finelybook
Options Pricing with Python: Master option pricing and apply Python to quantitative finance, trading, and risk management
Author(s): Mhamed Bettaieb (Author)
- Publisher Finelybook 出版社: Packt Publishing
- Publication Date 出版日期: September 18, 2026
- Edition 版本: 1st
- Language 语言: English
- Print length 页数: 656 pages
- ISBN-10: 1807301990
- ISBN-13: 9781807301996
Book Description
Begin your professional options trading journey by learning the principles, creating methods, and using Python to thrive in the volatile trading market
Key Features
- Master option pricing with Python using Black-Scholes, binomial and trinomial trees, and Monte Carlo simulation
- Decode implied volatility and option Greeks to analyze sensitivities, valuation, and risk
- Apply option pricing across asset classes through real-world case studies, machine learning applications, portfolio optimization, and risk management
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description
Master option pricing with Python by turning financial theory into practical pricing models, analysis, and real-world applications.
Learn options trading fundamentals and prepare financial data before implementing Black-Scholes, binomial and trinomial trees, Monte Carlo simulation, implied volatility models, and option Greeks. Advance to exotic options, risk-neutral valuation, and numerical pricing methods while learning how to test and evaluate your models.
Practice what you learn through real-world options pricing across asset classes and machine learning applications. Understand trading strategies, portfolio optimization, hedging, and risk management, and discover how option pricing models fit into quantitative finance and trading workflows.
By the end, you will be able to build, test, and apply Python option pricing models and understand how AI/ML and emerging techniques are shaping the future of quantitative finance.
What you will learn
- Master Black-Scholes option pricing with Python
- Build binomial, trinomial, and Monte Carlo models
- Apply option pricing across FX, equity, rates, commodities, and other asset classes
- Decode implied volatility and volatility models
- Understand option Greeks and risk sensitivities
- Practice trading strategies, hedging, and portfolio optimization
- Price exotic options using numerical methods
- Apply machine learning techniques to options pricing and risk analysis
Who this book is for
This book is for capital markets professionals, quantitative and algorithmic traders, researchers, developers, and finance students who want to master option pricing with Python. Readers will learn to build and test pricing models, analyze implied volatility and Greeks, and apply Python to quantitative finance, trading, portfolio optimization, and risk management.
Table of Contents
- Introduction to Options Trading
- Options Types and Trading Fundamentals
- Gathering and Preparing Data
- Black-Scholes Closed-Form Pricing
- Binomial and Trinomial Trees
- Understanding Monte Carlo Simulation
- Implied Volatility and Volatility Models
- Greeks and Sensitivity Analysis
- Exotic Options Pricing Models
- Risk-Neutral Valuation and Numerical Methods
- Testing and Evaluating Options Pricing Models
- Designing Options Strategies, Optimizing Portfolios, and Managing Risk
- Real-World Case Study: Option Valuation Differences Across Asset Classes
- Real-World Case Study: Machine Learning Applications in Options Pricing
- Best Practices, AI/ML and Future Trends in Options Pricing
Editorial Reviews
Editorial Reviews
Review
“An excellent book to build your expertise in options markets with Python. The author brings extensive professional experience to the field, combining solid quantitative concepts with valuable knowledge and real-world insights. A highly recommended resource for anyone looking to expand their skills in options pricing.”
Dr. Naoual Amrouche, Author of Technology-Driven Business Strategy, Associate Professor at LIU
“Mhamed Bettaieb’s book, Options Pricing with Python, is a carefully laid-out treatment of the now widely established basics of real-world options valuation implementations, from data setup and coding, to understanding the output of option models, with tested samples throughout.
Avoiding algebra and stochastic calculus derivations, the book acts as a practical, focused guide, enabling a wide range of readers from desk analysts to risk managers, from buy-side hedge funds to sell-side banks, and even beginner personal account traders, to bring a range of proven, useful option models, from the Black-Scholes formula to the SABR model and beyond, into production and add value as quickly as possible.”
Robert L. Navin, PhD, Founder of Real Time Risk Systems, Author of The Mathematics of Derivatives: Tools for Designing Numerical Algorithms
About the Author
Mhamed Bettaieb, a capital markets and derivatives expert, has 28+ years of experience in risk management, portfolio management, trading, and consulting. With an MSc in Finance, CFA, FRM, and NFA Series 3, he’s a derivatives valuation specialist skilled in algo trading and derivatives portfolios dynamic hedging. As the Founder and CEO of Cap Bon Consulting, Mhamed has led numerous derivatives system implementations and consulted for global financial institutions. His career includes roles at Mizuho, Credit Suisse, Mitsui, Nomura, AEGON, Barclays Capital, CDPQ, Santander, Bear Stearns, MUSI, ABN, Natexis, JPM, BMO, Accenture, KPMG, NBC, and BT.
