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  • Financial Theory with Python: A Gentle Introduction

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Financial Theory with Python: A Gentle Introduction

by Yves Hilpisch (Author) Format: Paperback
4.3 out of 5 stars (38)

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Nowadays, finance, mathematics, and programming are intrinsically linked. This book provides the relevant foundations of each discipline to give you the major tools you need to get started in the world of computational finance.

Using an approach where mathematical concepts provide the common background against which financial ideas and programming techniques are learned, this practical guide teaches you the basics of financial economics. Written by the best-selling author of Python for Finance, Yves Hilpisch, Financial Theory with Python explains financial, mathematical, and Python programming concepts in an integrative manner so that the interdisciplinary concepts reinforce each other.

  • Draw upon mathematics to learn the foundations of financial theory and Python programming
  • Learn about financial theory, financial data modeling, and the use of Python for computational finance
  • Leverage simple economic models to better understand basic notions of finance and Python programming concepts
  • Use both static and dynamic financial modeling to address fundamental problems in finance, such as pricing, decision-making, equilibrium, and asset allocation
  • Learn the basics of Python packages useful for financial modeling, such as NumPy, pandas, Matplotlib, and SymPy

Read more
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  1. ISBN-10
    1098104358
  2. ISBN-13
    978-1098104351
  3. Edition
    1st
  4. Publisher
    O'Reilly Media
  5. Publication date
    November 2, 2021
  6. Language
    English
  7. Dimensions
    6.75 x 0.5 x 8.75 inches
  8. Print length
    201 pages
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From the Publisher

Financial Theory with Python

Target Audience

I have written a number of books about Python applied to finance. My company, The Python Quants, offers a number of live and online training classes in Python for finance. For all of my previous books and the training classes, the book readers and training participants are expected to already have some background knowledge in both finance and Python programming or a similar language.

This book starts completely from scratch, with just the expectation that the reader has some basic knowledge in mathematics, in particular from calculus, linear algebra, and probability theory. Although the book material is almost self-contained with regard to the mathematical concepts introduced, an introductory mathematics book like Mathematics for Economists (2016) by Pemberton and Rau is recommended for further details if needed.

Given this approach, this book targets students, academics, and professionals alike who want to learn about financial theory, financial data modeling, and the use of Python for computational finance. It is a systematic introduction to the field on which to build through more advanced books or training programs.

Readers with a formal financial background will find the mathematical and financial elements of the book rather simple and straightforward. On the other hand, readers with a stronger programming background will find the Python elements rather simple and easy to understand.

Even if the reader does not intend to move on to more advanced topics in computational finance, algorithmic trading, or asset management, the Python and finance skills acquired through this book can be applied beneficially to standard problems in finance, such as the composition of investment portfolios according to modern portfolio theory (MPT). This book also teaches, for example, how to value options and other derivatives by standard methods such as replication portfolios or risk-neutral finance.

This book is also suitable for executives in the financial industry who want to learn about the Python programming language as applied to finance. On the other hand, it can also be read by those already proficient in Python or another programming language who want to learn more about the application of Python in finance.

Financial Theory with Python: A Gentle Introduction
Python for Finance: Mastering Data-Driven Finance
Python for Algorithmic Trading: From Idea to Cloud Deployment
Artificial Intelligence in Finance: A Python-Based Guide
Reinforcement Learning for Finance: A Python-Based Introduction
Customer Reviews
4.3 out of 5 stars 38
4.6 out of 5 stars 323
4.4 out of 5 stars 151
4.5 out of 5 stars 66
5.0 out of 5 stars 4
Also by Yves Hilpisch A Gentle Introduction Mastering Data-Driven Finance From Idea to Cloud Deployment A Python-Based Guide A Python-Based Introduction

Editorial Reviews

About the Author

Dr. Yves J. Hilpisch is the founder and CEO of The Python Quants (http://home.tpq.io), a group focusing on the use of open source technologies for financial data science, artificial intelligence, algorithmic trading, and computational finance. He is also the founder and CEO of The AI Machine (http://aimachine.io), a company focused on AI-powered algorithmic trading based on a proprietary strategy execution platform.

Yves has a Diploma in Business Administration, a Ph.D. in Mathematical Finance, and is Adjunct Professor for Computational Finance.

Yves is the author of five books (https://home.tpq.io/books):

Artificial Intelligence in Finance (O’Reilly, forthcoming) Python for Algorithmic Trading (O’Reilly, forthcoming) Python for Finance (2018, 2nd ed., O’Reilly) Listed Volatility and Variance Derivatives (2017, Wiley Finance) Derivatives Analytics with Python (2015, Wiley Finance)

Yves is the director of the first online training program leading to University Certificates in Python for Algorithmic Trading (https://home.tpq.io/certificates/pyalgo) and Computational Finance (https://home.tpq.io/certificates/compfin). He also lectures on computational finance, machine learning, and algorithmic trading at the CQF Program (http://cqf.com).

Yves is the originator of the financial analytics library DX Analytics (http://dx-analytics.com) and organizes Meetup group events, conferences, and bootcamps about Python, artificial intelligence, and algorithmic trading in London (http://pqf.tpq.io), New York (http://aifat.tpq.io), Frankfurt, Berlin, and Paris. He has given keynote speeches at technology conferences in the United States, Europe, and Asia.

Product details

  • Publisher ‏ : ‎ O'Reilly Media
  • Publication date ‏ : ‎ November 2, 2021
  • Edition ‏ : ‎ 1st
  • Language ‏ : ‎ English
  • Print length ‏ : ‎ 201 pages
  • ISBN-10 ‏ : ‎ 1098104358
  • ISBN-13 ‏ : ‎ 978-1098104351
  • Item Weight ‏ : ‎ 2.31 pounds
  • Dimensions ‏ : ‎ 6.75 x 0.5 x 8.75 inches
  • Best Sellers Rank: #531,823 in Books (See Top 100 in Books)
  • Customer Reviews:
    4.3 out of 5 stars (38)

About the author

Follow authors to get new release updates, plus improved recommendations.
Yves J. Hilpisch

Yves J. Hilpisch

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Full content visible, double tap to read brief content.

Dr. Yves J. Hilpisch is founder and CEO of The Python Quants (http://tpq.io), a group focusing on the use of open source technologies for financial data science, artificial intelligence, algorithmic trading, and computational finance. He is also the founder and CEO of The AI Machine (http://aimachine.io), a company focused on AI-powered algorithmic trading based on a proprietary strategy execution platform.

Yves has a Diploma in Business Administration, a Ph.D. in Mathematical Finance and is Adjunct Professor for Computational Finance.

Yves is the author of five books (https://home.tpq.io/books):

* Artificial Intelligence in Finance (O’Reilly, forthcoming)

* Python for Algorithmic Trading (O’Reilly, forthcoming)

* Python for Finance (2018, 2nd ed., O’Reilly)

* Listed Volatility and Variance Derivatives (2017, Wiley Finance)

* Derivatives Analytics with Python (2015, Wiley Finance)

Yves is the director of the first online training program leading to University Certificates in Python for Algorithmic Trading (https://home.tpq.io/certificates/pyalgo) and Computational Finance (https://home.tpq.io/certificates/compfin). He also lectures on computational finance, machine learning, and algorithmic trading at the CQF Program (http://cqf.com).

Yves is the originator of the financial analytics library DX Analytics (http://dx-analytics.com) and organizes Meetup group events, conferences, and bootcamps about Python, artificial intelligence and algorithmic trading in London (http://pqf.tpq.io), New York (http://aifat.tpq.io), Frankfurt, Berlin, and Paris. He has given keynote speeches at technology conferences in the United States, Europe, and Asia.

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