Abstract:  I will present a framework for hedging a portfolio of exotic derivatives using modern kernel methods for time series. Parameterizing hedging strategies as points in the RKHS of carefully designed operator-valued kernels, I will explain how the solution to the original stochastic optimisation problem can be provably recovered by solving a ridge regression on observed market trajectories.

Bio: Since 2021, Cris Salvi has been a member of the Department of Mathematics at Imperial College London, first as a Chapman Postdoctoral Fellow and now as an Assistant Professor. He is also affiliated with Imperial-X, Imperial’s flagship institute for AI and data science. Prior to this, he completed his PhD at the University of Oxford under the supervision of Prof. Terry Lyons.

Meeting Recording: https://ucsb.zoom.us/rec/share/DBar81cquXgZTOEiSZOFvUYxIV6RvDWD3yKx9oB1TLdBaQcyEJjZprjf0xWtW276.KYfqSPDTj7Rr3TRH

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