Probability-free models in option pricing: statistically indistinguishable dynamics and historical vs implied volatility
Damiano Brigo

TL;DR
This paper explores probability-free models in option pricing, demonstrating that both historical and implied volatilities can be understood as pathwise properties, challenging traditional probabilistic frameworks.
Contribution
It connects historical and implied volatility through pathwise, probability-free models, extending previous work with rough paths theory and semimartingale analysis.
Findings
Implied volatility is a pathwise property, not purely statistical.
Models can be constructed without probability, using quadratic variation.
Historical and implied volatility differ fundamentally in their nature.
Abstract
We investigate whether it is possible to formulate option pricing and hedging models without using probability. We present a model that is consistent with two notions of volatility: a historical volatility consistent with statistical analysis, and an implied volatility consistent with options priced with the model. The latter will be also the quadratic variation of the model, a pathwise property. This first result, originally presented in Brigo and Mercurio (1998, 2000), is then connected with the recent work of Armstrong et al (2018, 2021), where using rough paths theory it is shown that implied volatility is associated with a purely pathwise lift of the stock dynamics involving no probability and no semimartingale theory in particular, leading to option models without probability. Finally, an intermediate result by Bender et al. (2008) is recalled. Using semimartingale theory, Bender…
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Taxonomy
TopicsStochastic processes and financial applications · Complex Systems and Time Series Analysis · Forecasting Techniques and Applications
