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 usually use the likelihood score, tying their updates to the logarithmic scoring rule. We study recursions driven instead by the negative parameter deriv…
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…