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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. 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한국어로 읽기 Leer en español In Deutsch lesen Gap اقرأ بالعربية Lire en français Читать на русском Last week, the Trump administration signed a deal with Ukraine that gives it privileged access to Ukraine’s natural resources. Some news outlets described the deal as Ukrainian President Volodymyr Zelensky “caving” to US President Donald Trump’s demands. But we see the agreement as the result of clever bargaining on the part of Ukraine’s war-time president. So, what does the deal mean for Ukraine? And will this help strengthen America’s mineral supply chains? Ukraine’s natural resource wealth Ukraine is home to 5% of the world’s critical mineral wealth, including 22 of the 34 minerals identified by the European Union as vital for defence, construction and high-tech manufacturing. However, there’s a big difference between resources (what’s in the ground) and reserves (what can be commercially exploited). Ukraine’s proven mineral reserves are limited. Further, Ukraine has an estimated mineral wealth of around US$14.8 trillion (A$23 trillion), but more than half of this is in territories currently occupied by Russia. What does the new deal mean for Ukraine? American support for overseas conflict is usually about securing US economic interests — often in the form of resource exploitation. From the Middle East to Asia, US interventions abroad have enabled access for American firms to other countries’ oil, gas and minerals. But the first iteration of the Ukraine mineral deal, which Zelensky rejected in February, had been an especially brazen resource grab by Trump’s government. It required Ukraine to cede sovereignty over its land and resources to one country (the US), in order to defend itself from attacks by another (Russia). These terms were highly exploitative of a country fighting against a years-long military occupation. In addition, they violated Ukraine’s constitution, which puts the ownership of Ukraine’s natural resources in the hands of the Ukrainian people. Were Zelensky to accept this, he would have faced a tremendous backlash from the public. In comparison, the new deal sounds like a strategic and (potentially) commercial win for Ukraine. First, this agreement is more just, and it’s aligned with Ukraine’s short- and medium-term interests. Zelenksy describes it as an “equal partnership” that will modernise Ukraine. Under the terms, Ukraine will set up a United States–Ukraine Reconstruction Investment Fund for foreign investments into the country’s economy, which will be jointly governed by both countries. Ukraine will contribute 50% of the income from royalties and licenses to develop critical minerals, oil and gas reserves, while the US can make its contributions in-kind, such as through military assistance or technology transfers. Ukraine maintains ownership over its natural resources and state enterprises. And the licensing agreements will not require substantial changes to the country’s laws, or disrupt its future integration with Europe. Importantly, there is no mention of retroactive debts for the US military assistance already received by Ukraine. This would have created a dangerous precedent, allowing other nations to seek to claim similar debts from Ukraine. Finally, the deal also signals the Trump administration’s commitment to “a free, sovereign and prosperous Ukraine” – albeit, still without any security guarantees. Profits may be a long time coming Unsurprisingly, the Trump administration and conservative media in the US are framing the deal as a win. For too long, Trump argues, Ukraine has enjoyed US taxpayer-funded military assistance, and such assistance now has a price tag. The administration has described the deal to Americans as a profit-making endeavour that can recoup monies spent defending Ukrainian interests. But in reality, profits are a long way off. The terms of the agreement clearly state the fund’s investment will be directed at new resource projects. Existing operations and state-owned projects will fall outside the terms of the agreement. Mining projects typically work within long time frames. The move from exploration to production is a slow, high-risk and enormously expensive process. It can often take over a decade. Add to this complexity the fact that some experts are sceptical Ukraine even has enormously valuable reserves. And to bring any promising deposits to market will require major investments. What’s perhaps more important It’s possible, however, that profits are a secondary calculation for the US. Boxing out China is likely to be as – if not more – important. Like other Western nations, the US is desperate to diversify its critical mineral supply chains. China controls not just a large proportion of the world’s known rare earths deposits, it also has a monopoly on the processing of most critical minerals used in green energy and defence technologies. The US fears China will weaponise its market dominance against strategic rivals. This is why Western governments increasingly make mineral supply chain resilience central to their foreign policy and defence strategies. Given Beijing’s closeness to Moscow and their deepening cooperation on natural resources, the US-Ukraine deal may prevent Russia — and, by extension, China — from accessing Ukrainian minerals. The terms of the agreement are explicit: “states and persons who have acted adversely towards Ukraine must not benefit from its reconstruction”. Finally, the performance of “the deal” matters just as much to Trump. Getting Zelensky to sign on the dotted line is progress in itself, plays well to Trump’s base at home, and puts pressure on Russian President Vladimir Putin to come to the table. So, the deal is a win for Zelensky because it gives the US a stake in an independent Ukraine. But even if Ukraine’s critical mineral reserves turn out to be less valuable than expected, it may not matter to Trump.

한국어로 읽기 Leer en español In Deutsch lesen Gap اقرأ بالعربية Lire en français Читать на русском Abstract  This paper looks at the development of Chinese exports to Central Asian countries after Russia’s invasion of Ukraine in February 2022. The analysis, which relies on export data from China to Asian countries at a general product level, shows that China’s exports to Central Asia have significantly increased since the start of the war. In particular, exports to Kazakhstan, Uzbekistan, and Kyrgyzstan have increased significantly. The analysis focuses on exports in Harmonized System (HS) categories 84, 85, 87, and 90. Many of the products sanctioned by the West in trade with Russia belong to these categories, but the categories also include many non-sanctioned products. Although the value of China’s exports to Central Asia is still smaller than direct trade with Russia, China’s exports – especially to Kyrgyzstan – have seen dramatic increases in the HS 84, 85, 87, and 90 categories. Along with the export growth from China to Central Asia, exports in these categories from Central Asia to Russia have also increased significantly.  Keywords: China, Central Asia, Russia, exports 1. Introduction  This policy brief sheds light on the development of Chinese exports to Central Asia after Russia’s invasion of Ukraine in early 2022. The analysis, which focuses on China’s dollar-denominated exports to Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan between 2018 and 2023, is based on the monthly and yearly customs data on goods exports from CEIC, China Customs Administration, Kazakhstan Bureau of National Statistics, and UN Comtrade. The analysis considers exports from Central Asian countries to Russia in some key product categories in the same time frame. Data on Chinese exports to Russia and the rest of the world (excluding Russia and Central Asian countries) help broaden the analysis.  The European Union, the United States, as well as a number of other countries, imposed sanctions on Russia in response to its invasion of Ukraine in February 2022. The sanctions packages targeted trade, investment, and cooperation with Russia, including sanctions on exports and imports of goods and services. While China has yet to impose sanctions on Russia, Chinese companies increasingly face the threat of secondary sanctions.  There is evidence that trade sanctions imposed against Russia have been circumvented by redirecting trade through Russia's neighboring countries (e.g. Chupilkin et al., 2023) and that China exports to Russia dual-use goods exploited by the Russian military (Kluge, 2024). This analysis shows that Chinese exports to Central Asia increased significantly after the Russian invasion of Ukraine in 2022. The soaring trade with Kyrgyzstan, a relatively tiny economy, is particularly notable. Chinese exports to Kazakhstan and Uzbekistan also rose sharply. Exports from Central Asian countries to Russia in selected key export categories increased in 2022, with Kazakhstan’s exports growing significantly, making it the largest exporter to Russia among Central Asian countries.  The paper analyzes the export of China to Central Asia by examining Harmonized System (HS) categories 84 (Machinery), 85 (Electrical equipment), 87 (Vehicles), and 90 (Optical and medical instruments). Categories 88 (Aircraft) and 89 (Ships) were omitted from the analysis since their export volumes were irregular and the data are inconsistent. These categories are important since many of the sanctions goods belong to these broad categories and often involve sophisticated technologies essential to Russian military efforts. Additionally, China is a major technology producing country and Russia’s main supplier of sanctioned technology products (Simola, 2024). Not all products in these categories are subject to sanctions and instead the analysis here only provides a broad view of the development of categories with sanctioned products.  The three-part analysis in this brief begins with a discussion of the development of Chinese exports to Central Asian countries at a general level. We then consider Chinese exports to Central Asia in HS categories 84, 85, 87 and 90, and conclude with an overview of Central Asia country exports to Russia in the same HS categories.  2. Chinese trade relations with Central Asia  From a trade perspective, China dominates trade relations with Central Asian countries. Most Central Asian countries run trade deficits with China. While Central Asian countries are geographically proximate with China (Kazakhstan, Kyrgyzstan, and Tajikistan share borders with China), total exports to these countries have traditionally represented a small slice of China’s total exports. In 2018, for example, Kazakhstan accounted for around 0.5 % of China’s total exports, and the shares of China’s exports to Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan were between 0.01 % and 0.2 %. China’s exports to Russia in 2018 were around 2 % that year. In 2023, however, exports to Kazakhstan had grown to 0.7 % of China’s total exports, and exports to other Central Asian economies were between 0.03 % and 0.6 %. The share of exports to Kyrgyzstan grew from 0.2 % to 0.6 % in terms of China’s total exports. In comparison, Chinese exports to Russia in 2023 represented 3 % of China’s total exports. In terms of annual growth, Kyrgyzstan on-year increase between stands out, with Chinese exports (measured in dollars) growing by 150 % in 2021 and 110 % in 2022.  The countries in the region are not a homogeneous group. Their economies differ in size and trade patterns. Measured by GDP, Kazakhstan was the largest regional economy in 2023, with a GDP of $260 billion. The second largest was Uzbekistan ($90 billion), followed by Turkmenistan ($59 billion), Kyrgyzstan ($14 billion), and Tajikistan ($12 billion) (World Bank, 2024). China’s top export destination in 2023 was Kazakhstan ($25 billion) and Kyrgyzstan ($20 billion). Turkmenistan had the least exports ($1 billion).  In addition to Russia’s war of aggression, new trade routes and warm bilateral relations may have played a role in Chinese exports to Central Asia. New trade routes have opened under the Belt & Road Initiative, and Xi Jinping’s relations with the leaders of Central Asian countries have been generally friendly.  China has been particularly active in Kyrgyzstan, where it has helped to build several transport infrastructure projects to improve transport connections within the country and the region. Especially in mountainous areas, new transport routes and improved logistics connections could have a major impact on trade volumes. Kyrgyzstan also changed presidents in 2021 following snap elections to quell a wave of protest. Kyrgyzstan’s newly elected president, Sadyr Zhaparov, emphasizes China’s importance as Kyrgyzstan’s trading partner and investor, and has called for closer relations with China.  A new trade route from China to Kazakhstan was opened in the summer of 2023 during the China-Central Asia Summit. During Xi Jinping’s visit to Kazakhstan in 2022, the leaders announced to deepen bilateral relations.  Uzbekistan, Turkmenistan, and Tajikistan have established friendly relations with Xi and China. With regard to vehicle exports, it is worth noting that the re-export of cars through the Eurasian Economic Union to Russia previously received tax relief, a policy that ended this year. 3. An overview of  Chinese exports to Central Asia Between 2018 and 2023, China primarily exported textile and wood-related products, as well as machinery, electronics, and vehicles to Central Asia (Figure 1). Compared to China’s overall export structure to the world (Figure 2), the share of textile and wood products in China’s exports to Central Asia is significantly higher. In contrast, approximately 50 % of China’s global exports consist of machinery, electronics, and vehicles, whereas these categories account for about 30–40 % of China’s exports to Central Asia.   In dollar terms, Chinese exports to Central Asia grew by 170 % from 2018 to 2023. This growth parallels China's export growth to Russia, which increased by 130 % over the same period. For comparison, Chinese exports to the rest of the world grew by around 40 % in that period. The largest export growth was seen in Kazakhstan, Kyrgyzstan, and Uzbekistan (Figure 3), with exports to Kyrgyzstan experiencing an explosive increase at the beginning of 2021. While more moderate, export growth to Kazakhstan and Uzbekistan also took off in the first half of 2022. Chinese exports to Kazakhstan, which were valued at $11 billion in 2018, surged to $25 billion in 2023. Chinese exports to Uzbekistan tripled from $4 billion in 2018 to $12 billion in 2023. Chinese exports more than tripled to Kyrgyzstan during the period from $6 billion in 2018 to $20 billion in 2023. Chinese exports to Kyrgyzstan are significant given the country’s modest GDP. Growth in Chinese exports to Russia mirrors the growth in exports to Central Asia (Figure 3). In dollar terms, however, China's exports to Russia are about double to those of China’s total exports to Central Asia.   The largest export categories to Central Asia in China’s 2023 export structure were footwear, textiles, and clothes ($20 billion); machinery and vehicles ($11 billion); electronics ($3 billion); and iron and steel ($2 billion). Exports of iron and steel to Tajikistan, Kyrgyzstan, and Turkmenistan were minimal, but significant for Kazakhstan and Uzbekistan, with growth starting in early 2023.  Chinese exports of footwear, textiles and clothes to Kyrgyzstan (and exports generally) began took off in early of 2021 (Figure 4). Kazakhstan’s export growth in the same category started after Russia’s invasion of Ukraine in 2022. Exports of machinery and vehicles to Kazakhstan, Uzbekistan, and Kyrgyzstan (Figure 4) skyrocketed in 2023. Chinese exports of iron and steel to Kazakhstan and Uzbekistan also soared in 2023 (Figure 5). In the export of electronics, Uzbekistan stands out as exports from China more than doubled in 2023 from 2022 levels (Figure 5). Electronics exports to Kyrgyzstan started increase in early 2021 (Figure 5).     When examining annual changes in these export categories, the dollar-based annual growth of Chinese exports to Kyrgyzstan clearly stands out from other Central Asian countries across all export categories (see Figures 6 and 7). The annual growth to Kyrgyzstan began to increase in early 2021 and remains high throughout 2022. For instance, Chinese exports to Kyrgyzstan in electronics and in footwear, textiles and clothes peaked around 300 % in early 2022. Chinese exports to Turkmenistan and Tajikistan are significantly smaller in dollar terms than for other Central Asian countries, so they do not stand out in earlier figures. However, annual growth patterns show that China’s annual export growth to Turkmenistan and Tajikistan also rose in 2022.     This section examines Chinese exports to Central Asian countries in the HS categories 84 “Machinery,”1 85 “Electrical equipment,”2 87 “Vehicles”,3 and 90 “Optical and medical instruments.”4 HS categories 88 “Aircraft”5 and 89 “Ships”6 were omitted from the analysis since the export volumes were irregular and inconsistent. The data used in the analysis is the sum of HS8-level customs data for the respective category, so values may slightly differ from the actual HS2-level values.  China’s dollar-denominated exports in machinery (HS 84) increased in 2022 and 2023 from the pre-invasions period (Figure 8). Growth in exports is already apparent in 2022 for Kazakhstan, Kyrgyzstan, and Tajikistan, while the rise in Uzbekistan begins in 2023. Exports of machinery to Russia started to increase in 2021, with higher growth in 2022 and 2023 (Figure 9). China’s exports to the rest of the world in the same category rose through 2021, and decreased from 2022 to 2023 (Figure 9).   For electrical equipment (HS 85), China’s exports increased significantly compared to the period before the war, especially to Kyrgyzstan, where exports surged in 2022 and continued to grow in 2023 (Figure 10). China’s exports to Uzbekistan also surged in 2023. Exports to Kazakhstan decreased from 2021 to 2022, but grew in 2023, slightly surpassing the 2021 level. When examining Chinese exports to Russia, dollar-denominated changes follow a similar trend (Figure 11). During the same period, China’s exports to the rest of the world increased from 2021 to 2022 and decreased in 2023, a trend similar to that of machinery (Figure 11).   In the export of vehicles (HS 87), China’s exports to Central Asia followed a similar trend in exports to Kazakhstan, Kyrgyzstan, and Uzbekistan, i.e. initial growth in 2022 and strong growth in 2023 (Figure 12). Chinese exports to Russia also surged in 2023 (Figure 13). In the vehicle category, Chinese exports to the rest of the world grew steadily in 2021, 2022, and 2023 (Figure 13).   For optical and medical instruments (HS 90), China’s exports to Kazakhstan and Kyrgyzstan increased significantly in 2022, and grew further  in 2023, albeit at a more moderate pace (Figure 14). China’s exports to Uzbekistan increased post-invasion in 2022 and 2023, although export levels were similar to 2019 and 2020. Exports to Turkmenistan grew by 260 % in 2022 from the previous year, although this is less noticeable in the figures due to the smaller dollar value amounts related to other Central Asian countries. China’s exports of optical and medical instruments to Russia grew steadily, with a sharper increase beginning in 2022 (Figure 15). However, China’s exports to the rest of the world in this category decreased from 2021 to 2022 (Figure 15).   In summary, China’s dollar-denominated exports to Central Asia increased significantly over the past couple of years, particularly those to Kazakhstan, Kyrgyzstan, and Uzbekistan. Reflecting the general trend of China’s exports to Central Asian countries, the highest dollar amounts for Chinese exports involved products to Kazakhstan across all analyzed harmonized system categories. The most significant dollar-denominated export growth was observed for Kyrgyzstan: the annual growth rate of China’s exports in electrical equipment in 2022 approaches 400 %, and for vehicles nearly 500 % in 2022 and about 300 % in 2023. Additionally, in optical and medical instruments, China’s 2022 exports grew by nearly 300 % to Kyrgyzstan and Turkmenistan from the previous year. When comparing China’s exports to Central Asia with its exports to Russia, it is evident that the dollar value of China’s exports to Russia is higher than to Central Asian countries, and the dollar value changes in exports are also more significant. For instance, in 2023, China’s exports of machinery to Russia amounted to $24 billion, while exports to the entire Central Asia region were approximately $7 billion. In the electrical equipment category, China’s exports to Russia were $13 billion compared to $5 billion to Central Asia. In the vehicles category, exports to Russia were $18 billion, while exports to Central Asia were $8 billion. On the other hand, the annual growth rates of individual Central Asian countries are higher in percentage terms compared to Russia. For example, as illustrated in Figure 12, China’s exports to Kyrgyzstan grew from $41 million in 2021 to $1.5 billion in 2022, while China’s exports to Russia increased from $1.2 billion dollars to $1.8 billion in the same period. The annual growth rates for Russia do not exhibit similar spikes, nor do they significantly exceed the growth rates for any Central Asian country in any category. 5. Central Asian exports to Russia in HS categories 84, 85, 87 and 90 In the HS categories 84 (Machinery), 85 (Electrical equipment), 87 (Vehicles), and 90 (Optical and medical instruments), exports from Central Asian countries to Russia exhibited significant growth in 2022 (Figures 16 and 17), with continued expansion in 2023 (with the exception of Kazakhstan in vehicles and parts). In total, exports from Central Asia (Kazakhstan, Kyrgyzstan, Turkmenistan, and Uzbekistan) in these categories grew in 2022 by 600 % from the previous year. Notably, Kazakhstan was the biggest export in dollar terms. Its exports to Russia surged across all categories in 2022, with on-year growth rates for machinery, electrical equipment and sound devices, and optical and medical instruments ranging between 400 % and 600 %. In addition to Kazakhstan, Uzbekistan and Kyrgyzstan recorded substantial increases in exports in 2022, particularly in the machinery and electrical equipment categories. Kyrgyzstan’s exports machinery increased from $2 million in 2021 to $49 million in 2022, a jump of about 2,500 %. However, when comparing the Chinese exports to Kyrgyzstan in electrical equipment, the dollar value in exports to Russia seems considerably smaller. Thus, no direct conclusion should be drawn from the fact that higher quantities of electronics pass through Kyrgyzstan to Russia. Although not depicted in the graph, it is important to highlight Turkmenistan’s growth in the export of electrical equipment in 2023 when it grew from $2,075 (2022) to $3 million in 2023, onyear growth of approximately 200,000 %. Similarly, Uzbekistan’s annual growth in exports of optical and medical instruments was around 40,000 % in 2022. As to vehicles and parts, Kyrgyzstan’s export growth commenced already in 2021. In the optical and medical instruments category, both Kyrgyzstan and Uzbekistan experienced notable export growth, particularly in 2023. At the HS category levels of 84, 85, 87 and 90, data for Tajikistan’s exports to Russia were unavailable.     6. Conclusion Chinese exports to Central Asia have significantly increased since Russia’s 2022 invasion of Ukraine, with concurrent growth China’s exports to Russia. Notably, there was a substantial surge in Chinese exports to Kyrgyzstan prior to invasion. Chinese exports to Kyrgyzstan, which has a modest GDP, saw the largest dollar-value increase from 2021 to 2023 in the categories of footwear, textiles, and clothes, as well as machinery and vehicles starting in 2022. The annual growth rates in Chinese exports to Kyrgyzstan show clear increases in the major export categories in 2022.  In dollar terms, Chinese exports to Kazakhstan and Uzbekistan also rose significantly from 2018 to 2023. For Uzbekistan, the largest growth in China's exports began in 2021 in electronics. Exports to Kazakhstan grew the most in 2022–2023 in the categories of footwear, textiles, and clothes, and machinery and vehicles.  The trade categories with notable growth in Chinese exports to Central Asian countries were machinery (HS 84), electrical equipment (HS 85), vehicles (HS 87), and optical and medical instruments (HS 90). Generally, the steepest rise in Chinese exports to Central Asia occurred in the vehicles category, with significant increases in exports to Kazakhstan, Kyrgyzstan, and Uzbekistan in 2022 continuing to a sharp rise in 2023. The trend for Chinese vehicle exports to Russia is similar. It is worth noting that Chinese vehicle exports to the rest of the world also accelerated after 2020. Additionally, there was substantial growth in Chinese exports to Kyrgyzstan in the electrical equipment category in 2022 and 2023. In these categories, Chinese exports to Russia are significantly higher in dollar terms that exports to Central Asia. However, the annual growth rates in between 2018 and 2023 of Chinses exports to individual Central Asian countries have generally seen larger increases in percentage terms than those for Russia.  Exports from Central Asian countries to Russia in the selected key export categories increased significantly across all examined categories in 2022. Among Central Asian countries, Kazakhstan was the largest exporter to Russia in dollar terms from 2018 to 2023, with sharp growth in 2022 in all four categories examined in this paper. Additionally, the exports of Uzbekistan and Kyrgyzstan to Russia grew significantly in 2022, particularly in the categories of machinery, and electrical equipment. The most notable annual growth in exports was posted by Turkmenistan – an increase from $2,075 in 2022 to $3 million in 2023, a 200,000 % increase in electrical equipment exports from the previous year. References Chupilkin, Maxim and Javorcik, Beata and Plekhanov, Alexander. (2023). The Eurasian Roundabout: Trade Flows Into Russia Through the Caucasus and Central Asia. EBRD Working Paper No. 276, Available at SSRN: http://dx.doi.org/10.2139/ssrn.4368618 or https://ssrn.com/abstract=4368618 Kluge, Janis. (2024). Russia-China economic relations: Moscow’s road to economic dependence, SWP Research Paper, No. 6/2024, Stiftung Wissenschaft und Politik (SWP), Berlin, https://doi.org/10.18449/2024RP06 Simola, H. (2024). Recent trends in Russia’s import substitution of technology products. BOFIT Policy Brief 5/2024, June 2024.  World Bank, 2024, read 14.8.2024, https://www.worldbank.org/en/region/eca/brief/central-asia 1 Harmonized System code 84: Nuclear reactors, boilers, machinery and mechanical appliances; parts thereof.  2 Harmonized System code 85: Electrical machinery and equipment and parts thereof; sound recorders and reproducers, television image and sound recorders and reproducers, and parts and accessories of such articles.  3 Harmonized System code 87: Vehicles other than railway or tramway rolling stock, and parts and accessories thereof.  4 Harmonized System code 90: Optical, photographic, cinematographic, measuring, checking, precision, medical or surgical instruments and apparatus; parts and accessories thereof. 5 Harmonized System code 88: Aircraft, spacecraft, and parts thereof.  6 Harmonized System code 89: Ships, boats, and floating structures.