Anonymous shelf assessment
Quantitative Finance with Python: An Object-Oriented Approach
Shelf score 7.5 / 10
On Quantitative Finance with Python: An Object-Oriented Approach · Dylan Toscano · John Wiley & Sons
Published 23 March 2026
This book provides an object-oriented approach to quantitative finance using Python.
Overview
Published in 2018 by John Wiley & Sons, this text is aimed at intermediate readers with a focus on financial applications. It covers essential topics such as portfolio optimization, option pricing, and backtesting, making it a practical resource for traders and quants.
The book emphasizes the use of object-oriented programming in Python to develop quantitative finance applications and trading systems. This approach is particularly beneficial for those looking to implement systematic trading strategies or enhance their financial modelling skills.
While the book is rich in practical systems and applications, it assumes a foundational knowledge of Python, which may limit its accessibility to complete beginners. It is best suited for individuals already familiar with programming concepts who wish to deepen their understanding of finance through technology.
By area & interest
Target Audience
The book is specifically tailored for quants, traders, and technologists who are looking to leverage Python in their financial analyses.
Practical Applications
It provides hands-on guidance in areas such as portfolio optimization and option pricing, making it a valuable resource for real-world financial decision-making.
Technical Requirements
Readers should possess an intermediate understanding of Python, as the book does not cover basic programming concepts.
Basis of this assessment
The assessment is based on the catalogue description and topics, highlighting its practical applications and target audience.
Strengths
The book excels in its practical approach to quantitative finance, offering valuable insights into financial applications and trading systems using Python.
Limitations
Its assumption of intermediate Python knowledge may exclude beginners who lack programming experience.
Ideal reader
Ideal readers include finance professionals and students who have a solid grasp of Python and wish to apply it in quantitative finance contexts.