Options Pricing with Python: Master option pricing and build profitable trading strategies with Python - Softcover

Mhamed Bettaieb

Softcover

ISBN 10: 1807301990 ISBN 13: 9781807301996

Publisher: Packt Publishing, 2026

Synopsis

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 Python across multiple asset classes through real-world case studies, machine learning applications, portfolio optimization, risk management, and emerging AI/ML trends
• 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

1. Introduction to Options Trading
2. Options Types and Trading Fundamentals
3. Gathering and Preparing Data
4. Black-Scholes Closed-Form Pricing
5. Binomial and Trinomial Trees
6. Understanding Monte Carlo Simulation
7. Implied Volatility and Volatility Models
8. Greeks and Sensitivity Analysis
9. Exotic Options Pricing Models
10. Risk-Neutral Valuation and Numerical Methods
11. Testing and Evaluating Options Pricing Models
12. Designing Options Strategies, Optimizing Portfolios, and Managing Risk
13. Real-World Case Study: Option Valuation Differences Across Asset Classes
14. Real-World Case Study: Machine Learning Applications in Options Pricing
15. Best Practices, AI/ML and Future Trends in Options Pricing

About this title

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.

Edition details

• Publisher: Packt Publishing
• Publication date: 2026
• Language: English
• ISBN 10: 1807301990
• ISBN 13: 9781807301996
• Binding: Paperback
• Edition number: 1
• Number of pages: 656