Risk in a Data-Rich Model

March 2026

Risk in a Data-Rich Model

Dario Caldara, Harun Mumtaz, Molin Zhong

Abstract:

We characterize asymmetric tail risk across over one hundred U.S. macroeconomic and financial variables using a dynamic factor model with stochastic volatility. The model unifies growth-at-risk, inflation-at-risk, and sectoral heterogeneity through common factors whose volatility responds endogenously to shocks, combined with heterogeneous factor loadings. We find that asymmetric tail risk is pervasive and heterogeneous: some sectors exhibit severe asymmetry while others show minimal asymmetry, with variation across activity, price, and financial variables. The framework disentangles supply- and demand-driven tail risk dynamics, revealing how the balance of risks shifts across episodes, and identifies where vulnerabilities concentrate across the economy.

Keywords: Dynamic Factor Model, Tail Risk, Stochastic Volatility, Leverage Effect, Growth-at-Risk, Sectoral Heterogeneity

DOI: https://doi.org/10.17016/IFDP.2026.1435

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