3 papers
q-fin.TR2025
Kernel Learning for Mean-Variance Trading Strategies
Owen Futter, Nicola Muca Cirone, Blanka Horvath
In this article, we develop a kernel-based framework for constructing dynamic, pathdependent trading strategies under a mean-variance optimisation criterion. Building on the theore…
stat.ML2025
Signature Maximum Mean Discrepancy Two-Sample Statistical Tests
Andrew Alden, Blanka Horvath, Zacharia Issa
Maximum Mean Discrepancy (MMD) is a widely used concept in machine learning research which has gained popularity in recent years as a highly effective tool for comparing (finite-di…
cs.LG2024
Scalable Signature-Based Distribution Regression via Reference Sets
Andrew Alden, Carmine Ventre, Blanka Horvath
Distribution Regression (DR) on stochastic processes describes the learning task of regression on collections of time series. Path signatures, a technique prevalent in stochastic a…