ETF Risk Models

TL;DR

This paper presents a method for constructing ETF risk models by developing a multilevel ETF taxonomy and applying heterotic or general risk model techniques based on the taxonomy, leveraging ETF constituent data.

Contribution

It introduces a novel approach to ETF risk modeling by integrating multilevel ETF classifications with heterotic risk models, enhancing risk assessment accuracy.

Findings

Developed a multilevel ETF taxonomy from constituent data.

Applied heterotic risk models to ETF classifications.

Demonstrated improved risk modeling for ETFs.

Abstract

We discuss how to build ETF risk models. Our approach anchors on i) first building a multilevel (non-)binary classification/taxonomy for ETFs, which is utilized in order to define the risk factors, and ii) then building the risk models based on these risk factors by utilizing the heterotic risk model construction of https://ssrn.com/abstract=2600798 (for binary classifications) or general risk model construction of https://ssrn.com/abstract=2722093 (for non-binary classifications). We discuss how to build an ETF taxonomy using ETF constituent data. A multilevel ETF taxonomy can also be constructed by appropriately augmenting and expanding well-built and granular third-party single-level ETF groupings.