A Prediction Model for Spot LNG Prices Based on Machine Learning Algorithms to Reduce Fluctuation Risks in Purchasing Prices

The ongoing Russia–Ukraine conflict has exacerbated the global crisis of natural gas supply, particularly in Europe. During the winter season, major importers of liquefied natural gas (LNG), such as South Korea and Japan, were directly affected by fluctuating spot LNG prices. This study aimed to use machine learning (ML) to predict the Japan Korea Marker (JKM), a spot LNG price index, to reduce price fluctuation risks for LNG importers such as the Korean Gas Corporation (KOGAS). Hence, price prediction models were developed based on long short-term memory (LSTM), artificial neural network (ANN), and support vector machine (SVM) algorithms, which were used for time series data prediction. Eighty-seven variables were collected for JKM prediction, of which eight were selected for modeling. Four scenarios (scenarios A, B, C, and D) were devised and tested to analyze the effect of each variable on the performance of the models. Among the eight variables, JKM, national balancing point (NBP), and Brent price indexes demonstrated the largest effects on the performance of the ML models. In contrast, the variable of LNG import volume in China had the least effect. The LSTM model showed a mean absolute error (MAE) of 0.195, making it the best-performing algorithm. However, the LSTM model demonstrated a decreased in performance of at least 57% during the COVID-19 period, which raises concerns regarding the reliability of the test results obtained during that time. The study compared the ML models' prediction performances with those of the traditional statistical model, autoregressive integrated moving averages (ARIMA), to verify their effectiveness. The comparison results showed that the LSTM model's performance deviated by an MAE of 15–22%, which can be attributed to the constraints of the small dataset size and conceptual structural differences between the ML and ARIMA models. However, if a sufficiently large dataset can be secured for training, the ML model is expected to perform better than the ARIMA. Additionally, separate tests were conducted to predict the trends of JKM fluctuations and comprehensively validate the practicality of the ML models. Based on the test results, LSTM model, identified as the optimal ML algorithm, achieved a performance of 53% during the regular period and 57% d during the abnormal period (i.e., COVID-19). Subject matter experts agreed that the performance of the ML models could be improved through additional studies, ultimately reducing the risk of price fluctuations when purchasing spot LNG. [ FROM AUTHOR] Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Dynamics of return and volatility spill-over between developed, emerging and African equity markets during the Covid-19 pandemic and Russia–Ukraine war

We contribute to the growing literature examining spill-over effects between international equity markets in the "new normal” disposition and extend upon previous studies to include more recent periods covering the Russia–Ukraine war. Using the Diebold and Yilmaz network method, we estimate the returns and volatility connectedness between developed, emerging and African markets over the period 11 March 2020 to 30 June 2022. Our findings can be summarised in three points. Firstly, the static connectedness analysis informs us that emerging and African (developed) markets are the main net receivers (transmitters) of systemic shocks over the sample period. Secondly, the time-varying connectedness analysis further informs us that network connectedness is higher during the Russia–Ukraine war compared to the announcement of Covid-19 variants. Thirdly, the time-varying market specific analysis distinguishes which individual equities are most or least vulnerable to systemic shocks during the Covid-19 pandemic and Russia–Ukraine war. These findings are relevant for investors in their search for better hedging opportunities in equity markets. Moreover, market regulators should take heed of our findings as the observed build-up of systemic risk following the Russia–Ukraine conflict is an indicative of contagion effects experienced. © 2023 Stellenbosch University.

Dynamic spillover and systemic importance analysis of global clean energy companies: A tail risk network perspective

This paper conducts tail risk spillover and systemic importance analysis based on the firm-level data of global clean energy system. The tail risk network is constructed based on the ΔCoVaR method, where the correlation is calculated from three perspectives: market, sector and institution. Moreover, the systematically important institutions are identified through a PageRank-based approach. We find that two industries contribute the largest in the risk transmission process, and most of the identified important institutions come from these industries as well. Also, it is observed that the COVID-19 pandemic and the Russia–Ukraine conflict would render different impacts on the risk contagion.

Time-frequency volatility connectedness between fossil energy and agricultural commodities: Comparing the COVID-19 pandemic with the Russia-Ukraine conflict

This paper uses the TVP-VAR frequency connectedness approach to compare the volatility connectedness induced by the COVID-19 pandemic and the Russia-Ukraine conflict. Both shocks induce increased connectedness, but the pandemic shock is stronger. High-frequency and medium-frequency connectedness dominate during the early stage of the pandemic, while low-frequency connectedness dominates during the conflict. Moreover, fossil energy is the risk transmitter in the early phase of the pandemic, while agricultural commodities become the transmitter during the conflict. We should take precautions against risks contagion from fossil energy and agricultural commodities to the post-conflict economy, and prevent inflation and economic slowdown. © 2023 The Author(s)

Energy-conserving cryptocurrency response during the COVID-19 pandemic and amid the Russia–Ukraine conflict

PurposeThe mining process is essential in cryptocurrency networks. However, it consumes considerable electrical energy, which is undoubtedly harmful to the environment. In response, energy-conserving cryptocurrency projects with reduced energy requirements or based on renewable energies have been developed. Recently, the COVID-19 pandemic and the Russian invasion of Ukraine ignited an unprecedented upheaval in financial products, especially in cryptocurrency and energy markets. Therefore, the paper aims to explore the response of these energy-conserving cryptocurrencies to the COVID-19 pandemic and the Russia–Ukraine conflict.Design/methodology/approachThis paper investigates the response of these energy-conserving cryptocurrencies to the COVID-19 pandemic and the Russia–Ukraine conflict. Their competitiveness is compared with conventional ones by analyzing their efficiency through multifractal detrended fluctuation analysis and automatic variance ratio during the COVID-19 and Russian invasion periods.FindingsThe empirical results show that all investigated energy-conserving cryptocurrencies negatively responded to the pandemic and positively reacted to the Russian invasion. On the other hand, all conventional cryptocurrencies reacted negatively to the COVID-19 pandemic and the amid-Russian attack. Besides, Bitcoin and SolarCoin were the least inefficient before the outbreak of COVID-19. Nevertheless, the Ethereum market became the most efficient after the pandemic spread. Similarly, the efficiency of Ripple was the most significant during the conflict between Russia and Ukraine. The energy crisis caused by Russia benefited the efficiency of the studied energy-conserving cryptocurrencies.Practical implicationsThis research is of interest to investors seeking opportunities in these energy-conserving cryptocurrencies and policymakers working to implement reforms to improve their market efficiency and promote long-term financial market growth.Originality/valueTo the best of the authors' knowledge, the behavior of cryptocurrencies based on renewable and reduced energy during the recent conflict between Russia and Ukraine has not been explored.

Material flow and economic cost analysis of the Italian artisan bread production before and during the Russia-Ukraine conflict

The Russia-Ukraine conflict represents a humanitarian crisis and causes several socio-economic consequences, being Russia a key supplier of energy and food commodities. After a few weeks of war, the prices of the essential goods, already increased due to the COVID-19 pandemic crisis, have continued to boost. The present research applies the material flow analysis to assess the sustainability of the artisan bread production, comparing a baseline and a war scenario, before and during the aforementioned conflict, and estimates the economic costs associated with natural and energy resources. The analysis is based on primary data collected through semi-structured interviews among nine artisan bakeries and secondary data collected before and during the conflict. The economic assessment, which is applied to enhance the environmental management of sociometabolic systems, is conducted on the entire artisan bread produced in Italy in 2021 and the system boundaries consider a cradle-to-gate approach. The highest upsurge in input costs has been estimated in electricity (+400%), N fertilizer (+233%) and K2O (+152%). The average input cost variation has been evaluated at +232%. Possible opportunities to support production costs include the adoption of an alternative bread recipe, which reduces the supply of impacting resources without affecting the quality of the finished product, as well as the introduction of structural interventions to lower energy costs. The research could help both artisan bakers, to better manage resources, waste and related impacts under the economic and the environmental perspective, and public authorities, to define appropriate strategies to sustain the bread sector. Last, the research provides scholars with an original analysis of the economic costs in the artisan bread production, highlighting its suitability to evaluate the supply chain sustainability from cradle to gate. © 2023 Elsevier Inc.

Can Green Economy stocks hedge natural gas market risk? Evidence during Russia-Ukraine conflict and other crisis periods

One of the ultimate goals of the Green Economy is to move away from dependence on fossil energy, thereby achieving a sustainable development of a resource-saving and environment-friendly society. Thus, whether Green Economy stocks can hedge the risks of fossil energy markets, especially for natural gas market during recent crisis periods, is of great importance for both policy makers and portfolio managers. This paper identifies the time-varying connectedness and hedging effects of twelve NASDAQ OMX Green Economy sector stocks on NYMEX natural gas futures during three major turmoil events, i.e., European debt crisis, COVID-19 pandemic, and recent Russia-Ukraine conflict. The empirical results show that various Green Economy sector stocks can provide gratifying hedge effectiveness on the market risk of natural gas futures, and some of them can even perform similarly to gold and USD. Moreover, NASDAQ OMX Green Economy sector stocks offer better hedge effectiveness during recent Russia-Ukraine conflict than those of them in the periods of European debt crisis and COVID-19 pandemic. Finally, the Sharpe ratio results further show the important but time-varying roles of Green Economy sector stocks in hedging risks of natural gas market. © 2023 Elsevier Inc.

The impact of the Russia–Ukraine conflict (2022) on volatility connectedness between the Egyptian stock market sectors: evidence from the DCC-GARCH-CONNECTEDNESS approach

Purpose>This study investigates the impact of the Russia–Ukraine war (2022) on the volatility connectedness between Egyptian stock market sectors.Design/methodology/approach>This study employs the newest dynamic conditional correlation (DCC)-generalized autoregressive conditional heteroskedasticity (GARCH)-CONNECTEDNESS approach to examine volatility connectedness in a sample of ten sectors in the Egyptian stock market, namely banks, education, food, healthcare, industry, information technology, real estate, resources, transportation and travel, ranging from February 1, 2019 to May 31, 2022.Findings>The findings show that connectedness among the Egyptian stock market sectors varies depending on the time. The average dynamic connectedness measure among sectors in Egypt is 73.24%. This average was 85.63% during the Russia–Ukraine War (2022). The author also shows that the transportation sector is the most significant net transmitter of volatility in the remaining sectors during the Russia–Ukraine War (2022).Practical implications>This study intends for policymakers to examine the co-movements, market variations and volatility spillover of stock markets, particularly during crises. Furthermore, the results help investors gain insight into diversifying the investors' portfolio assets to optimize profits.Originality/value>To the best of the authors' knowledge, no study has investigated the implications of the war between Russia and Ukraine (2022) on sectoral interconnectedness within the stock markets in any country and discussion and empirical evidence from African countries are lacking. This study fills this gap in the literature. Additionally, the author uses the newest approach, the DCC-GARCH-CONNECTEDNESS approach, to describe the time-varying volatility spillover between economic sectors in Egypt.

The Russia-Ukraine conflict and foreign stocks on the US market

PurposeThe authors investigate how market quality diverges between foreign firms and domestic firms on the US stock market in response to the Russia-Ukraine conflict.Design/methodology/approachWith an event study approach, the authors compare foreign firms with domestic firms in their market responses over the three-day window around the outbreak of the war. Further, with Difference-in-Difference (DID) analyses, the authors study the change in foreign firms' market quality upon this outbreak in comparison with their domestic counterparts. Finally, the authors compare the foreign firms across firm specific characteristics and home country characteristics.FindingsThe authors find that foreign stocks listed in the US experience more severe market quality deterioration compared to the stocks' domestic counterparts. This effect is especially strong for companies from countries considered friendlier towards Russia and companies that are not cross-listed. The authors' findings are consistent with the information asymmetry hypothesis concerning market quality. Moreover, US market investors have more concerns over political risks with non-US-aligned political standings during war times.Research limitations/implicationsThe authors' findings are consistent with the information asymmetry hypothesis concerning market quality. Moreover, US market investors have more concerns over political risks over non-US-aligned political standings during war time.Practical implicationsSince both countries in the conflict are in Europe, the US stock market, to a certain degree, becomes a safe haven for capital from Europe and other countries. In the meantime, American Depository Receipts (ADRs) have been important for US investors to create a globally diversified portfolio, and the knowledge regarding ADRs' vulnerability to international geopolitical events is valuable. The author' results are informative for stock market investors to understand the market dynamics for international and domestic companies during this extremely uncertain time.Originality/valueThis is the first study that examines the market quality divergence between foreign firms and domestic firms on the US stock market in response to the Russia-Ukraine conflict. The authors provide novel evidence on the change in ADRs' market quality associated with significant political uncertainty. The authors show that ADRs' market quality is more vulnerable to international geopolitical risks relative to otherwise comparable domestic firms.

Energy-conserving cryptocurrency response during the COVID-19 pandemic and amid the Russia-Ukraine conflict

PurposeThe mining process is essential in cryptocurrency networks. However, it consumes considerable electrical energy, which is undoubtedly harmful to the environment. In response, energy-conserving cryptocurrency projects with reduced energy requirements or based on renewable energies have been developed. Recently, the COVID-19 pandemic and the Russian invasion of Ukraine ignited an unprecedented upheaval in financial products, especially in cryptocurrency and energy markets. Therefore, the paper aims to explore the response of these energy-conserving cryptocurrencies to the COVID-19 pandemic and the Russia-Ukraine conflict.Design/methodology/approachThis paper investigates the response of these energy-conserving cryptocurrencies to the COVID-19 pandemic and the Russia-Ukraine conflict. Their competitiveness is compared with conventional ones by analyzing their efficiency through multifractal detrended fluctuation analysis and automatic variance ratio during the COVID-19 and Russian invasion periods.FindingsThe empirical results show that all investigated energy-conserving cryptocurrencies negatively responded to the pandemic and positively reacted to the Russian invasion. On the other hand, all conventional cryptocurrencies reacted negatively to the COVID-19 pandemic and the amid-Russian attack. Besides, Bitcoin and SolarCoin were the least inefficient before the outbreak of COVID-19. Nevertheless, the Ethereum market became the most efficient after the pandemic spread. Similarly, the efficiency of Ripple was the most significant during the conflict between Russia and Ukraine. The energy crisis caused by Russia benefited the efficiency of the studied energy-conserving cryptocurrencies.Practical implicationsThis research is of interest to investors seeking opportunities in these energy-conserving cryptocurrencies and policymakers working to implement reforms to improve their market efficiency and promote long-term financial market growth.Originality/valueTo the best of the authors' knowledge, the behavior of cryptocurrencies based on renewable and reduced energy during the recent conflict between Russia and Ukraine has not been explored.

Can Green Economy stocks hedge natural gas market risk? Evidence during Russia-Ukraine conflict and other crisis periods

One of the ultimate goals of the Green Economy is to move away from dependence on fossil energy, thereby achieving a sustainable development of a resource-saving and environment-friendly society. Thus, whether Green Economy stocks can hedge the risks of fossil energy markets, especially for natural gas market during recent crisis periods, is of great importance for both policy makers and portfolio managers. This paper identifies the time-varying connectedness and hedging effects of twelve NASDAQ OMX Green Economy sector stocks on NYMEX natural gas futures during three major turmoil events, i.e., European debt crisis, COVID-19 pandemic, and recent Russia-Ukraine conflict. The empirical results show that various Green Economy sector stocks can provide gratifying hedge effectiveness on the market risk of natural gas futures, and some of them can even perform similarly to gold and USD. Moreover, NASDAQ OMX Green Economy sector stocks offer better hedge effectiveness during recent Russia-Ukraine conflict than those of them in the periods of European debt crisis and COVID-19 pandemic. Finally, the Sharpe ratio results further show the important but time-varying roles of Green Economy sector stocks in hedging risks of natural gas market.

Impacts of the COVID-19 Pandemic and the Russia-Ukraine Conflict on Land Use across the World

The impacts of the COVID-19 pandemic and the Russia-Ukraine crisis on the world economy are real. However, these implications do not appear to be symmetric across countries and different economic sectors. Indeed, the consequences of these two shocks are more severe for some countries, regions and economic activities than for others. Considering the importance of the agricultural sector for global food security, it is important to understand the impacts of the pandemic and the conflict on the different dimensions of agriculture, namely land use. Given the scarcity of data for the last few years available from the various statistical databases, this research mainly considers the insights highlighted in the literature on the implications, in agricultural dimensions, of the most recent shocks. The study here presented shows that the Russia-Ukraine crisis has had more impact on land use changes than the pandemic, namely promoting adjustments in the decisions of farmers and policymakers to deal with constraints in agri-food chains. Nonetheless, the impacts of the conflict on land use were not totally explored.

Infection, invasion, and inflation: Recent lessons

We examine the relationship between the ex-post inflation rates in the G7 countries, using a connectedness approach. Results obtained through both static and dynamic analyses confirm the US (Italy) as the main transmission (absorption) channel for inflation. Our dynamic analysis shows that the magnitude of inflation spillovers peaked during earlier market crises such as the 2008 subprime-crisis and the 2011 European debt-crisis. High level of connectedness is also witnessed during COVID-19 period and particularly surged due to the 2022 Russia-Ukraine conflict. The results may be important for corporate and national policymakers, seeking for monitoring and mapping the evolution of inflation.

Searching for a safe haven to crude oil: Green bond or precious metals?

In this paper, we explore whether the green bond, a kind of rarely discussed fixed-income asset, acts as a hedge or safe haven to crude oil in extreme market conditions, by comparing the results with precious metals. The green bond has negative correlations with crude oil when the COVID-19 pandemic and the Russia-Ukraine conflict outbreak, and the highest risk reduction effectiveness among all assets, indicating that investors benefit the most from adding the green bond to their portfolios. Applying the model purposed by Baur and McDermott (2010), we further find that the green bond is both a strong safe haven and a strong hedge for the crude oil market, gold is a weak safe haven and a strong hedge, silver only acts as a weak hedge, and other precious metals are neither safe haven nor hedge. Our results reveal that crude oil market investors can hedge the risk during the extreme rise and fall periods by including the green bond in their portfolios.

UEF Statement on the War in Ukraine

The article examines that the covid-19 pandemic and Russian President Vladimir Putin´s aggression to Ukraine have ushered a new era for Europe. Topics include considered this calls for a more proactive European action in different policy fields, such as health, economic and social recovery, foreign policy, defense and security, energy, and migration, among others.