3 papers
cs.LG2026
Online Learning of Scale Parameters in Score-Driven Filters
Fabrizio Lillo, Giulia Livieri, Gianluca Palmari
A score-driven filter multiplies its scaled log-likelihood score by a scale parameter. We call this coefficient the gain and learn it online. Given the current state and realised s…
math.ST2026
Proper-score observation-driven filters: local geometry, estimation, and continuous-time limits
Giulia Livieri, Gianluca Palmari
Observation-driven filters typically use likelihood-score updates, corresponding to the logarithmic scoring rule. We generalise these updates to negative parameter derivatives of d…
math.OC2024
Optimal execution with deterministically time varying liquidity: well posedness and price manipulation
Gianluca Palmari, Fabrizio Lillo, Zoltan Eisler
We investigate the well-posedness in the Hadamard sense and the absence of price manipulation in the optimal execution problem within the Almgren-Chriss framework, where the tempor…