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267294991
Options Pricing with Python: Master option pricing and apply Python to quantitative finance, trading, and risk management
Item #:
267294991
XCD 165
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- Begin your professional options trading journey by learning the principles, creating methods, and using Python to thrive in the volatile trading marketKey FeaturesMaster option pricing with Python using Black-Scholes, binomial and trinomial trees, and Monte Carlo simulationDecode implied volatility and option Greeks to analyze sensitivities, valuation, and riskApply option pricing across asset classes through real-world case studies, machine learning applications, portfolio optimization, and risk managementPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionMaster 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 learnMaster Black-Scholes option pricing with PythonBuild binomial, trinomial, and Monte Carlo modelsApply option pricing across FX, equity, rates, commodities, and other asset classesDecode implied volatility and volatility modelsUnderstand option Greeks and risk sensitivitiesPractice trading strategies, hedging, and portfolio optimizationPrice exotic options using numerical methodsApply machine learning techniques to options pricing and risk analysisWho this book is forThis 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 ContentsIntroduction to Options TradingOptions Types and Trading FundamentalsGathering and Preparing DataBlack-Scholes Closed-Form PricingBinomial and Trinomial TreesUnderstanding Monte Carlo SimulationImplied Volatility and Volatility ModelsGreeks and Sensitivity AnalysisExotic Options Pricing ModelsRisk-Neutral Valuation and Numerical MethodsTesting and Evaluating Options Pricing ModelsDesigning 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 PricingBest Practices, AI/ML and Future Trends in Options Pricing
| Publisher | Packt Publishing |
| Publication date | September 18, 2026 |
| Edition | 1st |
| Language | English |
| Print length | 656 pages |
| ISBN-10 | 1807301990 |
| ISBN-13 | 978-1807301996 |
| Item Weight | 2.45 pounds (1.11 kg) |
| Dimensions | 7.5 x 1.48 x 9.25 inches (19.1 x 3.8 x 23.5 cm) |
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