Dmitrii Silvestrov, Stockholms universitet: Optimal Stopping and Convergence for American Type Options
The lecture presents a survey of the latest results on optimal option pricing for modulated price processes achieved by the author and his collaborators. These results are: discovery of multi-threshold structure of optimal stopping strategies for American option models with general convex payoffs and formulation of conditions, which implicate multi- and one-threshold structures for optimal stopping strategies; introduction and investigation of new models of multivariate price processes modulated by semi-Markov market indices; obtaining of skeleton approximations, uniform with respect to a perturbation parameter, for continuous- and discrete-time option pricing models; finding of new effective general conditions for convergence of optimal expected reward functionals for American type options for multivariate price processes modulated by semi-Markov market indices; constructing new Monte Carlo algorithms for pricing of options based on information about structure of optimal stopping domains and effective binomial-trinomial approximation algorithms for evaluation of optimal reward functionals for American type options for exponential multivariate diffusion price processes. The latest achievements are connected with stochastic models for reselling of options and optimal option pricing for mean-reverse models used to describe stochastic dynamics of energy prices. New directions for further research studies in the area will be also discussed.
Tillbaka till huvudsidan.