Paper: arXiv 2601.21447

Authors: Demetrio Lacava, Edoardo Otranto

Abstract

This paper investigates the impact of Trade Policy Uncertainty (TPU) on stock-bond correlation dynamics in the United States. Using daily data on major U.S. stock indices and the 10-year Treasury bond from 2015 to 2025, we estimate correlation within a two-step GARCH-based framework, relying on multivariate specifications, including Constant Conditional Correlation (CCC), Smooth Transition Conditional Correlation (STCC), and Dynamic Conditional Correlation (DCC) models. We extend these frameworks by incorporating TPU index and a presidential dummy to capture effects of trade uncertainty and government cycles. The findings show that constant correlation models are strongly rejected in favor of time-varying specifications. Both STCC and DCC models confirm TPU’s central role in driving correlation dynamics, with significant differences across political regimes. DCC models augmented with TPU and political effects deliver the best in-sample fit and strongest forecasting performance, as measured by statistical and economic loss functions.

Complexity vs Empirical Score

  • Math Complexity: 5.5/10
  • Empirical Rigor: 7.5/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper applies well-established multivariate GARCH frameworks (DCC, STCC) and extends them to model stock-bond correlations by incorporating trade policy uncertainty and political cycle variables. It exhibits solid empirical evaluation using in-sample fit and out-of-sample loss functions across a relevant modern dataset.

Research Flowchart

  flowchart TD
    A[Research Goal: Assess Trade Policy Uncertainty <br>impact on U.S. Stock-Bond Correlations] --> B[Data Inputs: Daily U.S. Stock Indices, <br>10Y Treasury Bonds, TPU Index, & Political Dummy <br> 2015-2025]
    B --> C[Methodology: Estimate Two-Step GARCH Models <br> CCC, STCC, and DCC]
    C --> D[Computational Augmentation: Incorporate <br>TPU Index & Presidential Dummy into Correlations]
    D --> E[Model Evaluation: Compare Fit & Forecasting <br>via Statistical & Economic Loss Functions]
    E --> F[Key Outcome: Constant models rejected; TPU & Regime-Augmented <br>DCC provides superior fit & forecasting]

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