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Abstract We examine the roles of Gold and Bitcoin as a hedge, a safe haven, and a diversifier against the coronavirus disease 2019 (COVID-19) pandemic and the Ukraine War. Using a rolling window estimation of the dynamic conditional correlation (DCC)-based regression, we present a novel approach to examine the time-varying safe haven, hedge, and diversifier properties of Gold and Bitcoin for equities portfolios. This article uses daily returns of Gold, Bitcoin, S&P500, CAC 40, and NSE 50 from January 3, 2018, to October 15, 2022. Our results show that Gold is a better safe haven than the two, while Bitcoin exhibits weak properties as safe haven. Bitcoin can, however, be used as a diversifier and hedge. This study offers policy suggestions to investors to diversify their holdings during uncertain times. Introduction Financial markets and the diversity of financial products have risen in both volume and value, creating financial risk and establishing the demand for a safe haven for investors. The global financial markets have faced several blows in recent years. From the Global Financial Crisis (GFC) to the outbreak of the pandemic and uncertainty regarding economic policy measures of governments and central banks, the financial markets including equity markets around the world were faced with severe meltdowns. This similar behavior was observed in other markets including equity and commodity markets, resulting in overall uncertainty. In this scenario, the investors normally flock toward the safe-haven assets to protect their investment. In normal situations, investors seek to diversify or hedge their assets to protect their portfolios. However, the financial markets are negatively impacted when there are global uncertainties. Diversification and hedging methods fail to safeguard investors’ portfolios during instability because almost all sectors and assets are negatively affected (Hasan et al., 2021). As a result, investors typically look for safe-haven investments to safeguard their portfolios under extreme conditions (Ceylan, 2022). Baur and Lucey (2010) provide the following definitions of hedge, diversifier, and safe haven: Hedge: An asset that, on average, has no correlation or a negative correlation with another asset or portfolio. On average, a strict hedge has a (strictly) negative correlation with another asset or portfolio.Diversifier: An asset that, on average, has a positive correlation (but not perfect correlation) with another asset or portfolio. Safe haven: This is the asset that in times of market stress or volatility becomes uncorrelated or negatively associated with other assets or a portfolio. As was previously indicated, the significant market turbulence caused by a sharp decline in consumer spending, coupled with insufficient hedging opportunities, was a common feature of all markets during these times (Yousaf et al., 2022). Nakamoto (2008) suggested a remedy by introducing Bitcoin, a “digital currency,” as an alternative to traditional fiduciary currencies (Paule-Vianez et al., 2020). Bitcoin often described as “Digital Gold” has shown greater resilience during periods of crises and has highlighted the potential safe haven and hedging property against uncertainties (Mokni, 2021). According to Dyhrberg (2016), the GFC has eased the emergence of Bitcoin thereby strengthening its popularity. Bouri et al. (2017) in their study indicate that Bitcoin has been viewed as a shelter from global uncertainties caused by conventional banking and economic systems. Recent research has found that Bitcoin is a weak safe haven, particularly in periods of market uncertainty like the coronavirus disease 2019 (COVID-19) crisis (Conlon & McGee, 2020; Nagy & Benedek, 2021; Shahzad et al., 2019; Syuhada et al., 2022). In contrast to these findings, a study by Yan et al. (2022) indicates that it can function as a strong safe haven in favorable economic times and with low-risk aversion. Ustaoglu (2022) also supports the strong safe-haven characteristic of Bitcoin against most emerging stock market indices during the COVID-19 period. Umar et al. (2023) assert that Bitcoin and Gold are not reliable safe-havens. Singh et al. (2024) in their study reveal that Bitcoin is an effective hedge for investments in Nifty-50, Sensex, GBP–INR, and JPY–INR, at the same time a good diversifier for Gold. The study suggests that investors can incorporate Bitcoin in their portfolios as a good hedge against market volatility in equities and commodities markets. During the COVID-19 epidemic, Barbu et al. (2022) investigated if Ethereum and Bitcoin could serve as a short-term safe haven or diversifier against stock indices and bonds. The outcomes are consistent with the research conducted by Snene Manzli et al. (2024). Both act as hybrid roles for stock market returns, diversifiers for sustainable stock market indices, and safe havens for bond markets. Notably, Bhuiyan et al. (2023) found that Bitcoin provides relatively better diversification opportunities than Gold during times of crisis. To reduce risks, Bitcoin has demonstrated a strong potential to operate as a buffer against global uncertainty and may be a useful hedging tool in addition to Gold and similar assets (Baur & Lucey, 2010; Bouri et al., 2017; Capie et al., 2005; Dyhrberg, 2015). According to Huang et al. (2021), its independence from monetary policies and minimal association with conventional financial assets allow it to have a safe-haven quality. Bitcoins have a substantial speed advantage over other assets since they are traded at high and constant frequencies with no days when trading is closed (Selmi et al., 2018). Additionally, it has been demonstrated that the average monthly volatility of Bitcoin is higher than that of Gold or a group of international currencies expressed in US dollars; nevertheless, the lowest monthly volatility of Bitcoin is lower than the maximum monthly volatility of Gold and other foreign currencies (Dwyer, 2015). Leverage effects are also evident in Bitcoin returns, which show lower volatilities in high return periods and higher volatilities in low return times (Bouri et al., 2017; Liu et al., 2017). According to recent research, Bitcoins can be used to hedge S&P 500 stocks, which increases the likelihood that institutional and retail investors will build secure portfolios (Okorie, 2020). Bitcoin demonstrates strong hedging capabilities and can complement Gold in minimizing specific market risks (Baur & Lucey, 2010). Its high-frequency and continuous trading further enrich the range of available hedging tools (Dyhrberg, 2016). Moreover, Bitcoin spot and futures markets exhibit similarities to traditional financial markets. In the post-COVID-19 period, Zhang et al. (2021) found that Bitcoin futures outperform Gold futures.Gold, silver, palladium, and platinum were among the most common precious metals utilized as safe-haven investments. Gold is one such asset that is used extensively (Salisu et al., 2021). Their study tested the safe-haven property of Gold against the downside risk of portfolios during the pandemic. Empirical results have also shown that Gold functions as a safe haven for only 15 trading days, meaning that holding Gold for longer than this period would result in losses to investors. This explains why investors buy Gold on days of negative returns and sell it when market prospects turn positive and volatility decreases (Baur & Lucey, 2010). In their study, Kumar et al. (2023) tried to analyse the trends in volume throughout futures contracts and investigate the connection between open interest, volume, and price for bullion and base metal futures in India. Liu et al. (2016) in their study found that there is no negative association between Gold and the US stock market during times of extremely low or high volatility. Because of this, it is not a strong safe haven for the US stock market (Hood & Malik, 2013). Post-COVID-19, studies have provided mixed evidence on the safe-haven properties of Gold (Bouri et al., 2020; Cheema et al., 2022; Ji et al., 2020). According to Kumar and Padakandla (2022), Gold continuously demonstrates safe-haven qualities for all markets, except the NSE, both in the short and long term. During the COVID-19 episode, Gold’s effectiveness as a hedge and safe-haven instrument has been impacted (Akhtaruzzaman et al., 2021). Al-Nassar (2024) conducted a study on the hedge effectiveness of Gold and found that it is a strong hedge in the long run. Bhattacharjee et al. (2023) in their paper examined the symmetrical and asymmetrical linkage between Gold price levels and the Indian stock market returns by employing linear autoregressive distributed lag and nonlinear autoregressive distributed lag models. The results exhibit that the Indian stock market returns and Gold prices are cointegrated. According to the most recent study by Kaczmarek et al. (2022), Gold has no potential as a safe haven, despite some studies on the COVID-19 pandemic showing contradictory results. The co-movements of Bitcoin and the Chinese stock market have also normalized as a result of this epidemic (Belhassine & Karamti, 2021). Widjaja and Havidz (2023) verified that Gold was a safe haven asset during the COVID-19 pandemic, confirming the Gold’s safe-haven characteristic. As previously pointed out, investors value safe-haven investments in times of risk. Investors panic at these times when asset prices fall and move from less liquid (risky) securities to more liquid (safe) ones, such as cash, Gold, and government bonds. An asset must be bought and sold rapidly, at a known price, and for a reasonably modest cost to be considered truly safe (Smales, 2019). Therefore, we need to properly re-examine the safe-haven qualities of Gold and Bitcoin due to the mixed evidences regarding their safe-haven qualities and the impact of COVID-19 and the war in Ukraine on financial markets. This work contributes to and deviates from the body of existing literature in the following ways. We propose a novel approach in this work to evaluate an asset’s time-varying safe haven, hedge, and diversifier characteristics. This research examines the safe haven, hedging, and diversifying qualities of Gold and Bitcoin against the equity indices; S&P 500, CAC 40, and NSE 50. Through the use of rolling window estimation, we extend the methodology of Ratner and Chiu (2013) by estimating the aforementioned properties of the assets. Comparing rolling window estimation to other conventional techniques, the former will provide a more accurate representation of an asset’s time-varying feature. This study explores the conventional asset Gold’s time-varying safe haven, hedging, and diversifying qualities during crises like the COVID-19 pandemic and the conflict in Ukraine. We use Bitcoin, an unconventional safe-haven asset, for comparison. Data and Methodology We use the daily returns of three major equity indices; S&P500, CAC 40, and NSE 50 from January 3, 2018, to October 15, 2022. The equity indices were selected to represent three large and diverse markets namely the United States, France, and India in terms of geography and economic development. We assess safe-haven assets using the daily returns of Gold and Bitcoin over the same time. Equity data was collected from Yahoo Finance, Bitcoin data from coinmarketcap.com, and Gold data from the World Gold Council website. Engle (2002) developed the DCC (Dynamic Conditional Correlation)-GARCH model, which is frequently used to assess contagion amid pandemic uncertainty or crises. Time-varying variations in the conditional correlation of asset pairings can be captured using the DCC-GARCH model. Through employing this model, we can analyse the dynamic behavior of volatility spillovers. Engle’s (2002) DCC-GARCH model contains two phases; 1. Univariate GARCH model estimation2. Estimation of time-varying conditional correlation. For its explanation, mathematical characteristics, and theoretical development, see here [insert the next link in “the word here” https://journals.sagepub.com/doi/10.1177/09711023251322578] Results and Discussion The outcomes of the parameters under the DCC-GARCH model for each of the asset pairs selected for the investigation are shown in Table 1.   First, we look at the dynamical conditional correlation coefficient, ρ.The rho value is negative and insignificant for NSE 50/Gold, NSE 50 /BTC, S&P500/Gold, and S&P500/BTC indicating a negative and insignificant correlation between these asset pairs, showing Gold and Bitcoin as potential hedges and safe havens. The fact that ρ is negative and significant for CAC 40/Gold suggests that Gold can be a safe haven against CAC 40 swings. The asset pair CAC/BTC, on the other hand, has possible diversifier behavior with ρ being positive but statistically insignificant. Next, we examine the behavior of the DCC-GARCH parameters; α and β. We find that αDCC is statistically insignificant for all the asset pairs, while βDCC is statistically significant for all asset pairs. βDCC quantifies the persistence feature of the correlation and the extent of the impact of volatility spillover in a particular market’s volatility dynamics. A higher βDCC value implies that a major part of the volatility dynamics can be explained by the respective market’s own past volatility. For instance, the NSE 50/Gold’s βDCC value of 0.971 shows that there is a high degree of volatility spillover between these two assets, with about 97% of market volatility being explained by the assets’ own historical values and the remainder coming from spillover. Thus, we see that the volatility spillover is highly persistent (~0.8) for all the asset pairs except NSE 50/BTC. The results above show that the nature of the dynamic correlation between the stock markets, Bitcoin and Gold is largely negative, pointing toward the possibility of Gold and Bitcoin being hedge/safe haven. However, a detailed analysis is needed to confirm the same by employing rolling window analysis, and we present the results in the forthcoming section. We present the rolling window results for S&P500 first. We present the regression results for Gold in Figure 1 and Bitcoin in Figure 2   Figure 1. Rolling Window Regression Results for S&P500 and Gold.Note: Areas shaded under factor 1 represent significant regression coefficients. In Figure 1, we examine the behavior of β0 (intercept term), β1, β2, and β3 (partial correlation coefficients). The intercept term β0 will give an idea about whether the asset is behaving as a diversifier or hedge. Here, the intercept term shows significance most of the time. However, during 2018, the intercept was negative and significant, showing that it could serve as a hedge during geopolitical tensions and volatilities in the global stock market. However, during the early stages of COVID-19, we show that the intercept is negative and showing statistical significance, suggesting that Gold could serve as a hedge during the initial shocks of the pandemic. These findings are contrary to the results in the study by Tarchella et al. (2024) where they found hold as a good diversifier. Later, we find the intercept to be positive and significant, indicating that Gold could act as a potential diversifier. But during the Russia-Ukraine War, Gold exhibited hedge ability again. Looking into the behavior of β1, which is the partial correlation coefficient for the tenth percentile of return distribution shows negative and insignificant during 2018. Later, it was again negative and significant during the initial phases of COVID-19, and then negative in the aftermath, indicating that Gold could act as a weak safe haven during the COVID-19 pandemic. Gold could serve as a strong safe haven for the SP500 against volatility in the markets brought on by the war in Ukraine, as we see the coefficient to be negative and large during this time. From β2 and β3, the partial correlation coefficients of the fifth and first percentile, respectively, show that Gold possesses weak safe haven properties during COVID-19 and strong safe haven behavior during the Ukraine crisis. Next, we examine the characteristics of Bitcoin as a hedge/diversifier/safe haven against the S&P500 returns. We present the results in Figure 2.   Figure 2. Rolling Window Regression Results for S&P500 and Bitcoin.Note: Areas shaded under factor 1 represent significant regression coefficients. Like in the previous case, we begin by analysing the behavior of the intercept coefficient, which is β0. As mentioned earlier the intercept term will give a clear picture of the asset’s hedging and diversifier property. In the period 2018–2019, the intercept term is positive but insignificant. This could be due to the large volatility in Bitcoin price movements during the period. It continues to be minimal (but positive) and insignificant during 2019–2020, indicating toward weak diversification possibility. Post-COVID-19 period, the coefficient shows the significance and positive value, displaying the diversification potential. We see that the coefficient remains positive throughout the analysis, confirming Bitcoin’s potential as a diversifier. Looking into the behavior of β1 (the partial correlation coefficient at tenth percentile), it is positive but insignificant during 2018. The coefficient is having negative sign and showing statistical significance in 2019, suggesting that Bitcoin could be a good safe haven in that year. This year was characterized by a long list of corporate scandals, uncertainties around Brexit, and tensions in global trade. We can observe that throughout the COVID-19 period, the coefficient is showing negative sign and negligible during the March 2020 market meltdown, suggesting inadequate safe-haven qualities. However, Bitcoin will regain its safe-haven property in the coming periods, as the coefficient is negative and significant in the coming months. The coefficient is negative and shows statistical significance during the Ukrainian crisis, suggesting strong safe-haven property. Only during the Ukrainian crisis could Bitcoin serve as a safe haven, according to the behavior of β2, which displays the partial correlation coefficient at the fifth percentile. Bitcoin was a weak safe haven during COVID-19 and the Ukrainian crisis, according to β3, the partial correlation coefficient for the first percentile (coefficient negative and insignificant). According to the overall findings, Gold is a stronger safe haven against the S&P 500’s swings. This result is consistent with the previous studies of Triki and Maatoug (2021), Shakil et al. (2018), Będowska-Sójka and Kliber (2021), Drake (2022), and Ghazali et al. (2020), etc. The same analysis was conducted for the CAC 40 and the NSE 50; the full analysis can be found here [insert the next link in “the word here” https://journals.sagepub.com/doi/10.1177/09711023251322578]. However, it is important to highlight the respective results: In general, we may say that Gold has weak safe-haven properties considering CAC40. We can conclude that Bitcoin’s safe-haven qualities for CAC40 are weak. We can say that Gold showed weak safe-haven characteristics during the Ukraine crisis and good safe-haven characteristics for the NSE50 during COVID-19. We may say that Bitcoin exhibits weak safe haven, but strong hedging abilities to NSE50. Concluding Remarks In this study, we suggested a new method to evaluate an asset’s time-varying hedge, diversifier, and safe-haven characteristics. We propose a rolling window estimation of the DCC-based regression of Ratner and Chiu (2013). Based on this, we estimate the conventional asset’s time-varying safe haven, hedging, and diversifying properties during crises like the COVID-19 pandemic and the conflict in Ukraine. For comparison purposes, we include Bitcoin, a nonconventional safe-haven asset. We evaluate Gold and Bitcoin’s safe haven, hedging, and diversifier properties to the S&P 500, CAC 40, and NSE 50 variations. We use a rolling window of length 60 to estimate the regression. From the results, we find that Gold can be considered as a better safe haven against the fluctuations of the S&P 500. In the case of CAC 40, Gold and Bitcoin have weak safe-haven properties. While Bitcoin demonstrated strong safe-haven characteristics during the Ukraine crisis, Gold exhibited strong safe-haven characteristics during COVID-19 for the NSE 50. Overall, the findings indicate that Gold is the better safe haven. This outcome is consistent with earlier research (Będowska-Sójka & Kliber, 2021; Drake, 2022; Ghazali et al., 2020; Shakil et al., 2018; Triki & Maatoug, 2021). When it comes to Bitcoin, its safe-haven feature is weak. Bitcoin, however, works well as a diversifier and hedge. Therefore, from a policy perspective, investing in safe-haven instruments is crucial to lower the risks associated with asset ownership. Policymakers aiming to enhance the stability of financial portfolios might encourage institutional investors and other market players to incorporate Gold into their asset allocations. Gold’s strong safe-haven qualities, proven across various market conditions, make it a reliable choice. Gold’s performance during crises like COVID-19 highlights its potential to mitigate systemic risks effectively. Further, Bitcoin could also play a complementary role as a hedge and diversifier, especially during periods of significant volatility such as the Ukraine crisis. While Bitcoin’s safe-haven characteristics are relatively weaker, its inclusion in a diversified portfolio offers notable value and hence it should not be overlooked. Further, policymakers may consider how crucial it is to monitor dynamic correlations and periodically rebalance portfolios to account for shifts in the safe haven and hedging characteristics of certain assets. Such measures could help reduce the risks of over-reliance on a single asset type and create more resilient portfolios that can better withstand global economic shocks. For future research, studies can be conducted on the estimation of the rolling window with different widths. This is important to understand how the safe-haven property changes across different holding periods. Further, more equity markets would be included to account for the differences in market capitalization and index constituents. This study can be extended by testing these properties for multi-asset portfolios as well. We intend to take up this study in these directions in the future. Data Availability StatementNot applicable.Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.FundingThe authors received no financial support for the research, authorship, and/or publication of this article.ReferencesAkhtaruzzaman M., Boubaker S., Lucey B. M., & Sensoy A. (2021). Is gold a hedge or a safe-haven asset in the COVID-19 crisis? Economic Modelling, 102, 105588. Crossref. Web of Science.Al-Nassar N. S. (2024). Can gold hedge against inflation in the UAE? A nonlinear ARDL analysis in the presence of structural breaks. PSU Research Review, 8(1), 151–166. Crossref.Barbu T. C., Boitan I. A., & Cepoi C. O. (2022). Are cryptocurrencies safe havens during the COVID-19 pandemic? A threshold regression perspective with pandemic-related benchmarks. Economics and Business Review, 8(2), 29–49. 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Introduction Geopolitical tensions are making global trade increasingly difficult. In order to reduce the associated risk of default, companies are shifting their trade relations to trading partners that are politically similar to them. In the course of the beginnings of geo-economic fragmentation, politically and economically like-minded countries are also gaining in importance for German and European decision-makers. Liaison countries1 in particular can form a counterforce to the trend towards polarization in foreign trade - especially between the USA and China: they are characterized by a pronounced economic and trade policy openness that overrides differences between geopolitical or ideological camps. Consequently, the question arises: How can relevant connecting countries for Germany and Europe be identified? What opportunities and risks do closer trade relations with these countries offer in order to strengthen foreign trade resilience in geopolitically uncertain times?  With a high degree of openness - defined as the sum of imports and exports in relation to gross domestic product - of over 80 percent2 , the German economy is strongly integrated into global trade. Accordingly, the disruptive effect of geo-economic fragmentation on the German economy would be above average. The defensive strategy to strengthen Germany's economic security by pushing for trade policy independence would only reinforce geo-economic fragmentation. Against the backdrop of comparatively high economic vulnerability, it is necessary to focus on those potential partner countries with which German and European foreign trade could be developed and expanded even under the condition of increasing fragmentation.  Geoeconomic Fragmentation  The term "geo-economic fragmentation" is used to describe the politically motivated reorganization of global goods and financial flows, in which strategic, economic and political interests primarily determine the choice of countries of origin and destination for trade flows.3 In the scenario of geo-economic fragmentation, the result would be the formation of a bloc within the global community of states, which would fundamentally change the regulatory structure of global economic networking. In this case, trade and investment would probably concentrate from a previously diverse range of economic partner countries - prior to the formation of the bloc - on those countries that now - since the formation of the bloc - belong to the same bloc.  The likelihood of this scenario occurring and leading to an increased fragmentation of the global economic order has increased again in the recent past. For example, Donald Trump's second term as US president is causing increasing geopolitical uncertainty worldwide.  Statements on the concrete form of a possible demarcation of potential blocs are subject to a great deal of uncertainty. However, the division of a large part of the global economy into a "US bloc" and a "China bloc" is a conceivable scenario for which German politics and business should prepare.  Data already shows that, at a global level, foreign trade openness has decreased in the recent past. Data from the World Trade Organization (WTO) illustrates the increasing hurdles in global trade in goods. While 3.1% of global imports were still affected by tariff or non-tariff barriers to trade in 2016 - including under WTO rules - this figure rose to 11.8% in 2024 over the following years.4 This development goes hand in hand with a noticeable loss of importance and enforcement of the WTO since the 2010s, which previously played a central role as the guardian of the rules-based global economic order.  Studies by the International Monetary Fund (IMF) have already found indications of an incipient geo-economic fragmentation along potential bloc borders. It shows that trade in goods and foreign direct investment between countries that would belong to the opposing camp in the event of a bloc formation declined on average in 2022 and 2023 - in contrast to foreign trade between countries that are geopolitically close.5  In this initial phase of geo-economic fragmentation, liaison countries are beginning to establish themselves as a counterforce, holding the fragmenting global community of states together with new trade and investment routes.  Identification of liaison countries Specifically, liaison countries have the following characteristics: a pronounced openness to foreign trade in the form of a high foreign trade quota and low tariff and non-tariff trade barriers, as well as pronounced economic relations with partner countries from different geopolitical camps. The geopolitical orientation of countries can be examined using data on voting behavior within the United Nations.6 This involves analyzing whether a country can be assigned to the US or Chinese camp - or whether there is no pronounced proximity and therefore political neutrality or "non-alignment" in the sense of ideological independence. The data-based identification of connecting countries is relatively new. Empirical analyses are also limited to connecting countries in the context of US-Chinese foreign trade - specifically US imports from China. In this case, the characteristics of a connecting country can be broken down into (1) "non-alignment" - i.e. a geopolitical distance to both a Western and an Eastern bloc - as well as (2) an increase in imports and foreign investment from China and (3) a simultaneous increase in exports to the United States. In a narrower sense, this is an evasive reaction to trade restrictions, i.e. circumventing trade. If the foreign trade indicators - specifically the trade and investment data relating to the US and China - of "non-aligned" countries for the period from 2017 to 2020 show corresponding characteristic-related changes compared to previous years, these can be identified as countries connecting the US and China.  The analysis of trade data shows that the value of direct exports from China to the USA fell during Donald Trump's first term in office. At the same time, both Chinese exports to some of the "non-aligned" countries and exports from these countries to the USA have increased significantly. These countries have presumably stepped in as a link on the export route from China to the US after the previously direct trade flow was interrupted by trade barriers and had to find a new route. Companies producing in China are therefore likely to have sought new, indirect ways to maintain access to the US sales market.  A certain statistical inaccuracy in the foreign trade data makes it difficult to draw a definitive conclusion in this context. It should be noted: No single commodity can be tracked across national borders in trade data collection. Whether the additional goods imported from China actually found their way to the United States can only be assumed approximately. However, if the trade flows are aggregated, a clearer picture emerges and the circumvention trade via selected connecting countries - including Vietnam and Mexico - becomes visible.  Data on foreign direct investment rounds off the analysis.7 "Non-aligned" countries in which an increase in Chinese investment can be seen between 2016 and 2020 in addition to trade flows can be identified as connecting countries. Here, too, available data suggests that the companies concerned either exported their goods to the United States via a stopover or even outsourced parts of their production destined for the US market to connecting countries. Five connecting countries between the US and China Based on the 2017-2020 study period, various connecting countries can be empirically identified that were used to indirectly maintain access to the US market. In terms of foreign trade volume, the economically most important connecting countries include Mexico, Vietnam, Poland, Morocco and Indonesia.8 All five countries are characterized by the fact that both their exports of goods to the US and their imports of goods from China increased significantly between 2017 and 2020. In addition, greenfield investments (foreign direct investment to set up a new production facility) have risen significantly compared to the period before 2017.  However, the five countries show different priorities in their development, which differentiate them in their role as connecting countries between the USA and China. In Vietnam, exports to the USA in particular have risen sharply. China has been the most important procurement market for Vietnamese companies for years. Poland, Mexico and Indonesia are characterized as connecting countries primarily by the significant increase in imports from China. Morocco, in turn, was able to attract more Chinese foreign investment in particular. Greenfield investments have almost tripled here since 2017. However, Poland - a rather surprising candidate for the role of liaison country, as it is intuitively assigned to the US-oriented bloc - is positioned fairly centrally between the US and China according to the analysis of voting behavior within the United Nations9. In addition, Poland qualifies primarily due to the sharp rise in greenfield investments from China, primarily in the expansion of domestic battery production.10  It cannot be concluded from the previous studies on the USA and China whether German companies are also circumventing trade barriers from the USA via the countries identified. As the trade policy conflicts between the US and China differ significantly from those between the EU and China, there has been a lack of comparable empirical data to analyze connecting countries in the EU context. Opportunities and challenges As the German economy is strongly oriented towards foreign trade and is closely networked with both the USA and China, German companies play a particularly exposed role in the area of tension between the USA and China. Increased economic exchange with potential connecting countries would offer German companies an opportunity to mitigate the expected shock of a geopolitical bloc. They could at least maintain international trade to a certain extent and thus secure some of the endangered sales and procurement markets. On the other hand, there are also costs associated with expanding foreign trade relations with potential connecting countries. The greater complexity also increases the risk in the value chains. Companies that position themselves wisely within this trade-off buy themselves valuable time in the event of a shock to reorganize themselves against the backdrop of changed foreign trade conditions.  From the perspective of foreign trade policy, it is also possible to examine the extent to which stronger foreign trade cooperation with (potential) connecting countries could have advantages. The trade-off between resilience and complexity must then be assessed at a macroeconomic level, beyond individual company interests. In order to make it easier for companies to connect to potential connecting countries and to create appropriate framework conditions, German and European policy can build on existing comprehensive strategies at national and European level. Both the China Strategy11 and the National Security Strategy12 focus foreign policy on connecting countries as part of a stronger economic and political risk diversification. There is also a similar framework at European level with the EU's Strategic Compass13 . Following on from this, the German government could create targeted incentives to open up new markets in liaison countries, which would diversify critical supply chains and reduce one-sided dependencies.  At the same time, connecting countries pose a challenge. These can be used to circumvent foreign trade measures such as sanctions if flows of goods can find alternative routes via connecting countries more easily than before.  In order to realize opportunities and overcome challenges, close cooperation between science, politics and companies is required. This first requires the identification of a selection of potential connecting countries through scientifically sound analysis. This creates the basis for the subsequent steps in which European and German policymakers work closely with companies to create attractive framework conditions for trade with potential connecting countries - for example through bilateral trade agreements.  Attractive foreign trade framework conditions can create the necessary incentive to actually expand trade relations with potential connecting countries. Companies need to weigh up individual cases and make forward-looking decisions: To what extent is there a risk of a loss of production triggered by geopolitical conflicts? And how much would the complexity of the value chain increase if more potential connecting countries were included? Ultimately, the actual choice of preferred sales and procurement markets lies with the individual companies. LicenseThis work is licensed under CC BY 4.0 References1. Verbindungsländer werden im Sinne von Connectors verstanden, vgl. 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On 3 January 2026, the US carried out a surprise military operation in Venezuela, capturing President Nicolás Maduro and his wife, Cilia Flores. The US has made little effort to cloak its operation in either solidarist language, such as appeals to democracy promotion, human rights, or liberal peacebuilding – or in pluralist rhetoric emphasizing the preservation of international order. Instead, Washington has presented the action in largely instrumental and strategic terms, signalling a willingness to sidestep both dominant justificatory traditions within international society. While Maduro and Flores are charged with narco-terrorism conspiracy and cocaine importation conspiracy, international debates focus on the future of Venezuela’s oil (Poque González 2026). On 7 January administration officials said the US plans to effectively assume control over the sale of Venezuela’s oil “indefinitely” (Sherman 2026) and President Donald Trump confirmed that he expected the US to run Venezuela, insisting that the country’s interim government was “giving us everything that we feel is necessary” (Sanger et al. 2026). Attention is fixed not only on Washington’s plans for Venezuela’s oil sector and control over its export revenues, but also on the replies from Moscow and Beijing, Maduro’s chief foreign backers and heavyweight players in energy politics. Consequently, this article asks two questions. First, to what extent does American control of Venezuelan oil threaten China’s and Russia’s energy interests? Second, what does the resulting US–China–Russia triangle imply for how energy security itself is being redefined? A constructivist perspective, recognizes that oil is an idea—valuable not only because it burns but because control over it symbolizes power and authority (Kuteleva 2021). Thus, when the US claims the right to supervise Venezuelan oil revenues, it is not only increasing leverage over barrels, but asserting the authority to define legitimate energy exchange itself. In this context, while the material threat is limited for China and already largely sunk for Russia, the symbolic, institutional and political threat is profound. A straightforward constructivist interpretation of the US–China–Russia triangle centres on status. China had cultivated Venezuela as an “all-weather strategic partnership” (Ministry of Foreign Affairs of PRC 2025b) and major debtor, only to watch Maduro captured days after senior Chinese officials visited Caracas (Ministry of Foreign Affairs of PRC 2025a). In constructivist terms, this is an obvious status injury: China appeared present but powerless. China’s energy diplomacy had functioned as proof of its global influence, and the nullification of China’s energy ties with Venezuela by US force undermines China’s narrative as a protective patron for the Global South. Beijing accused Washington of “hegemonic thinking” (Liu and Chen 2026), “bullying” (Global Times 2026a), and violating Venezuelan sovereignty and “the rights of the Venezuelan people” (Global Times 2026b). This strong pluralist language is not incidental—it is a bid to reclaim moral authority and redefine the event as norm-breaking rather than capability-revealing. Similarly, Russia’s involvement in Venezuela was never purely economic. Moscow saw the alliance with Venezuela as a way to advance its anti-American agenda and to signal that it could cultivate allies in Washington’s traditional backyard (Boersner Herrera and Haluani 2023; Gratius 2022; Herbst and Marczak 2019). It used Venezuela as leverage against the US, subsidised the regime during periods of domestic recession, and framed support as proof of great-power reliability. As senior Russian executives put it, “economic considerations took a back seat to political goals of taking swipes at the US” (Seddon and Stognei 2026). US control of Venezuelan oil thus removes a symbolic platform on which Russia enacted its identity as an energy superpower and geopolitical spoiler. While Russia continues loud sovereignty talk, its demonstrated incapacity to protect partners pushes it toward opportunistic bargaining (“concert” deals, see Lemke 2023) rather than overt defense of UN-pluralist restraint. As such, Dmitry Medvedev (2026) bluntly claimed that the US special military operation in Venezuela all but justifies Russia’s own actions in Ukraine. Venezuela is not a core supplier for China in volumetric terms. In 2025, Venezuelan exports to China averaged roughly 395,000 barrels per day—about 4% of China’s seaborne crude imports, according to Kpler data cited by the FT (Leahy and Moore 2026). China has diversified routes, strategic reserves covering at least 96 days of imports, and strong purchasing power in global markets (Downs 2025). Hence, from a narrow supply perspective, the loss of Venezuelan oil is manageable. That said, around one-fifth of China’s crude imports come from suppliers under US or western sanctions, primarily Iran, Venezuela and Russia, much of it disguised via transshipment near Malaysia (Downs 2025). Independent “teapot” refiners (Downs 2017)—who account for about a quarter of China’s refining capacity—are structurally dependent on this discounted, politically risky oil. Consequently, Trump’s seizure of Maduro alarmed China not mainly because of Venezuela itself, but because it demonstrated Washington’s capacity to escalate from sanctions to physical control of an energy sector, and thus potentially to Iran. Here, constructivism reveals the problem: “sanctioned oil” is not simply cheaper crude; it is a political category—oil marked as illegitimate by a dominant legal-financial order. The US move signals that this stigma can be converted into coercive authority, turning commercial vulnerability into geopolitical dependence. This reclassification transforms Chinese domestic actors into security subjects. “Teapot” refiners are no longer just businesses; they become strategic vulnerabilities whose survival depends on US tolerance. Analysis warn that a cutoff of Iranian oil could force many to shut down entirely (Leahy and Moore 2026). In this context, US control of Venezuelan oil reshapes Chinese energy security discourse from one of diversification and market access to one of hierarchy and exposure to political permission. Russia’s oil interests in Venezuela were largely written down years earlier. In 2020, Rosneft had sold most formal assets after pouring around $800m into loans and projects that produced little return (The Economist 2020). Much of the remaining exposure consisted of debts and shadow ownership arrangements. More important is the damage to Russia’s sanctions-evasion architecture. Russia had become the leading marketer of Venezuelan oil by trading crude as debt repayment and using banks partly owned by sanctioned Russian institutions, creating what the 2019 Atlantic Council report described as “a counter financial system to the one dominated by the West” (Herbst and Marczak 2019). The recent reporting on the US tracking a tanker linked to Venezuela, Russia and Iran illustrates how this counter-order is being contested operationally (Sheppard et al. 2026). The vessel sailed under false flags, was sanctioned for carrying Iranian oil, later re-registered under Russian jurisdiction, and became vulnerable to boarding under the UN Convention on the Law of the Sea because it was “without nationality.” Such episodes show that energy security is increasingly constituted by maritime law, insurance rules, and surveillance practices. US control over Venezuelan oil expands this regime of enforcement, making Russia’s informal trading networks less viable. A constructivist approach suggests that American control of Venezuelan oil is best understood not as a supply shock, but as an act of social stratification in the international system. Energy markets have always been hierarchical, but the hierarchy was largely implicit: reserve currencies, shipping insurance, futures exchanges, and contract law already privileged Western institutions. What is new is the explicit performance of hierarchy—the public demonstration that a great power can redefine ownership, legality, and access through coercion and administrative authority. This produces a stratified energy order: First, rule-makers – states whose legal systems, sanctions regimes, and corporate actors define what counts as legitimate oil (primarily the US and its allies). Second, rule-takers – states whose energy security depends on access to these institutions (most importers). And third, rule-evaders – states forced into informal networks (Russia, Iran, Venezuela) whose energy becomes socially “tainted.” China occupies an unstable middle category: economically powerful but institutionally dependent. 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