Geopolitical Risks and the High-Frequency Movements of the US Term Structure of Interest Rates

We use daily data for the period 25th November, 1985 to 10th March, 2020 to analyse the impact of newspapers-based measures of geopolitical risks (GPRs) on the level, slope and curvature factors derived from the term structure of interest rates of the United States (US) Treasury securities covering maturities of 1 to 30 years. Linear causality tests detect no evidence of predictability of overall GPRs, and the same due to threats and acts. However, statistical tests performed on the linear model provide evidence of structural breaks and nonlinearity, and hence indicate that the Granger causality test results are based on a misspecified framework, and cannot be relied upon. Given this, we use a nonparametric causality in-quantiles test to reconsider the predictive ability of the overall and decomposed GPRs on the three latent factors, with this model being robust to misspecification due to regime changes and nonlinearity, as it is a data-driven approach. Moreover, this framework allows us to capture the entire conditional distribution of the level, slope and curvature factors, and hence can accommodate, via the lower quantiles, the zero lower bound situation seen in our sample period. Using this robust model, we find overwhelming evidence of causality from the GPRs, with relatively stronger effects from threats than acts, for the entire conditional distribution of the three factors, with higher impacts on medium- and long-run maturities, i.e., curvature and level factors, suggesting the predictability of the entire US term structure based on information contained in GPRs. Our results have important implications for academics, investors and policymakers.