Heydt Mastering Pandas for Finance

Master pandas, an open source Python Data Analysis Library, for financial data analysis
1. Auflage 2025
ISBN: 978-1-78398-511-1
Verlag: De Gruyter
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 298 Seiten

Key FeaturesBook DescriptionIf you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.What you will learn - Modeling and manipulating financial data using the pandas DataFrame
- Indexing, grouping, and calculating statistical results on financial information
- Timeseries modeling, frequency conversion, and deriving results on fixed and moving windows
- Calculating cumulative returns and performing correlations with index and social data
- Algorithmic trading and backtesting using momentum and mean reversion strategies
- Option pricing and calculation of Value at Risk
- Modeling and optimization of financial portfolios
Who this book is forIf you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.

Autoren/Hrsg.

Heydt, Michael

Fachgebiete

• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein

Über Autor(innen)

Heydt Michael :

Michael Heydt is an independent consultant, programmer, educator, and trainer. He has a passion for learning and sharing his knowledge of new technologies. Michael has worked in multiple industry verticals, including media, finance, energy, and healthcare. Over the last decade, he worked extensively with web, cloud, and mobile technologies and managed user experiences, interface design, and data visualization for major consulting firms and their clients. Michael's current company, Seamless Thingies, focuses on IoT development and connecting everything with everything. Michael is the author of numerous articles, papers, and books, such as D3.js By Example, Instant Lucene. NET, Learning Pandas, and Mastering Pandas for Finance, all by Packt. Michael is also a frequent speaker at.NET user groups and various mobile, cloud, and IoT conferences and delivers webinars on advanced technologies.