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This paper attempts to investigate the impact of the Russia–Ukraine war on the returns and volatility of the United States (US) natural gas futures market.

The study uses secondary data of 996 trading day provided by the US Department of Energy and investing.com websites and applies the event study methodology in addition to the generalized autoregressive conditional heteroscedastic (GARCH) family models.

The findings from the exponential EGARCH (1,1) estimate are the best indication of a significant positive effects of the Ukraine–Russia war on the returns and volatility of the US natural gas futures prices. The cumulative abnormal returns (CARs) of the event study show that the natural gas futures prices reacted negatively but not significantly to the Russian–Ukraine war at the event date window [−1,1] and the [−15, −4] event window. CARs for the longer pre and post-event window display significant positive values and coincides with the standard finance theory for the case of the US natural gas futures over the Russia–Ukraine conflict.

This is the first study to examine the impact of the Russia–Ukraine war on natural gas futures prices in the United States. Thus, it provides indications on the behavior of investors in this market and proposes new empirical evidence that help in investment analyses and decisions.

This study investigates the impacts of the Russia–Ukraine conflict on the cross-correlation between agricultural commodity prices and crude oil prices.

The authors used MultiFractal Detrended Fluctuation Cross-Correlation Analysis (MF-X-DFA) to explore the correlation behavior before and during conflict. The authors analyzed the price connections between future prices for crude oil and agricultural commodities. Data consists of daily futures price returns for agricultural commodities (Corn, Soybean and Wheat) and Crude Oil (Brent) traded on the Chicago Mercantile Exchange from Aug 3, 2020, to July 29, 2022.

The results suggest that cross-correlation behavior changed after the conflict. The multifractal behavior was observed in the cross correlations. The Russia–Ukraine conflict caused an increase in the series' fractal strength. The study findings showed that the correlations involving the wheat market were higher and anti-persistent behavior was observed.

The study was limited by the number of observations after the Russia–Ukraine conflict.

This study contributes to the literature that investigates the impact of the Russia–Ukraine conflict on the financial market. As this is a recent event, as far as we know, we did not find another study that investigated cross-correlation in agricultural commodities using multifractal analysis.

This paper aims to investigate the impact of geopolitical events of the Russia–Ukraine conflict on the stock market volatility of G20 countries. Furthermore, the paper also investigates the possible reasons for any similarities or differences in the results of the three sectors.

This paper measures the impact of the stock market sectoral index price (SIP) by using the daily closing price as a dependent variable. In addition, this study uses three independent variables: geopolitical risk (GPR), commodity price (CP) and foreign exchange rate (FER). Seventeen countries from the G20 are analyzed using a daily timeframe from September 2021 to August 2022 (before and during the Russian invasion).

The results revealed that FER, CP and GPR all affect SIP, but the level of significance and positive/negative signs vary in all three sectors. The positive FER affects SIP in all sectors, while the negative CP and GPR significantly impact SIP in the energy and transportation sectors.

This study’s research model is more suited for transportation and energy than consumer goods. Future researchers can enhance the research model for the consumer goods sector by incorporating additional variables to understand their relationship with SIP better.

This study explores the impact of the Russia–Ukraine conflict on the stock market in G20 countries, focusing on the top three most affected sectors.

The recent Russia–Ukraine conflict highlights the geopolitical importance of natural gas, especially in Europe. In this light, this study examines the impact of the Russia–Ukraine conflict on the spread of price bubbles from European natural gas to international energy prices.

The Generalized Supremum Augmented Dickey-Fuller (GSADF) test is employed to detect the occurrence of price bubble episodes while the Dynamic Logit Model is used to examine price bubble contagion between the two markets. Further, a tri-variate VAR model is used to examine the determinants of the price bubble.

The findings reveal multiple bubble episodes in both European natural gas and international energy prices. Further, evidence of bilateral contagion between European natural gas and the international energy market is found. In addition, the Russia–Ukraine conflict triggers price bubble episodes in both markets. Finally, a counterfactual analysis suggests that the conflict increases the bubble contagion from the European natural gas market to the international energy market by about 40%. These findings imply that the Russia–Ukraine conflict is a significant driver of high upside risks to bubble occurrence and subsequent contagion to both European natural gas and international energy prices.

To the best of our knowledge, this study contributes new empirical evidence that the Russian–Ukrainian conflict significantly impacts the spread of price bubbles from the European natural gas market to international energy markets.

The European Union (EU) and Russia are considered to be trapped into security concerns in a form of spillover, in a zero sum perspective, considering each step of the other as directed against another. Such an approach seems to prevail, after attempts of engagements for decades after the Cold War. Rather history prevailed in informing perceptions and currently driving the behaviors toward each other, in other words in othering each other.

Discourse analysis

The move in Eastern Europe of both parties is perceived with suspicion from both sides, materialized through their policies, culminated in clash of interests and crash of policies between both parts, manifested by Russian aggression in Ukraine in 2014 and recently in 2022 in one side, and the EU response through massive, unprecedented sanctions against Russia. This has created a context that fosters not just keeping a status quo of clash and struggle for influence between them in the region, but also nourishes further securitization of their respective policies toward the Eastern Europe and beyond. In 2014 and more recently in 2022 Russian aggression in Ukraine, the EU and Russia appear to have the same image to each other as they had during the Cold War, or even beyond. Having this in mind, this paper will address those developments, with particular focus on attempts to avoid them, the failure to do so and how they are impacting the EU, Russia and global politics in a form of emerging new world (dis)order.

This paper is an original paper having a critical approach toward the current conflicts going on in Eastern Europe.

Social media has played a pivotal role in polarizing views on Russia–Ukraine conflict. The effects of polarization in online interactions have been extensively studied in many contexts. This research aims to examine how multiple social media sources may act as an integrator of information and act as a platform for depolarizing behaviors.

This study analyzes the communications of 6,662 tweets related to the sanctions imposed on Russia by using textual analytics and predictive modeling.

The research findings reveal that the tweeting behavior of netizens was depolarized because of information from multiple social media sources. However, the influx of information from non-organizational sources such as trending topics and discussions has a depolarizing impact on the user’s pre-established attitude.

For policymakers, conflict mediators and observers, and members of society in general, there is a need for (1) continuous and consistent communication throughout the crisis, (2) transparency in the information being communicated and (3) public awareness of the polarized and conflicting information being provided from multiple actors that may be biased in the claims being made about the conflict crisis.

While previous research has examined Russia–Ukraine conflict from a variety of perspectives, this is the first study to examine how social media might be used to reduce attitude polarization during times of conflict.

This paper aims to examine the short-term market impact of the beginning of the military conflict between Russia and Ukraine (24 February 2022), the world’s largest oil and gas companies.

The authors examine the world’s 100 largest listed oil and gas companies at and around the beginning of the military conflict between Russia and Ukraine using an event study methodology.

The authors observe a positive and statistically significant stock price reaction at and around the military conflict. These results are consistent with the asset pricing perspective. Conversely, the stock market returns of Russian oil and gas companies, as well as those companies that were “forced” to divest in Russia due to corporate activism, exhibit a negative and statistically significant impact from the conflict. These reactions are reinforced or mitigated by company-specific characteristics such as size, profitability and institutional ownership. Finally, the findings indicate that companies engaged in oil and gas exploration and production report abnormally higher returns compared to firms in the other two subsectors of the industry.

The effect of the war on stock markets has been relatively little examined in the financial theory. This study intends to fill this gap in the literature.

This paper aims to investigate the safe haven feature of Bitcoin, gold and two gold-backed cryptocurrencies (DGX and PAXG) against energy and agricultural commodities (crude oil, natural gas and wheat) during the COVID-19 pandemic, the Russia–Ukraine conflict and the Silicon Valley Bank (SVB) collapse.

The authors use the threshold GARCH (T-GARCH)-asymmetric dynamic conditional correlation (ADCC) model to evaluate the asymmetric dynamic conditional correlation between the return series and compare the diversifying, hedging and safe-haven ability of Bitcoin, gold and the two gold-backed cryptocurrencies (DGX and PAXG) against financial swings in the commodity market during the COVID-19 outbreak, the Russian–Ukrainian military conflict and SVB collapse. The authors also calculate the hedging ratios (HR) and hedging effectiveness index (HE). The authors finally use the wavelet coherence (WC) approach to check our results’ robustness and further investigate the impact of the three crises on the relationship between Bitcoin, gold gold-backed cryptocurrencies and commodities.

The results show that PAXG serves as a strong hedging instrument while gold, Bitcoin and DGX act as strong diversifiers during normal times. During crises, gold outperforms Bitcoin as a diversifier and a safe haven against commodities. Gold-backed cryptocurrencies also exhibit strong performance as diversifiers and safe havens. HR results indicate that Bitcoin and DGX are more cost-effective for commodities risk mitigation than gold and PAXG. In terms of hedging effectiveness, gold and PAXG emerge as the best hedging instruments for commodities, while DGX is considered the worst one. Bitcoin shows superior hedging against oil compared to wheat and gas risks. Moreover, the results of the WC approach confirm those of the T-GARCH-ADCC results in both the short and long run.

This paper provides a comprehensive analysis of the diversification ability of gold, Bitcoin and gold-backed cryptocurrencies during different crises (the COVID-19 pandemic, the Russia–Ukraine conflict and the SVB collapse). By taking into consideration gold-backed cryptocurrencies, the authors expand the understanding of safe havens beyond conventional assets.

Sharing and obtaining information over social media has enabled people to express their opinions regarding any event. Since the tweets regarding the Russia-Ukraine war were extensively publicized on social media, this study aims to analyse the temporal sentiments people express through tweets related to the war.

Relevant hashtag related to the Russia-Ukraine war was identified, and tweets were downloaded using Twitter API, which were later migrated to Orange Data mining software. Pre-processing techniques like transformation, tokenization, and filtering were applied to the extracted tweets. VADER (Valence Aware Dictionary for Sentiment Reasoning) sentiment analysis module of Orange software was used to categorize tweets into positive, negative and neutral ones based on the tweet polarity. For ascertaining the key and co-occurring terms and phrases in tweets and also to visualize the keyword clusters, VOSviewer, a data visualization software, was made use of.

An increase in the number of tweets is witnessed in the initial days, while a decline is observed over time. Most tweets are negative in nature, followed by positive and neutral ones. It is also ascertained that tweets from verified accounts are more impactful than unverified ones. russiaukrainewar, ukraine, russia, false, war, nato, zelensky and stoprussia are the dominant co-occurring keywords. Ukraine, Russia and Putin are the top hashtags for sentiment representation. India, the USA and the UK contribute the highest tweets.

The study tries to explore the public sentiments expressed over Twitter related to Russia-Ukraine war.

This study aims to empirically analyze the market response of energy companies to the Russian-Ukrainian invasion. Additionally, it examines the comparison of market reactions between companies in NATO member countries and non-member countries.

This study utilizes a sample of 1,511 energy sector companies. To achieve the research objectives, two methods are employed. First, an event study is used to analyze the market reaction using Cumulative Abnormal Return (CAR) to the announcement of Russia's invasion of Ukraine on February 24, 2022 (event day) within an event window of (−30, +30). Second, a cross-sectional analysis is conducted to compare the responses of companies in NATO member countries with those in non-member countries.

The findings of this study reveal that energy companies worldwide reacted positively both before and after the announcement of the invasion, with significant reactions observed in companies from the Americas, Europe, and Asia & Pacific regions. However, the Middle East and Africa markets did not show significant reactions. Furthermore, the study indicates that most developed and emerging markets responded positively, likely due to the increase in energy commodity prices during the war. Moreover, the market reaction of companies in NATO member countries was stronger compared to other markets.

This study contributes to the existing literature by being the first to examine the impact of the Russian invasion of Ukraine on the energy sector, while categorizing markets as developed, emerging, and frontier. It also specifically explores the market reaction of energy companies in NATO member countries, providing unique insights into the differential responses within the energy sector.

研究目的: 本研究擬以經驗及觀察為依據, 去分析能源公司對俄羅斯–烏克蘭侵略行為的市場反應。研究亦擬進行關於北約成員國內的能源公司及非成員國內的能源公司的市場反應的比較研究。

研究設計/方法/理念: 研究使用的樣本為1511間能源領域內的公司。研究人員為能達到研究目標, 採用了兩個方法。首先, 他們使用事件研究法進行有關的研究。具體地說, 他們以累積異常報酬率, 來分析在 (−30, +30) 的事件視窗之內, 能源公司對俄羅斯於2022年2月24日 (事發日) 入侵烏克蘭的公告的市場反應。其次, 研究人員以橫向分析法, 就北約成員國內的能源公司及非成員國內的能源公司的反應進行比較研究。

研究結果: 研究結果顯示, 全球的能源公司於侵略行為公告前後均有正面的反應;而反應較為顯著的公司均來自美洲、歐洲和亞洲及太平洋地區。唯中東和非洲市場均沒有顯著的反應。研究結果亦顯示, 大多數已發展市場和新興市場, 均有正面的反應, 這很可能是因為於戰爭期間, 能源商品價格上升所致。再者, 北約成員國內的公司的市場反應較其他市場強烈。

研究的原創性: 本研究率先以已開發市場、新興市場和邊境市場的市場分類, 去探討俄羅斯入侵烏克蘭對能源部門的影響;就此, 本研究對現有文獻作出了貢獻。研究亦特意探索了北約成員國內能源公司及非成員國內的能源公司兩者的市場反應, 這給我們獨特的啟示, 以能了解能源領域內各種不同的反應。