MUMBAI
Python for Finance
Copyright © 2017 Packt Publishing
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First published: April 2014
Second edition: June 2017
Production reference: 1270617
Published by Packt Publishing Ltd.
35 Livery Street
Birmingham B3 2PB, UK.
Dr. Param Jeet
Nabih Ibrahim Bawazir, M.Sc.
Content Development Editor
Shweta H Birwatkar
About the Author
Yuxing Yan graduated from McGill University with a PhD in nance. Over the
years, he has been teaching various nance courses at eight universities: McGill
University and Wilfrid Laurier University (in Canada), Nanyang Technological
University (in Singapore), Loyola University of Maryland, UMUC, Hofstra
University, University at Buffalo, and Canisius College (in the US).
His research and teaching areas include: market microstructure, open-source nance
and nancial data analytics. He has 22 publications including papers published in
the Journal of Accounting and Finance, Journal of Banking and Finance, Journal
of Empirical Finance, Real Estate Review, Pacic Basin Finance Journal, Applied
Financial Economics, and Annals of Operations Research.
He is good at several computer languages, such as SAS, R, Python, Matlab, and C.
His four books are related to applying two pieces of open-source software to nance:
Python for Finance (2014), Python for Finance (2nd ed., expected 2017), Python for
Finance (Chinese version, expected 2017), and Financial Modeling Using R (2016).
In addition, he is an expert on data, especially on nancial databases. From 2003 to
2010, he worked at Wharton School as a consultant, helping researchers with their
programs and data issues. In 2007, he published a book titled Financial Databases
(with S.W. Zhu). This book is written in Chinese.
Currently, he is writing a new book called Financial Modeling Using Excel — in an
R-Assisted Learning Environment. The phrase "R-Assisted" distinguishes it from
other similar books related to Excel and nancial modeling. New features include
using a huge amount of public data related to economics, nance, and accounting;
an efcient way to retrieve data: 3 seconds for each time series; a free nancial
calculator, showing 50 nancial formulas instantly, 300 websites, 100 YouTube
videos, 80 references, paperless for homework, midterms, and nal exams; easy to
extend for instructors; and especially, no need to learn R.
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