Hidden Risks and Optionalities in American Options

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.