Kernel-Based Algorithms for Efficient Pricing, Stress Testing, and Time Series Modeling in Finance

This paper introduces novel kernel-based algorithms that demonstrate the relevance and effectiveness of reproducing kernel Hilbert space (RKHS) techniques for three key applications in finance: asset pricing, reverse stress testing, and time series modeling.