ETF Risk Models

ArXiv ID: 2110.07138 “View on arXiv”

Authors: Unknown

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.

Keywords: ETF risk models, Multilevel taxonomy, Risk factors, Heterotic risk model, Constituent data, ETFs

Complexity vs Empirical Score

• Math Complexity: 7.0/10
• Empirical Rigor: 4.0/10
• Quadrant: Lab Rats
• Why: The paper introduces advanced mathematical frameworks like heterotic risk models and discusses factor covariance matrix construction with detailed formulas, but lacks concrete backtesting results, performance metrics, or implementation-specific data.

  flowchart TD
    A["Research Goal: Build ETF Risk Models"] --> B{"Select Classification Type"}
    B -->|Binary| C1["Heterotic Risk Model"]
    B -->|Non-Binary| C2["General Risk Model"]
    
    D["ETF Constituent Data"] --> E["Construct Multilevel ETF Taxonomy"]
    E --> B
    
    C1 --> F["Risk Factor Definition"]
    C2 --> F
    
    F --> G["Compute ETF Risk Models"]
    G --> H["Key Findings: Improved Risk Measurement & Taxonomy Framework"]