The aim of this thesis project is to make further progress in the development of advanced mathematical methods, working with applications at the interplay between mathematics and finance. Specifically, develop new methods in stochastic control theory including Hida-Malliavin calculus, white noise theory and functional analysis, with applications to optimal portfolio, pricing and risk assessments, extend the mathematical finance models, including stock price models, to make them more realistic. In particular, I will do this by developing calculus for other types of stochastic processes, including processes with jumps, mean-field and memory, study stochastic Volterra integral partial equations with space interactions, this topic is important for applications in biology such as population dynamics and epidemiology, use machine learning techniques and numerical approximations to solve the problems explicitly
An advanced level degree; A completed undergraduate program of at least 240 credits, including 60 credits at the advanced level; Or the equivalent knowledge obtained in or outside of Sweden
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