Risk Models for Crypto Assets: Fundamental vs. PCA
This analysis compares fundamental factor models with principal component analysis (PCA) for risk modeling in digital assets. If you're managing a crypto portfolio, discover which approach better captures market risk and enhances portfolio performance.
Risk Models for Crypto Assets: Fundamental vs. PCA
Introduction
This analysis compares fundamental factor models with principal component analysis (PCA) for risk modeling in digital assets. If you're managing a crypto portfolio, discover which approach better captures market risk and enhances portfolio performance.
Abstract: This analysis compares factor models and principal component analysis (PCA) for building risk models for digital assets. We explore the benefits of PCA, such as orthogonal factors and reduced over-fitting, as well as its potential to serve as an alternative to factor models. We provide an overview of multifactor models and describe two different models. We present the PCA model's R-squared by components and compare the first component to market return. Additionally, we compare the in-sample and out-of sample performance of both models and present bias statistics.
Download the full paper to find out which approach is more promising for constructing risk models for digital assets.
*Note: Cloudwall and the technology behind its Serenity System were acquired by Talos in April 2024. Learn more.
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