Asset Pricing under uncertainty
type: Dataset
description: We study the effect of parameter uncertainty on a stochastic diffusion model, in particular the impact on the pricing of contingent claims, using methods from the theory of Dirichlet forms. We apply these techniques to hedging procedures in order to compute the sensitivity of SDE trajectories with respect to parameter perturbations. We show that this analysis can justify endogenously the presence of a bid-ask spread on the option prices. We also prove that if the stochastic differential equation admits a closed form representation then the sensitivities have closed form representations. We examine the case of log-normal diffusion and we show that this framework leads to a smiled implied volatility surface coherent with historical data.
issued: 2026-05-24T18:12:13.417495
language: en
modified: 2026-05-24T18:12:13.417501
contact point: Organization
  fn: CCSD
keyword: ams-60h30-91b16-and-91b70
keyword: bid-ask-spread
keyword: dynamic-hedging
keyword: error-theory-using-dirichlet-forms
keyword: infoeu-reposemanticspreprint
keyword: mathmath-prmathematics-mathprobability-mathpr
keyword: preprints-working-papers-
keyword: stochastic-differential-equations
keyword: uncertainty
keyword: value-at-risk
landing page: https://hal.science/hal-00679037

Asset Pricing under uncertainty
type: Distribution
format: HTML
issued: 2026-05-24T18:12:13.488068
modified: 2026-05-24T18:12:13.383634
access URL: https://hal.science/hal-00679037

test_moissonnage_selune
type: Agent