Proper-Score Observation-Driven Filters: Local Geometry, Estimation, and Continuous-Time Limits

By Giulia Livieri, Gianluca Palmari

Published 2026-09-01

Everscope rating

1318.1

Relevance to quantitative trading

8 / 10

Implementation complexity

7 / 10

Reproducibility

4 / 5

About this paper

Methodology: Proper-Score Observation-Driven Filtering. Problem types: Time Series Forecasting, Risk Management, Density Estimation, Volatility Modeling, Robust Filtering, Stochastic Approximation, Continuous-Time Limit Analysis, Misspecification Analysis.

arXiv:2608.02828 · Paper rankings

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