Hidden Risks and Optionalities in American Options
Noura El Hassan, Bacel Maddah, and Nassim N. Taleb

TL;DR
This paper introduces a stochastic framework for better capturing hidden risks and optionalities in American options, addressing limitations of traditional deterministic models.
Contribution
It presents a novel heuristic method that incorporates stochasticity into key inputs, improving the assessment of early-exercise flexibility and convexity.
Findings
Enhanced risk quantification in American options
More accurate pricing of early-exercise features
Addresses underestimation issues in conventional models
Abstract
We develop a practical framework for identifying and quantifying the hidden layers of risks and optionality embedded in American options by introducing stochasticity into one or more of their underlying determinants. The heuristic approach remedies the problems of conventional pricing systems, which treat some key inputs deterministically, hence systematically underestimate the flexibility and convexity inherent in early-exercise features.
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Taxonomy
TopicsStochastic processes and financial applications · Risk and Portfolio Optimization · Capital Investment and Risk Analysis
