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
