ABSTRACT
Based on the TVP-VAR (time-varying parameter vector autoregressive) based extended joint connectedness methodology, this study analyzes the joint connectedness among BRICS’s (Brazil, Russia, India, China, and South Africa) geopolitical risks and the US macro economy (interest rates, consumer price index, crude oil prices, stock prices, and gross domestic production) for return and volatility. Evidence suggests that shocks from geopolitical risks have a considerable impact on emerging economies. Emerging economies are closely linked to developed economies in today’s globalized world. Hence, the geopolitical risk of BRICS countries may further impact developed economies. In this study, we performed a cross-sectional analysis of the relationships between geopolitical risks in BRICS nations and a developed economy (e.g., US macroeconomic indicators). Our results were significant in at least two ways. First, geopolitical risks in China and Russia considerably impact the return and volatility system. In contrast, geopolitical risks in China have fewer impacts on the US macro economy than in Russia, Brazil, and India. Second, the value of total joint connectedness during the COVID-19 period was greater than during the 2007–2008 global financial crisis. Third, the consumer price index, crude oil prices, and stock prices receive greater connectedness from the others. The results suggest that policymakers and investors should not pay excessive attention to geopolitical risk in China. Moreover, because the oil and stock markets are highly interdependent, risk spikes for investors who hold both oil and stock when facing high geopolitical risk. We recommend that investors reduce their simultaneous holdings of both assets in times of high geopolitical risk and consider alternative safe haven assets.
ABSTRACT
This study analyzes the connectedness effect among the News Headlines Sentiment Index (SI), Infectious Disease Equity Market Volatility Tracker (IDEMV), financial markets (financial stress (FS), crude oil future prices (WTI)), and macroeconomic indicators (economic index (WEI), 1-Month Treasury Constant Maturity rate (R)) for returns and volatility in the US. We employ a mixed approach consisting of the Diebold-Yilmaz framework in static analysis and time-varying parameter vector autoregressive (TVP-VAR) model in dynamic analysis. The most noteworthy findings of this study are that there is a strong interdependence between SI, IDEMV, and WEI, and that SI and IDEMV have greater contributions to WEI compared to its impact on FS, R, and WTI for the return system, but not for volatility.