Return and volatility spillovers among global assets: Comparing health crisis with geopolitical crisis

This study investigates the dynamic mechanism across equity, cryptocurrency, and commodity markets before and during health and geopolitical crisis (Covid-19 and the Ukrainian war). We apply the (TVP-VAR) based extended joint connectedness methodology, to understand return and volatility connectedness of financial markets for 2010–2023 period. The empirical results indicate that spillovers were particularly high during the Covid-19 and Russia-Ukraine war. First, health and geopolitical risks considerably impact the return and volatility system. Second, the value of total joint connectedness during the COVID-19 period was greater than during Russia-Ukraine war crisis. Also, evidence suggests that Commodity markets, received the highest shocks from other markets after Russia-Ukraine war and wheat was the main commodity receiving chocks from both health and geopolitical crisis. Our findings indicate that spillover channels differ depending on the type of crisis. Specifically, low-frequency components are the main transmission channels during the health crisis, whereas high-frequency components are the main transmission channels during the geopolitical crisis. Finally, results indicate that, cryptocurrency markets played some minor role in transmitting risks between markets. Our results are important in understanding how assets affect return and volatility spillover during geopolitical and health crises and are of particular importance to policymakers, market regulators, investors, and portfolio managers.

Sustainable development in natural resources industry: is geopolitical risk a catalyst for corporate excess cash holdings?

With the outbreak of the Russia-Ukraine conflict, combined with the COVID-19 epidemic and the Federal Reserve's interest rate hike, geopolitical risks have increased sharply, which has brought great pressure on the sustainable development of natural resources industry. This study aims to discuss the impact of geopolitical risk (GPR) on corporate excess cash holdings in China's natural resources industry. The findings suggest that GRP can encourage enterprises in the natural resources industry to hold more excess cash. The findings still hold with a suite of robustness tests. The study also evidences that the above effect is more significant for state-owned enterprises, enterprises in the mining industry, and large-scale enterprises. Finally, further results show that with the increase of GPR, enterprises with strong risk-taking capacity tend to hold more excess cash, while enterprises registered in higher market-oriented regions are inclined to retain less excess cash. These findings can conduce to a deep understanding of the influence of GPR on corporate excess cash holdings and serve as a reference for policy-makers to adjust policies. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

An application of QVAR dynamic connectedness between geopolitical risk and renewable energy volatility during the COVID-19 pandemic and Russia-Ukraine conflicts.

The article is the first to employ a quantile vector autoregression (QVAR) to identify the connectedness between geopolitical risks and energy volatility from January 1, 2015, to April 03, 2023. This paper is also the first to examine the mediating roles of uncertain events like the COVID-19 pandemic and the Russia-Ukraine conflict on this interlinkage. Dynamic connectedness is 29% in the short term and approximately 6% in the long term. Dynamic net total directional connectedness over a quantile also indicates that connectedness is very intense for both highly positive changes (above the 80% quantile) and negative changes (below the 20% quantile). In the short term, the geopolitical risks remained net receivers of shock, but they turned into net shock transmitters during 2020 in the long term. Clean energy, in the short term, transmits shocks to other markets, and it plays the same role in the long term. Crude oil was a net receiver of shocks during COVID-19 and turned into a net transmitter of shocks in early 2022. Dynamic net pairwise directional connectedness over a quantile suggests that uncertain events like the COVID-19 epidemic or the Russia-Ukraine conflict influence the dynamic interlinkages between geopolitical risks and renewable energy volatility and change their roles in the designed system. These findings are critical since they help authorities develop effective policies to lessen the vulnerabilities of these indicators and minimize how widely the renewable and non-renewable energy market is exposed to risk or uncertainty.

Exploration of industrial risk contagion characteristics and mechanism under geopolitical events: evidence from China

Based on the TVP-VAR-DY and TVP-VAR-BK models, this article examines the characteristics and mechanisms of systemic risk contagion in the Chinese industries under geopolitical events by selecting data spans from 1 January 2010 to 31 August 2022. First, dynamic analysis of full-sample risk contagion shows that there is a significant climb in total risk during geopolitical events. Then the static analysis of risk contagion in the full sample specifically shows the correlation between risk contagion and industry chain between the financial and real sectors. Besides, the sub-sample analysis illustrates that during geopolitical events such as the Sino-US Trade War, the COVID-19 Pandemic and the Russia-Ukraine Conflict, Chinese industrial stock indexes show short-term risk spillovers from key industries related to geopolitical events, and gradually spread along the industrial chain in the long run compared to the Chinese ‘Stock Market Crash'. Through further mechanistic tests, we find that the irrational behaviour of investors in the market exacerbates short-term risk contagion, while the financial distress of real firms due to financing constraints exacerbates long-term risk contagion. In addition, geopolitical risk, economic uncertainty, and policy uncertainty as macro variables also have an impact on the short-run and long-run risk contagion. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Time-frequency relationship between energy imports, energy prices, exchange rate, and policy uncertainties in India: Evidence from wavelet quantile correlation approach

This study examined the relationship between energy imports, energy prices, exchange rate, and policy uncertainty over different time-frequency and across various quantiles by employing the wavelet quantile correlation. The findings suggest that the relationship changes over different time-frequencies and across various quantiles. Moreover, during the COVID-19 to neo-normal period, exchange rate and geopolitical risk exhibit a relatively stronger relationship than energy prices and economic policy uncertainty at both lower and higher frequencies across quantiles. Further, the findings suggest that to reduce energy imports, policymakers should adopt different strategies for both shorter and longer time-horizons.

Environmental reverberations of geopolitical risk and economic policy uncertainty resulting from the Russia-Ukraine conflict: A wavelet based approach for sectoral CO2 emissions.

After the COVID-19 pandemic, Russia invaded Ukraine in February 2022, and a natural gas crisis between the European Union (EU) and Russia has begun. These events have negatively affected humanity and resulted in economic and environmental consequences. Against this background, this study examines the impact of geopolitical risk (GPR) and economic policy uncertainty (EPU) caused by the Russia-Ukraine conflict, on sectoral carbon dioxide (CO2) emissions. To this end, the study analyzes data from January 1997 to October 2022 by using wavelet transform coherence (WTC) and time-varying wavelet causality test (TVWCT) approaches. The WTC results show that GPR and EPU reduce CO2 emissions in the residential, commercial, industrial, and electricity sectors, while GPR increases CO2 emissions in the transportation sector during the period from January 2019 to October 2022, which includes Russia-Ukraine conflict. The WTC analysis also indicates that the reduction in CO2 emissions provided by the EPU is higher than that of the GPR for several periods. According to the TVWCT, there are causal impacts of the GPR and the EPU on sectoral CO2 emissions, but the timing of the causal impacts differs between the raw and decomposed data. The results suggest that the EPU has a larger impact on reducing sectoral CO2 emissions during the Ukraine-Russia crisis and that production disruptions due to uncertainty have the greatest impact on reducing CO2 emissions in the electric power and transportation sectors.

Financial Volatility Modeling with the GARCH-MIDAS-LSTM Approach: The Effects of Economic Expectations, Geopolitical Risks and Industrial Production during COVID-19

Forecasting stock markets is an important challenge due to leptokurtic distributions with heavy tails due to uncertainties in markets, economies, and political fluctuations. To forecast the direction of stock markets, the inclusion of leading indicators to volatility models is highly important;however, such series are generally at different frequencies. The paper proposes the GARCH-MIDAS-LSTM model, a hybrid method that benefits from LSTM deep neural networks for forecast accuracy, and the GARCH-MIDAS model for the integration of effects of low-frequency variables in high-frequency stock market volatility modeling. The models are being tested for a forecast sample including the COVID-19 shut-down after the first official case period and the economic reopening period in in Borsa Istanbul stock market in Türkiye. For this sample, significant uncertainty existed regarding future economic expectations, and the period provided an interesting laboratory to test the forecast effectiveness of the proposed LSTM augmented model in addition to GARCH-MIDAS models, which included geopolitical risk, future economic expectations, trends, and cycle industrial production indices as low-frequency variables. The evidence suggests that stock market volatility is most effectively modeled with geopolitical risk, followed by industrial production, and a relatively lower performance is achieved by future economic expectations. These findings imply that increases in geopolitical risk enhance stock market volatility further, and that industrial production and future economic expectations work in the opposite direction. Most importantly, the forecast results suggest suitability of both the GARCH-MIDAS and GARCH-MIDAS-LSTM models, and with good forecasting capabilities. However, a comparison shows significant root mean squared error reduction with the novel GARCH-MIDAS-LSTM model over GARCH-MIDAS models. Percentage decline in root mean squared errors for forecasts are between 39% to 95% in LSTM augmented models depending on the type of economic indicator used. The proposed approach offers a key tool for investors and policymakers.

The effect of oil implied volatility and geopolitical risk on GCC stock sectors under various market conditions

The importance of crude oil volatility and geopolitical risk for stock pricing is well known in both developed and emerging economies, but is relatively understudied in major oil-exporting countries at the sectoral level of stock indices and under various market conditions. Using daily data on eight Gulf Cooperation Council (GCC) stock sector indices over the period February 2010–30 June 2022, we capture the effect of two global risk factors, namely oil implied volatility and geopolitical risk, on stock returns and volatility while accounting for bull/bear markets and low/high volatility regimes. The analysis indicates the following results. Firstly, the effect of oil implied volatility is stronger than that of geopolitical risk, notably for Consumer Discretionary and Staples. Secondly, the effect on both returns and volatility is generally positive during bull markets, but it is stronger for volatility;the response of the returns of Energy, Materials, Industrials, and Financials is negative in bear markets and positive during bull markets. Thirdly, the effect of oil implied volatility on stock sector volatility is slightly higher during the COVID-19 outbreak for some cases and is prominent during bull markets. Our findings matter for the predictability of GCC stock sector returns and volatility and for the design of hedging strategies under various market states. © 2023 Elsevier B.V.

Impact of geo-political risk on stocks, oil, and gold returns during GFC, COVID-19, and Russian–Ukraine War

The study uses wavelet power spectrum and wavelet coherence transformation methodologies to examine how geopolitical risk affected the returns on stocks, oil, and gold during the GFC, COVID-19, and Russia-Ukraine war-three disruptive events that affected the world's financial markets. For better diversification benefits during the turbulent times, we further investigate the degree of co-movement in frequency and time domains. We observe that GPR has high variations during Russia-Ukraine war period compared to COVID-19 period and is shown to have least variation during the GFC period. WTI crude oil and DJGI indexes are observed to have high variations during GFC, and COVID-19 periods followed by Russia-Ukraine war. We further observe that GOLD offers better diversification opportunity as well as leading movement against WTI and DJGI during disruptive events in financial markets. The results provide new understanding of how geopolitical risk affects financial assets for international investors, fund managers, and regulators, which would further aid to find risky and safer haven possibilities during the turmoil periods. © 2023 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

Heterogeneity of investor sentiment, geopolitical risk and economic policy uncertainty: do Islamic banks differ during COVID-19 pandemic?

Purpose: This study examined the impact of;COVID-19 investor sentiment, COVID-19 cases, geopolitical risk (GPR), economic policy uncertainty (EPU), oil returns and Islamic banking on bank stock returns. In addition, it examined whether Islamic bank stock returns differed from conventional banks when interacting with selected variables. Design/methodology/approach: This study consisted of 137 conventional and Islamic stock market listed banks in 16 Middle East and North Africa (MENA) countries from February 2020 to July 2021. Monthly data were used for bank stock returns, number of COVID-19 cases, COVID-19 investor sentiment, oil price and EPU, while GPR data were obtained annually. This paper used unconditional quantile regression (UQR) in its analysis. Findings: COVID-19 investor sentiment and EPU negatively influenced bank stock returns. However, oil returns were only positive and significant in first quantile. Conversely, GPR negatively impacted bank returns up to the median quantile, while the impact was positive in upper quantiles. Islamic banks outperformed conventional banks in all quantiles. Additionally, GPR negatively influenced Islamic bank returns up to 75th quantile, while oil returns negatively impacted Islamic bank returns up to 95th quantile. Ultimately, COVID-19 investor sentiment and EPU positively influenced Islamic bank returns up to 95th quantile. Practical implications: Market conditions must be considered when implementing investment decisions and policies, as the effects of market shocks are mostly asymmetrical. For example, it is important for international investors to take into consideration asymmetric factors, such as market uncertainty in oil market. Especially in bearish Islamic markets, bad news concerning uncertainty can be perceived as riskier than good news. Social implications: A change in health sentiment, such as COVID-19 cases and COVID-19 investor sentiment, can be used to determine future direction of conventional and Islamic stock markets. Asymmetric effects associated with market news can make portfolio management more effective. COVID-19 investor sentiment states can be used to predict Islamic market index dynamics in MENA region. Originality/value: This paper offered insight into heterogeneity of market conditions and dependencies of Islamic banks' stock market returns on COVID-19 investor sentiment and uncertainty, among others that should be considered when implementing investment decisions and policies. © 2023, Emerald Publishing Limited.

The impact of geopolitical risk on cash holdings policy: evidence from an emerging market

Purpose: This study aims to examine whether geopolitical risk (GPR) impacts the cash holdings behavior of 210 Turkish firms between 2005 and 2019. The authors choose Turkey as a country of interest because Turkey has an important place in terms of geographical location and serves as a bridge between Europe and Asia. Considering the prominent role that can play in decision-making processes, the authors thought that analyzing the impact of GPR on the cash holdings determinants of Turkish firms would be important and interesting. A widely accepted view is that GPRs play an important role in the economic decisions of emerging countries, such as Turkey. Design/methodology/approach: The authors examine models with fixed effects (FE), random effects (RE) and pooled ordinary least squares (POLS), respectively. First, the authors analyzed whether POLS, FE or RE would be the most appropriate model. According to the F-test and the Breusch–Pagan LM test, the FE and the RE models are more suitable than POLS. Then, according to the Hausman test results, the authors found that FE is this study's most appropriate model. After determining the validity of FE, the diagnostics tests of heteroscedasticity, autocorrelation and serial correlation tests are examined. Due to the presence of these problems, Driscoll and Kraay's (1998) test, which is the robust standard error estimator, is used. Findings: The authors find a positive relationship between GPR and cash holdings after controlling firm-level control variables. Firms faced with uncertainty prefer to hoard cash as a precautionary measure. In keeping with real options theory, firms postpone the investments of firms under uncertain conditions. The use of alternative measurements for GPR and cash holdings ensures the validity of our results. The authors' research reveals that investors and politicians should pay more attention to the influence of GPR on the determinants of the cash holdings of firms. Research limitations/implications: There are limitations for this study, but this study may provide opportunities for further studies. First, this study has only data from Turkey. This situation mitigates cross-country effects. In future studies, the number of firms, countries of focus and time span can be expanded. Second, this study does not consider the period of coronavirus disease 2019 (COVID-19) that increased risk and uncertainty worldwide. Further studies may consider the impact of COVID-19 and geographical risks relating to cash holdings. Third, the authors try to choose more relied independent and control variables. Practical implications: The authors' results provide some insights that are relevant to practitioners and policymakers. Managers need to consider GPR in managers' financial decisions based on managers' firm-specific characteristics. Turkish policymakers should target improving policies to alleviate the negative effects of GPRs. Regulators should postulate more encouraging policies to firms in an environment of GPR. Regulators can give firms more time to understand and analyze the GPRs and the impacts of GPRs to adjust regulators' day-to-day activities. Originality/value: There are fewer studies in the literature that analyzed the relationship between GPR and cash holdings. This study aims to full this gap in the literature. © 2023, Emerald Publishing Limited.

A wavelet analysis of dynamic connectedness between geopolitical risk and renewable energy volatility during the COVID-19 pandemic and Ukraine-Russia conflicts.

The study explores inter-relations between the geopolitical risk index and renewable energy volatility index at frequency dimensions from April 4, 2019, to June 13, 2022, using novel multivariate wavelet analysis approaches, such as partial wavelet coherency and partial wavelet gain. Our method allows us to study these interlinkages at various time frequencies. We also consider the influences of uncertain events like the COVID-19 pandemic and Ukraine-Russia conflicts on their interconnectedness. The multiple coherencies between the geopolitical risk index and the green energy sector suggest four cycles in the low-frequency range (50-130 days) from March 2020 to October 2021 and from February 2022 to June 2022. The partial coherency between the geopolitical risk index and renewable energy volatility index suggests connectedness between renewable energy dynamics and geopolitical risks during the COVID-19 duration and the Russia-Ukraine conflict. The partial wavelet coherency of the volatility of green bonds and geopolitical risks suggests that alterations in green bonds caused alterations in geopolitical risks, and the association is negative from February 2021 to April 2021. Both indicators are in-phase with geopolitical risks pushing from February 2020 to April 2020 and from October 2021 to the end of the sample. The partial coherence between clean energy and geopolitical risk suggests geopolitical risks pushing anti-phase connectedness from September 2020 to September 2022. Our findings help policymakers design the most effective policies to lessen the vulnerabilities of these indicators and reduce the spread of risk or uncertainty across them by having insightful knowledge about the primary antecedents of the contagions among these indicators.

The dynamics of oil prices, uncertainty measures and unemployment: a time and frequency approach

PurposeThis study investigates the nexus between the returns on oil prices (OP) and unemployment (UR) while taking into account the influences of two of the most representative measures of uncertainty, the Baker et al. (2016) and Caldara and Iacovello (2021) indexes of economic policy uncertainty (EP) and geopolitical risks (GP), in the relationship.Design/methodology/approachThe authors use data on the US, Canada, France, Italy, Germany and Japan from January 2000 to February 2022 and the UK from January 2000 to December 2021. The authors then apply the continuous wavelet transform (CWT), wavelet coherence (WC), partial wavelet coherence (PWC) and multiple wavelet coherence (MWC) to examine the returns within a time and frequency framework.FindingsThe CWT tracks the movement and evolution of individual return series with evidence of high variances and heterogenous tendencies across frequencies that also align with critical events such as the GFC and COVID-19 pandemic. The WC reveals the presence of a bidirectional relationship between OP and UR across economies, showing that the two variables affect each other. The authors' findings establish the predictive influence of oil price on unemployment in line with theory and also show that the variation in UR can impact the economy and alter the dynamics of OP. The authors employ the PWC and MWC to capture the impact of uncertainty indexes in the co-movement of oil price and unemployment in line with the theory of "investment under uncertainty". Taking into account the common effects of EP and GP, PWC finds that uncertainty measures significantly drive the co-movement of oil prices and unemployment. This result is robust when the authors control for the influence of economic activity (proxied by the GDP) in the co-movement. Furthermore, the MWC reveals the combined intensity, strength and significance of both oil prices and the uncertainty measures in predicting unemployment across countries.Originality/valueThis study investigates the relationship between oil prices, uncertainty measures and unemployment under a time and frequency approach.

Geopolitical risk and the Saudi stock market: Evidence from a new wavelet packet multiresolution cross-causality

Recently, due to OPEC Plus cutting oil production, geopolitical tensions have escalated between the United States and Saudi Arabia. We explore the relationship between geopolitical risk and the Saudi stock market, developing a deep cross-causality approach based on wavelet methodology. Our sample includes Brexit, COVID-19, and the Russian–Ukrainian war. We identify causal patterns especially during times of crisis, evidencing one-way causality of geopolitical factors impacting the Saudi market. Scholars and policymakers will be interested in the sensitivity of the Saudi market to geopolitical risk. © 2023 Elsevier Inc.

Dynamic connectedness among climate change index, green financial assets and renewable energy markets: Novel evidence from sustainable development perspective

This paper investigates the connectedness among the climate change index, green financial assets, renewable energy markets, and geopolitical risk index from June 1, 2012 to June 13, 2022, using Quantile Vector Autoregressive (QVAR) and wavelet coherence (WC). The Total connectedness index (TCI) varies as long as the highest TCI originates in the upper quantile. We also note that the higher TCI decreases after the second wave of COVID19 and increases during the first 100 days of the Russia-Ukraine conflict. Moreover, the results show that Geopolitical risk (GPR) is a net transmitter of the climate change index during the Russian invasion of Ukraine. The green bond and clean energy markets are negatively connected to the GPR at extreme 10 th and 90 th quantiles. The wavelet coherence confirms the QVAR results that the climate change market can be a safe haven against GPR during the Russian invasion. The climate change index, green financial assets, and clean energy are strong influencers in the financial markets and are vital to international peace, reducing geopolitical risk. The study reports a few novel conclusions and implications from a sustainable development perspective.

Geopolitical risk and the Saudi stock market: Evidence from a new wavelet packet multiresolution cross-causality

Recently, due to OPEC Plus cutting oil production, geopolitical tensions have escalated between the United States and Saudi Arabia. We explore the relationship between geopolitical risk and the Saudi stock market, developing a deep cross-causality approach based on wavelet methodology. Our sample includes Brexit, COVID-19, and the Russian-Ukrainian war. We identify causal patterns especially during times of crisis, evidencing one-way causality of geopolitical factors impacting the Saudi market. Scholars and policymakers will be interested in the sensitivity of the Saudi market to geopolitical risk.

Investment in renewable energy and electricity output: Role of green finance, environmental tax, and geopolitical risk: Empirical evidence from China

The global financial downturn induced by COVID-19 has hampered the effectiveness of renewable energy developments, impeding the accomplishment of the United Nations' sustainable development targets. Green finance is a significant means for promoting renewable energy investment and achieving sustainability. Using data from 2012 to 2021 from fifty energy firms in China, this study highlights the starring part of geopolitical risk, green finance, and environmental tax in investment in renewable energy (IRE) sources. It also investigated how IRE impacts the studied firms' electricity output. The data were analyzed through quantile regression and dynamic analysis techniques. The results indicated that green financing and environmental tax significantly impact IRE sources with 0.137*** and 0.428*** beta values, respectively. However, geopolitical risk significantly impedes such projects. Similarly, IRE significantly increases the electricity output of Chinese energy firms. This research is unique in the sense of studying green financing, geopolitical risk, and environmental tax nexus in renewable energy investments leading to electricity generation, which shows a pivotal role in achieving environmental sustainability and provides valuable insights to environmentalists and policymakers to design and implement ecological strategies leading to achieving sustainable development goals.

Role of sustainable finance, geopolitical risk and economic growth in renewable energy investment: Empirical evidence from China

The global economic recession caused by COVID-19 has posed a severe threat to the feasibility of renewable energy projects, hampering the United Nation (UN) sustainable development goals. Sustainable financing (SF) is a crucial instrument for promoting investment in renewable energy (IRE) sources, as it is regarded as a crucial aspect in achieving long-term sustainability. This study sheds insight on the impact of SF, geopolitical risk (GPR), economic growth (EG), and environmental regulation (ER) on IRE sources by evaluating 10 years of data from 35 Chinese energy businesses from 2012 to 2021. The data analysis is done by utilizing quantile regression and dynamic analytic techniques, demonstrating that SF, EG, and ER have a significant positive effect on IRE sources. However, GPR has a significant detrimental impact on IRE in China. This is one of the early studies to examine the crucial role of SF, GPR, EG, and ER in IRE, which is critical for environmental sustainability. In addition, it provides policymakers and environmentalists with crucial insights for developing and executing environmental strategies that can deliver long-term benefits and meet SD goals.

Uncertainty measures and inflation dynamics in selected global players: a wavelet approach.

This study investigates the dynamic relationship between economic policy uncertainty (EPU), geopolitical risks (GPR), the interaction of EPU and GPR (EPGR), and inflation in the USA, Canada, the UK, Japan, and China. We employ the continuous wavelet transform (CWT) to track the evolution of model variables and the wavelet coherence (WC) to examine the co-movement and lead-lag status of the series across different frequencies and time. To strengthen the WC, we apply the multiple wavelet coherence (MWC) to determine how good the linear combination of independent variables co-moves with inflation across various time-frequency domains. The CWT reveals heterogeneous characteristics in the evolution of each variable across frequencies. Inflation across samples shows strong variance in the short-term and medium-term while the volatility fizzles out in the long-term. For the explanatory variables, a similar pattern holds for EPU except for Japan and China, where coherence is evident in the short-term. The USA's and Canada's GPR reveal strong coherence in the short- and medium-term. Also, the UK and China reflect strong coherence in the short-term but weak significance in the medium-term, while Japan's GPR reflects only strong coherence in the short-term. The EPGR shows strong variation in the short-and-medium-term in the samples except in China. The WC's phase-difference reflects bidirectional causalities and switches in signs among series across different scales and periods in the samples, while the MWC reveals the combined intensity, strength, and significance of both EPU and GPR in predicting inflation across frequency bands among the countries. Findings also show significant co-movement among series at date-stamped periods, corroborating critical global events such as the Asian financial crisis, Global financial crisis, and COVID-19 pandemic. The paper has policy implications.

A connectedness analysis among BRICS’s geopolitical risks and the US macroeconomy

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.