Geopolitical risks and energy commodities dynamics in G7 economies towards business sustainability

ABSTRACTThe aim of this study is to investigate the impact of geopolitical risk and economic policy uncertainty on natural resource rents for selected MENA countries and Turkey, covering the period 1973–2021. The geopolitical risk index was researched by Caldara and Iacoviello and the World Uncertainty Index was taken from Ahir et al. We used linear and nonlinear ARDL techniques. Results from linear ARDL models document that geopolitical risk has a significant positive effect on natural resource rents in Egypt and Turkey, while it has a negative effect on natural resource rents in Saudi Arabia and Tunisia. When we look at the impact of uncertainty on natural resource rents, we see that increasing uncertainty reduces natural resource rents in all countries except Saudi Arabia. Moreover, the findings of nonlinear ARDL models show that negative and positive shocks in the geopolitical risk and uncertainty index affect natural resource rents in both the short and long term. Our results show that geopolitical risk and economic policy uncertainty can be used to improve models of natural resource markets.

A way to achieve sustainable economic growth in developing countries is to increase investments with domestic savings. However, not every country has an equal opportunity in terms of domestic savings. The desired level of investment expenditures cannot be reached in countries with a savings gap. In this case, foreign direct investment (FDI) becomes more valuable in meeting countries’ investment needs. Nevertheless, companies may not behave very bravely in their investment actions in other countries. There is a considerable risk and uncertainty avoidance in the nature of investment because uncertainty and risk are accepted as harbingers of instability for a country. Since the main goal of companies is to make a profit, they may start thinking that they will not have the opportunity to make a profit in an unstable economy. Hence, the risk perception in the investment environment must be low for developing countries to become attractive for FDI inflows. Geopolitical risks, as well as economic, political, and strategic risks that countries will be exposed to, are important indicators considered in FDI inflows. Literature research shows that investors are aggressive in investing with a profit appetite and, with exceptions, are sensitive to geopolitical risks. In other words, FDI decreases in countries where geopolitical risks tend to increase. The present study tested the validity of this assumption in the literature for Türkiye. The impact of geopolitical risks on FDI was analyzed with the ARDL Boundary Test Approach for the period 1985-2020. FDI inflows were used as the dependent variable, and the Geopolitical Risk (GPR) Index, a measure of geopolitical risk, was used as the independent variable. Moreover, growth, globalization, and inflation are the other independent variables analyzed. The test results demonstrated the negative effect of the increase in the GPR index on FDI inflows. In terms of the results obtained, the study provides an important perspective on the prioritization of the geopolitical risk factor in the evaluation of foreign investment performance.

Geopolitical risk uncertainty and oil future volatility: Evidence from MIDAS models

The fundamental aim of this paper is to test the symmetric and asymmetric effects of geopolitical risk on the five selected prices of energy commodities, consisting of coal, crude oil, gasoline, heating oil, and natural gas, during the period 2 January 2020–29 July 2022 by application of linear and nonlinear ARDL models. Moreover, we also study the impact of anticipated financial volatility on energy commodities. Our results suggest that, over the long term, there is no linear relationship between geopolitical risk, financial volatility, and energy prices. On the other hand, we find statistically significant asymmetrical effects of geopolitical risk and financial volatility on crude oil, gasoline, and heating oil prices in the long and short run. We also identify that coal and natural gas prices do not respond to changes in geopolitical risk during the analysed period.

Geopolitical risk, encompassing wars, terrorism, and tensions between states, exerts a significant impact on global affairs. Previous studies have examined the relationship between geopolitical risk and military spending. However, these studies were limited by certain shortcomings in the measurement tools used to assess geopolitical risk. The introduction of a new geopolitical risk index, leveraging textual analysis technology, offers a way to overcome some of these limitations. Despite this advancement, research exploring the predictive capacity of this geopolitical risk index on military spending behaviour remains scarce. Specifically, no previous studies have investigated the predictive power of both local and global geopolitical risk indices on military spending behaviour. To bridge this gap, this study employs panel VAR analysis for 34 countries worldwide, spanning from 1993 to 2022. The results indicate that the military spending behaviour of countries is significantly influenced by local geopolitical risk rather than global geopolitical risk. Furthermore, the findings also reveal that an increase in geopolitical risk during a given year can predict military spending behaviour in the subsequent 2 years. These findings provide valuable insights for policymakers seeking to understand governments' behaviour regarding military spending.

PurposeOur aim in this study is to investigate the relative importance of the economic policy uncertainty and of the geopolitical risk on U.S. REITs (Real Estate Investment Trusts) returns with a special focus on the different real estate sectors.Design/methodology/approachWe use an augmented Fama-French (1993)’s asset pricing model, including economic policy uncertainty indices (EPU), introduced by Baker et al. (2016), and geopolitical risk indices (GPR) recently developed by Caldara and Iacoviello (2022), to price the potential risk factors for U.S. Nareit indices returns. To obtain robust economic results, we correct for the problems of errors-in-variables in linear asset pricing models; we advocate the use of higher moments estimators as instruments in a generalized method of moments (GMM) framework.FindingsOur results report that economic policy uncertainty (EPU), and geopolitical risk (GPR) are priced for the different Nareit sectors for the last three decades. The GPR index stands as a relevant risk factor. The coefficient estimates are low compared to Fama-French risk factors. They are higher for Shopping Centers, Retail and Region Malls and lower for Health Care and Lodging/Resorts. EPU indices are also priced and less statistically significant. Health Care sector, followed by Shopping Centers and Retail are the most policy-sensitive sectors.Practical implicationsIn their “2023–2024 Top Ten Issues Affecting Real Estate” “political unrest and global economic health” is ranked 1 issue by the Counselors of Real Estate. Our results report that economic policy uncertainty and geopolitical risk are priced for the different Nareit sectors. They suggest implications for investors, insurers, bankers, policymakers and other stakeholders. The geopolitical risk index (GPR) stands as a relevant and significant risk factor for REITs returns.Originality/valueBased on parsimonious robust asset pricing models, the results shed a new light on the relative importance of geopolitical risk and economic policy uncertainty in the real estate sector, with a special focus on the different U.S. REITs sectors. They suggest possible implications for investors, insurers, bankers, policymakers and other stakeholders in a context marked by higher uncertainty shocks and geopolitical risks.

This paper reveals joint stochastic behaviours of the world’s stock markets and geopolitical risk by a copula approach for the 37 world’s stock markets over the period of June 1997 to December 2017. The various bivariate copulas show the different degrees of tail dependences and rank correlations. The differences between overall geopolitical risk index and action‐related geopolitical risk index lie in the higher tail dependence with overall geopolitical risk index, the dominancy of concordant movements of stock market indexes with overall geopolitical risk and that of discordant movements of stock market indexes with action‐related geopolitical risk index. The results illustrate that action‐related geopolitical risk is more often adversely related to the world’s stock market performances with less tail dependence.

Previous studies have found that geopolitical risk (GPR) caused by geopolitical events such as terrorist attacks can affect the movements of asset prices. However, the studies on whether and how these influences can explain and predict the volatility of stock returns in emerging markets are scant and emerging. By using the data from China’s CSI 300 index, we provide some evidence on whether and how the GPR factors can explain and forecast the volatility of stock returns in emerging economies. We employed the GARCH-MIDAS model and the model confidence set (MCS) to investigate the mechanism of GPR’s impact on the China stock market, and we considered the GPR index, geopolitical action index, geopolitical threat index, and different country-specific GPR indices. The empirical results suggest that except for a few emerging economies such as Mexico, Argentina, Russia, India, South Africa, Thailand, Israel, and Ukraine, the global and most of the regional GPR have a significant impact on China’s stock market. This paper provides some evidence for the different effects of GPR from different countries on China’s stock market volatility. As for predictive potential, GPRAct (geopolitical action index) has the best predictive power among all six types of GPR indices. Considering that GPR is usually unanticipated, these findings shed light on the role of the GPR factors in explaining and forecasting the volatility of China’s market returns.

ABSTRACTThis study examined how Bitcoin, energy prices, and geopolitical risk interact by examining the first four moments (mean, variance, skewness, and kurtosis) of their return distributions by using wavelet analysis. The findings reveal that the co‐movement patterns of energy index, geopolitical risk index, and Bitcoin prices are time and frequency sensitive. During the turbulent period of 2020–2024, significant cross effect was observed at medium‐ and long‐term time scales in the relationship between the energy index and the geopolitical risk index. Similarly, in the case of Bitcoin and the geopolitical risk index, significant cross‐effects were detected at medium‐ and short‐term time scales. From 2021 onwards, a strong coherence is observed at high and medium frequencies for all four moment pairs among Bitcoin, energy prices, and geopolitical risk. In terms of the Bitcoin‐energy relationship, significant co‐movement in mean and volatility is noted throughout most of the sample period and across different frequency bands. Moreover, cross‐skewness and cross‐kurtosis connections are more prominent at short‐ and medium‐term horizons, especially during covid pandemic. These insights are valuable for investors and policymakers in risk management.

Objective: The aim of this research is to determine empirically the impact of geopolitical risk originating from countries with high geopolitical risk and domestic ones on the Composite Stock Price Index in Indonesia. In addition, this research aims to determine the role of geopolitical actions in strengthening or weakening the relationship between geopolitical risk and the Composite Stock Price Index in Indonesia. Design/Methods/Approach: This research uses geopolitical risk index (GPRH) data from countries with the highest geopolitical risk index in the last 3 years and domestic ones consisting of Ukraine, Russia, America, China and Indonesia. Meanwhile, geopolitical action risk (GPRA) is a risk index measured in aggregate from January 2004-October 2023, so the number of observations in this study reached 238. Findings: The findings in the research show that Ukraine and America have a negative and significant influence, while China and Russia have a positive and significant impact on the composite stock price index in Indonesia. Apart from that, this research also found that the influence of geopolitical risk on the composite stock price index in Indonesia is greater when geopolitical actions such as escalation of war and acts of terror occur. Originality/Value: This research complements several previous studies regarding the impact of geopolitical risk on the Indonesian composite stock price index. Several previous studies have not examined the impact of each country's geopolitical risk on the composite stock price index and how it is moderated by geopolitical action. Practical/Policy implication: The findings in this research prove that countries that have high geopolitical risk have a significant influence on the Composite Stock Price Index in Indonesia. So that investors can use this research as a consideration when investing in the capital market by considering geopolitical risks originating from abroad and domestically.

Geopolitical risks (GPR) can affect the prices of natural resources, which are crucial for survival and sustainable economies. Based on the TVP-VAR-BK models, this paper examines the asymmetric risk contagion between geopolitical risk, bulk energy, and chemical commodity from a time-frequency perspective. The results show that the risk contagion of geopolitical risks, bulk energy and chemical commodity markets has time-varying asymmetry and periodicity, and is susceptible to extreme events. Furthermore, the main driving factor is high-frequency spillover, which has “short-term fragility”, that is, the risk spillover in the short term is more significant than in the medium and long term, and network spillover is mainly caused by negative risk changes. In addition, the bulk energy market is the main risk transmitter, while the chemical commodity market is the main risk receiver. The risk contagion of crude oil on bitumen markets is the most significant. Finally, as a downstream market of the crude oil industry, the chemical commodity market not only directly accepts risk contagion from the crude oil market, but also transmits risks along the “bulk energy - geopolitical risk - chemical commodity” path. This evidence has important implications for governments and regulators in taking steps to prevent extreme spillover effects and a series of chain reactions from geopolitical risks.

This study investigates the co-movements between prominent financial assets-crude oil, natural gas, gold, and Bitcoin-and uncertainty indices, including the Infectious Disease Equity Market Volatility Tracker (IDEMV) and the Geopolitical Risk Index (GPR), from January 2017 to January 2023. By employing advanced wavelet techniques-Wavelet Power Spectrum (WPS), Bi-Wavelet Coherence (WCA), Multiple Wavelet Coherence (MWC), and Partial Wavelet Coherence (PWC)-we analyze their time- and frequency-dependent responses to market shocks. The results reveal that Bitcoin and WTI exhibit time-varying sensitivity to IDEMV, particularly at short- and medium-term frequencies, highlighting their vulnerability to health-related crises like COVID-19. In contrast, gold and natural gas respond more strongly to GPR, with gold demonstrating a long-term leading role during geopolitical uncertainties, while Bitcoin and WTI lead in health-related shocks. The Russia-Ukraine conflict further amplified GPR's impact on Bitcoin and increased natural gas's vulnerability to geopolitical disruptions. These findings underscore the need for tailored strategies to address health and geopolitical risks. Policymakers should enhance crisis-response frameworks for Bitcoin and crude oil, while investors can reduce uncertainty by diversifying portfolios with resilient assets like gold and natural gas.

In the present study, it was explored how the volatility of the carbon neutrality concept index (CNCI) was affected by China economic policy uncertainty (CEPU) index, climate policy uncertainty (CPU) index, and geopolitical risk (GPR) index. According to the research of Amendola et al. the GARCH-MIDAS model was improved by introducing the realized kernel volatility of China stock market into the short-term volatility component. On this basis, the GARCH-RKV-MIDAS model was constructed. Meanwhile, both GARCH-MIDAS and GARCH-RKV-MIDAS models were applied to identify the influencing factors for CNCI volatility during the period between January 2018 and June 2022, with CNCI predicted. According to the research results, both the CPU index and the GPR index exert a significant effect on the long-term volatility of CNCI, despite no significant difference made by the CEPU index to the long-term volatility of CNCI. As for the prediction of CNCI volatility, the GARCH-RKV-MIDAS model clearly outperforms the GARCH-MIDAS model. Moreover, the CPU index outperforms the GPR index and the CEPU index in predicting the volatility of the CNCI.

How do political tensions and geopolitical risks impact oil prices?

This paper explores the correlation between the Financial Development Index (FDI) and the Geopolitical Risk Index (GPR) in relation to Sustainable Development Goals (SDGs) within the E3 countries: Germany, France, and the United Kingdom. With limited research available on the interaction between these indices and the SDGs, this study aims to bridge that gap by focusing on SDG 13 (Climate Action) and SDG 7 (Affordable and Clean Energy). Using data spanning from 2000 to 2021, the analysis employs ARDL and Dynamic Conditional Correlation (DCC) models to assess the impact of geopolitical risks and financial development on these sustainability targets. Findings reveal that in Germany, there are significant long-term relationships between FDI and both SDG 13 and SDG 7, with geopolitical risks negatively impacting both goals. Economic growth was observed to have a stronger influence on SDG 13. In France, FDI positively affected SDG 13 but had no statistically significant impact on SDG 7. Geopolitical risks had adverse effects on both goals, while economic growth?s impact on SDG 7 was found to be insignificant. In the UK, no significant long-term relationships were identified; however, short-term analysis highlighted notable effects of FDI and geopolitical risks on SDG 7. The DCC analysis revealed that the relationship between SDG 13 and SDG 7 was relatively strong around 2000 but weakened over time.