Pathwise functional calculus and applications to continuous-time finance (PhD thesis)
Candia Riga

TL;DR
This thesis introduces a pathwise functional calculus framework for analyzing continuous-time trading strategies and hedging robustness without relying on probabilistic models, extending classical results to path-dependent derivatives.
Contribution
It develops a non-anticipative functional calculus approach for defining gains and self-financing conditions pathwise, enabling model-free analysis of hedging strategies for path-dependent derivatives.
Findings
Pathwise formula for hedging error of path-dependent derivatives
Conditions for robustness of delta hedging strategies
Discontinuities in the underlying worsen hedging performance
Abstract
This thesis develops a mathematical framework for the analysis of continuous-time trading strategies which, in contrast to the classical setting of continuous-time finance, does not rely on stochastic integrals or other probabilistic notions. Using the recently developed 'non-anticipative functional calculus', we first develop a pathwise definition of the gain process for a large class of continuous-time trading strategies which include the important class of delta-hedging strategies, as well as a pathwise definition of the self-financing condition. Using these concepts, we propose a framework for analyzing the performance and robustness of delta-hedging strategies for path-dependent derivatives across a given set of scenarios. Our setting allows for general path-dependent payoffs and does not require any probabilistic assumption on the dynamics of the underlying asset, thereby…
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Taxonomy
TopicsStochastic processes and financial applications · Financial Risk and Volatility Modeling · Economic theories and models
