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Book synopsis

Beyond Black-Scholes: Barrier, Asian, and American Options with Monte Carlo and PDE Method

Vanilla options are only the beginning. In today's global markets, traders and quants rely on exotic derivatives, barrier, Asian, lookback, and American options-to structure deals, hedge complex exposures, and capture hidden opportunities.

Exotic Options and Advanced Pricing Models with Python is your complete guide to understanding, modeling, and implementing these instruments using modern quantitative methods and real Python code. Whether you're a quant professional or a self-taught trader, this book equips you with the tools to expand your skillset and compete at the highest levels of options trading.

What You'll Learn

• Exotic Payoffs Demystified: Barrier, Asian, lookback, chooser, and more explained with clarity.

• Numerical Pricing Techniques: Binomial/trinomial trees, finite difference methods (PDE/FDM), and lattice models.

• Monte Carlo Simulations: Path-dependent pricing for complex derivatives.

• Volatility Surface Integration: Modeling skew, smile, and term structure.

• Python Implementation: Step-by-step code for pricing exotic contracts and validating results.

Tools and Frameworks Covered

• Python (NumPy, Pandas, SciPy, Matplotlib)

• Monte Carlo engines for path-dependent options

• PDE solvers for American and early-exercise features

• Data handling for volatility surfaces and market calibration

Who This Book Is For

• Traders looking to go beyond vanilla calls and puts

• Quantitative analysts expanding into exotic derivatives

• Python developers breaking into quantitative finance

• Risk managers seeking better hedging models

Book details

• Full title: Exotic Options and Advanced Pricing Models with Python
• Subtitle: Beyond Black-Scholes: Barrier, Asian, and American Options with Monte Carlo and PDE Methods
• Author: Hayden Van Der Post, Alice Schwartz
• Language: English
• Binding: Paperback
• Number of pages: 672
• EAN: 9798268329148
• ID: 50558454
• Publisher: Independently published
• Weight: 1148 g
• Dimensions: 254 × 178 × 34 mm
• Date of publishing: 03. October 2025

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