Global Geopolitical Risk and the Long- and Short-Run Impacts on the Returns and Volatilities of US Treasuries

ABSTRACT

We examine the impact of global geopolitical risk (GPR) measures on US Treasuries’ returns and volatilities, differentiating between long- and short-run investment behaviours among an array of time-to-maturities ranging from 1 month to 30 years, taking into account various economic and financial factors. Using monthly data and a panel autoregressive distributed lag (ARDL) model, the results indicate a negative long-run relationship between US Treasuries’ returns and the global GPR index. These results generally hold when we consider geopolitical threats and geopolitical acts, although they exhibit some discrepancies between these two components and across the yield curve. Further results show a positive and strong long-run relationship between the US Treasuries’ realized volatilities and the various geopolitical risk measures. The evidence holds true when we disentangle ‘bad’ from ‘good’ realized volatilities, although the impact of bad volatility is stronger than that of good volatility, which points to an asymmetric effect of realized volatility in US Treasuries. A sub-sample analysis suggests the robustness of the main results. Our analyses provide the first empirical evidence of the information content of GPR for US Treasury securities’ returns and volatilities, which matters to fixed-income investors and decision-makers at the Federal Reserve.

KEYWORDS:

• Global geopolitical risk
• threats and acts
• long- and short-run effects
• returns and volatilities
• US treasuries yield curve

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Notes

1. Another line of literature considers the predictability of the term structure of US interest rates based on crude oil uncertainty (Bouri et al. 2022) and risk aversion (Bouri et al. 2021).

2. https://www.ft.com/content/6f198784-c938-4674-af6f-d760b18fcb2d.

3. We refer the reader to Chudik et al. (2013).

4. Regarding the sum of coefficients and their standard errors, Chudik et al. (2016) propose two methods, the cross-sectionally augmented ARDL (CS-ARDL) and the cross-sectionally augmented distributed lag (CS-DL) estimator. An alternative method is an error correction model (ECM).

5. The Boston Globe, Chicago Tribune, Daily Telegraph, Financial Times, Globe and Mail, Guardian, Los Angeles Times, New York Times, Times, Wall Street Journal, and Washington Post.

6. The set extends that used by Stock and Watson (2005), which has since been used in a number of factor analyses, see, for example, Bai and Ng (2008) and De Mol, Giannone, and Reichlin (2008).

7. Some series need to be transformed to be stationary. In general, real variables are expressed in growth rates, first differences are used for nominal interest rates, and second log differences are used for prices.

8. A close examination of the short-run relationship, especially the third and fourth factors, which are strongly related to prices, reveals statistically significant negative coefficients across Treasury securities groups (or sub-portfolios). It is well known that higher inflation induces higher required yield and negatively impacts Treasury security returns, hence the importance of inflation expectation being closely monitored by market participants, via either 5-year, 5 year forward contracts or 5-year forward 5-year interest rate swaps. The implications of this number go well beyond economics and finance, with important social and political implications.

9. We refer the reader to FOMC November 5^th, 2020 meeting (https://www.federalreserve.gov/monetarypolicy/fomcminutes20201105.htm).