Which ETFs Protect Against U.S. Equity Crashes? Regime-Dependent Hedging and Safe-Haven Evidence from DCC-GJR-GARCH

Which liquid ETFs actually protect investors when U.S. equities crash? This paper answers that question using daily observations from 2012-03-02 to 2026-02-27 for SPY and eight cross-asset ETFs spanning gold, oil, broad commodities, the U.S. dollar, Treasuries, real estate, high-yield credit, and investment-grade credit. Pairwise DCC-GJR-GARCH models recover time-varying correlations, and nested downside regressions identify behavior in the lower 10%, 5%, and 1% tails of SPY returns. To prevent an incremental correlation decline from being misclassified as a safe haven, inference is based on HC3-robust Wald tests of the cumulative tail-state correlations. In the full sample, the U.S. dollar and U.S. Treasuries qualify as hedges, while the U.S. dollar and U.S. Treasuries reach statistically negative correlation in at least one downside state. Protection is sharply regime dependent. During COVID-19, effective safe-haven behavior is limited to the U.S. dollar and U.S. Treasuries; during the Russia-Ukraine regime it is observed for the U.S. dollar; and in the tariff window the hedge set narrows to gold and U.S. Treasuries. Across specifications, dollar exposure appears most frequently, while sovereign duration produces the deepest negative dependence in the full sample, COVID-19, and the tariff window. Gold remains episodic, and cyclical ETFs generally retain positive equity dependence. The findings show that hedge and safe-haven labels are state-contingent properties of the cross-asset correlation structure rather than permanent attributes of individual ETFs.

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Journal
Fractals
Published
2026-09-18
DOI
https://doi.org/10.1142/s0218348x26501525
Primary Topic
Market Dynamics and Volatility
Type
article
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article

Which ETFs Protect Against U.S. Equity Crashes? Regime-Dependent Hedging and Safe-Haven Evidence from DCC-GJR-GARCH

Fernando Henrique Antunes de Araujo, Fábio Sandro dos Santos, Kerolly Kedma Felix do Nascimento
Fractals
Market Dynamics and Volatility
article

Which ETFs Protect Against U.S. Equity Crashes? Regime-Dependent Hedging and Safe-Haven Evidence from DCC-GJR-GARCH

Fernando Henrique Antunes de Araujo, Fábio Sandro dos Santos, Kerolly Kedma Felix do Nascimento
article en

Abstract

Which liquid ETFs actually protect investors when U.S. equities crash? This paper answers that question using daily observations from 2012-03-02 to 2026-02-27 for SPY and eight cross-asset ETFs spanning gold, oil, broad commodities, the U.S. dollar, Treasuries, real estate, high-yield credit, and investment-grade credit. Pairwise DCC-GJR-GARCH models recover time-varying correlations, and nested downside regressions identify behavior in the lower 10%, 5%, and 1% tails of SPY returns. To prevent an incremental correlation decline from being misclassified as a safe haven, inference is based on HC3-robust Wald tests of the cumulative tail-state correlations. In the full sample, the U.S. dollar and U.S. Treasuries qualify as hedges, while the U.S. dollar and U.S. Treasuries reach statistically negative correlation in at least one downside state. Protection is sharply regime dependent. During COVID-19, effective safe-haven behavior is limited to the U.S. dollar and U.S. Treasuries; during the Russia-Ukraine regime it is observed for the U.S. dollar; and in the tariff window the hedge set narrows to gold and U.S. Treasuries. Across specifications, dollar exposure appears most frequently, while sovereign duration produces the deepest negative dependence in the full sample, COVID-19, and the tariff window. Gold remains episodic, and cyclical ETFs generally retain positive equity dependence. The findings show that hedge and safe-haven labels are state-contingent properties of the cross-asset correlation structure rather than permanent attributes of individual ETFs.

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Which ETFs Protect Against U.S. Equity Crashes? Regime-Dependent Hedging and Safe-Haven Evidence from DCC-GJR-GARCH — Fernando Henrique Antunes de Araujo, Fábio Sandro dos Santos, et al. · Fractals (2026) | TGRS Research Map | TGRS