Shifting Correlations: How Trade Policy Uncertainty Alters stock-T bill Relationships

TL;DR

This study investigates how trade policy uncertainty affects the correlation between U.S. stock indices and short-term government bonds, revealing that policy shocks significantly influence market relationships especially under political tensions.

Contribution

It introduces an augmented DCC model incorporating trade policy uncertainty, enhancing the understanding of policy impacts on financial market correlations.

Findings

Trade policy uncertainty significantly affects stock-T bill correlations.

Political conditions amplify the impact of trade shocks on markets.

Enhanced DCC models improve correlation forecast relevance.

Abstract

This paper examines how trade policy uncertainty influences the correlation between U.S. stock indices and short-term government bonds. The objective is to assess whether policy-related shocks, especially those linked to trade tensions, alter the traditional stock-T bill relationship and its implications for investors. We extend the Dynamic Conditional Correlation (DCC) framework by incorporating exogenous variables to account for external shocks. Three specifications are analyzed: one using the Trade Policy Uncertainty (TPU) index, one including a dummy variable reflecting presidential-cycle effects, and one combining both through an interaction term. The analysis is based on daily data for major U.S. stock indices and the 3-month Treasury bill. Results indicate that trade policy uncertainty exerts a significant effect on stock-T bill correlations. Moreover, its influence becomes stronger under specific political conditions, suggesting that political agendas can amplify the impact of trade-related shocks on financial markets. Crucially, augmenting the DCC framework with trade-policy-related variables improves also the economic relevance of correlation forecasts. Therefore, this study contributes to the literature by explicitly integrating policy-related uncertainty into correlation modeling through an augmented DCC framework. The findings provide new insights for portfolio allocation and risk management in environments characterized by heightened trade tensions.