Identification of Atlas models
Robert Fernholz

TL;DR
This paper presents a method to identify parameters of Atlas models, which are systems of rank-dependent Ito processes, by analyzing the variance of the top-ranked process over various sampling intervals.
Contribution
The paper introduces a novel approach to parameter identification in Atlas models using variance measurements at different sampling intervals.
Findings
Parameters can be identified from variance measurements.
Method applies to simple Atlas models.
Effective for different sampling intervals.
Abstract
Atlas models are systems of Ito processes with parameters that depend on rank. We show that the parameters of a simple Atlas model can be identified by measuring the variance of the top-ranked process for different sampling intervals.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStochastic processes and financial applications · Financial Risk and Volatility Modeling · Complex Systems and Time Series Analysis
