Non-energy Commodity Research Articles

Heterogeneous Responses of Energy and Non-Energy Assets to Crises in Commodity Markets

In this study, we investigate the heterogeneity in energy and non-energy commodities by analyzing their four realized moments: returns, realized volatility, realized skewness and realized kurtosis. Utilizing monthly data, we examine two commodity categories over various crisis periods. This study examines a comparative approach to descriptive statistics across different crisis periods and the full sample and assesses the out-of-sample significance of heteroscedasticity using GARCH models. The findings reveal significant heterogeneity in both energy and non-energy commodities, with energy commodities exhibiting higher average returns and volatility. Crisis periods markedly influence the statistical properties of these commodities. GARCH models outperform ARMA models in forecasting realized moments, particularly for non-energy commodities. This research contributes to the literature by providing robust evidence of heterogeneity in commodity markets and highlights the importance of considering all four realized moments in such analyses.

Consequences of using renewable energy sources

Developed countries offset global warming by abandoning high-carbon products in favour of low-carbon products and by introducing a transboundary carbon tax for those countries that are unable to make the transition immediately. One of the ways of the transition in developed countries is proposed generation of electricity from renewable energy sources (hereinafter referred to as RES). The purpose of the article is to assess the consequences of ­using RES as one of the ways to the transition to low-carbon products. RES are the object of the study, especially wind and solar power plants. Energy generation on them is considered an environmentally friendly production and does not require large operational costs. The subject of the study is economic relations that occur concerning construction and use of RES. The methodological basis of the study includes general scientific methods (generalization, systematisation) and economic-statistical methods (comparative analysis, tabular techniques for data visualisation). The main results of the study lie in justifying large investment costs in RES which are associated with provision of significant areas of land and sea and their withdrawal from agricultural turnover; with scarce and poorly developed deposits of non-energy commodities which are necessary for the creation of RES equipment; with unevenness in energy production and its low density in wind and solar power plants. That requires investments in storage and balancing systems. In pursuit of environmentally friendly production the West does not consider many components of economic efficiency: environmental protection and safety of working and living conditions of some countries in Asia, Africa and South America, and natural means of absorbing greenhouse gases. It should be ignored in the future when justifying economic efficiency of RES.

High inflation during Russia–Ukraine war and financial market interaction: Evidence from C-Vine Copula and SETAR models

This paper examines the interaction between three financial markets: energy and non-energy commodities, bonds and equities, in a particular context of high inflation worldwide, that of Russia–Ukraine war. Our data cover the period January 2016-October 2022. Using a SETAR-GARCH C-Vine Copula model, we provide evidence of two inflation breakouts within COVID pandemic and shortly before Russia–Ukraine war, for all assets considered, and particularly for US 10-Year bond, as an inflation-indexed asset. Over the Russia–Ukraine war period, both linear and nonlinear models explain the studied assets’ behavior faced with high inflation. C-Vine Copula analysis shows that oil prices (WTI), as an inflation-producing assets, impact the volatility of financial markets (VIX) in times of war. This analysis indicates also that the NASDAQ index, as an inflation-exposed assets, is sensitive to commodities and energy prices that drive inflation. Furthermore, we find a high positive Kendall’s tau for all combinations between US 10-Year and all other assets. These results provide strong evidence of the association between US 10-Year futures, as a vehicle of inflation, and all studied assets. Lastly, our findings confirm the evidence that Russia–Ukraine war generated two significant shocks, Gas (NG) prices and financial markets’ volatility (VIX). This study is of crucial interest to policy and decision makers to the extent that it provides a framework for understanding, in a context of high inflation, the mechanisms linked to the vehicles for transmitting this inflation, its pricing process, and its impact on the equity market.

Exploring the dynamic connectedness and portfolio diversification strategies between energy and non-energy commodities in India

Exploring the dynamic connectedness and portfolio diversification strategies between energy and non-energy commodities in India

Does COVID-19 Epidemic Change the Risk Spillover Characteristics of Chinese Carbon Markets with Energy, Non-Energy Commodity and Stock Markets? Evidence from a Novel Network Method

This paper investigates the multi-dimensional risk spillover effects of carbon markets with energy, non-energy commodity and stock markets in China before and after the COVID-19 outbreak, through the DY network with GARCHSK-VaR method. The empirical results denote that the total bidirectional risk spillovers of carbon markets become larger after the COVID-19 outbreak than before the COVID-19 outbreak. Interestingly, in both periods, energy is the largest risk contributor to carbon markets, while carbon markets become the net risk contributors to stock markets under COVID-19. Furthermore, compared with Guangdong pilot, the impacts of Hubei pilot on other markets are stronger in both periods. Finally, the dynamic risk spillover effects have obvious differences between before and after the COVID-19 outbreak.

TESTING VOLATILITY PERSISTENCE WITH FRACTIONAL INTEGRATIONAND COINTEGRATION IN WORLDWIDE COMMODITY MARKETS

In this paper, we examine the volatility of commodity prices around the world using monthly data for the time period 1960–2022. During this period, there were significant economic crises that increased the prices of both energy and non-energy commodities in the short term. These past crises may provide insights into the behavior of current crises, as they generally exhibit similar patterns. We use fractional integration methods and find that the volatility for each variable exhibits mean reversion, with the effect of the shocks disappearing in the long run. While this may seem obvious, our paper is the first to empirically demonstrate this significant process of convergence using a flexible time series model. As an additional contribution, we complement our analysis by incorporating a fractional cointegration test to examine potential relationships among the commodity prices. Our findings reveal the existence of four distinct cointegrating relationships within the set of ten commodity prices. This implies that these commodities are not entirely independent and may share underlying connections that contribute to their price movements over time. This valuable insight further enriches our understanding of the intricate interactions within the commodity market. We conclude that although countries do not have effective policies for mitigating volatility, it is only a short-term phenomenon that will disappear in the long term.

Мировая кризисная ситуация и сырьевые рынки: анализ, тенденции, перспективы, риски

Based on various statistical and analytical sources, the article analyzes the current state and main trends of commodity markets. It shows the importance and role of commodities in the gross product and budget of the country. The main groups of commodity markets are classified according to their specific weight. The contribution of the most important energy and non-energy commodities in the country's economy is considered. Based on the analysis, conclusions and prospects are made, and the main risks in the current crisis are identified. Proposals for ways out of the difficult situation were made. It is noted that the crisis can play a positive role in the removal of disparities and contradictions and reaching a new long-term level of development.

High frequency volatility spillover between oil and non-energy commodities during crisis and tranquil periods.

In this article, we scrutinize volatility spillover between oil and individual non-energy commodities during crisis and non-crisis periods. We use high-frequency data to capture the effects of both the global financial crisis (2008) and the COVID-19 pandemic between 2008 and 2022. To this end, we utilize wavelet coherence analysis to diagnose the magnitudes of dynamic co-movements and lead-lag effects between commodities. Our results provide evidence of strong coherence between oil and the majority of individual non-energy commodities during both crises. Precious metals were generally found to exhibit heightened levels of co-movement with oil as opposed to other non-energy commodities. On the other hand, weak co-movements were found between oil and a few commodities, namely soy, wheat, zinc, and tin. The lead-lag effects of oil on agricultural commodities, base metals, and precious metals were evident, especially during crisis periods. However, aluminium and precious metals, especially gold, silver, and palladium, also had a lead-lag effect on oil at different points in time, including during the pandemic. We further utilize dynamic frequency-domain connectedness for capturing pairwise volatility spillover indices, with the results providing evidence of heightened volatility spillovers during turbulent times. Our findings have significant implications for retail investors, portfolio managers, and policymakers.

Co-movement between commodity and equity markets revisited—An application of the Thick Pen method

This paper analyses interdependence between the returns of specific energy and non-energy commodities and equities using (i) Thick Pen Measure of Association (TPMA) and (ii) Multi-Thickness Thick Pen Measure of Association (MTTPMA). We capture time-varying co-movement and co-movement across different time scales to analyse the short-term and long-term features of the time series using stationary data. Energy index futures show an increase in co-movement with equities since the start of the financialisation period. There are asymmetric effects in cross-scale co-movement between various commodities and equities. Weak co-movement between equity and specific commodity futures indicates diversification benefits for short-term and long-term investors.

Global Money Supply and Energy and Non-Energy Commodity Prices: A MS-TV-VAR Approach

Global Money Supply and Energy and Non-Energy Commodity Prices: A MS-TV-VAR Approach

Modelling systemic risk of energy and non-energy commodity markets during the COVID-19 pandemic.

COVID-19 led restrictions make it imperative to study how pandemic affects the systemic risk profile of global commodities network. Therefore, we investigate the systemic risk profile of global commodities network as represented by energy and nonenergy commodity markets (precious metals, industrial metals, and agriculture) in pre- and post-crisis period. We use neural network quantile regression approach of Keilbar and Wang (Empir Econ 62:1–26, 2021) using daily data for the period 01 January 2018–27 October 2021. The findings suggest that at the onset of COVID-19, the two firm-specific risk measures namely value at risk and conditional value of risk explode pointing to increasing systemic risk in COVID-19 period. The risk spillover network analysis reveals moderate to high lower tail connectedness of commodities within each sector and low tail connectedness of energy commodities with the other sectors for both pre- and post-COVID-19 periods. The Systemic Network Risk Index reveals an abrupt increase in systemic risk at the start of pandemic, followed by gradual stabilization. We rank commodities in terms of systemic fragility index and observe that in post COVID-19 period, gold, silver, copper, and zinc are the most fragile commodities while wheat and sugar are the least fragile commodities. We use Systemic Hazard Index to rank commodities with respect to their risk contribution to global commodities network. During post COVID-19 period, the energy commodities (except natural gas) contribute most to the systemic risk. Our study has important implications for policymakers and the investment industry.

Time‐varying pure contagion effect between energy and nonenergy commodity markets

AbstractThis paper combines the Kalman filtering technique and the time‐varying parameter vector autoregression model with stochastic volatility model to explore pure contagion effects between energy and nonenergy (i.e., industrial metals, precious metals, and agricultural) commodity markets. Empirical results show the significant pure contagion effects between energy and industrial metals markets in most periods, while pure contagion effects between energy and precious metals and agricultural markets occur only in a few specific periods. Comparing the level of pure contagion effects between different commodity markets, energy is still the main price transmitter. In addition, with the acceleration of the global commodity market financialization process, the frequency and harm of pure contagion effects are gradually increasing. Notably, the COVID‐19 pandemic is emerging as another major crisis after the global financial crisis, exacerbating the pure contagion effects between energy and precious metals and agricultural markets.

Time-frequency connectedness between energy and nonenergy commodity markets during COVID-19: Evidence from China

We aim to investigate the static and dynamic time-frequency connectedness between energy and nonenergy commodity markets in China during COVID-19 based on Baruník and Křehlík (2018) method. First, in this paper, we find that the short-term connectedness dominates the long-term one, and the total connectedness increases after the COVID-19 outbreak. Second, the energy commodity is the receiver and is influenced much by the spillovers of non-energy commodity markets (e.g. chemical commodities and non-ferrous metals) in the short run. At the same time, the impact is less at the long-term investment horizons. In addition, chemical commodities and soft commodities are the primary transmitters in this system in the short run. In contrast, chemical commodities and coal steel iron commodities are the main long-run primary transmitters. Third, the spillover role varies with the time-frequency domain during COVID-19. To be more specific, the energy commodity shows a net receiver role in the short and long run before the COVID-19 pandemic, but after it, the role of the net transmitter can be seen in the long run with ease. Finally, we show that COVID can reduce the hedging effectiveness at different investment horizons. The mineral policymakers should note our dynamic empirical results between energy and nonenergy commodity.

MODERN TOOLS TO PROMOTE EXPORT-ORIENTED INVESTMENT PROJECTS

Currently, in the field of foreign economic activity of the Russian Federation, the strategic task of increasing the volume of non-resource non-energy exports is being implemented, which is impossible without increasing the investment activity of Russian exporters. The authors have analyzed the current state, dynamics and structure of investments in the Russian Federation. A list of negative factors hindering the implementation of export-oriented investment projects has been determined. It is indicated that potential and existing investors in the field of foreign trade activities can take advantage of both general and specific measures to stimulate the investment process. Using the methods of comparison, system analysis and generalization, a characterization of modern measures of state support for the investment activities of export producers has been carried out, the most promising of which, according to the authors, are the corporate program to increase competitiveness, the mechanism of agreements on the protection and promotion of capital investments and the modernized version of the special investment contract. It has been identified what negative factors hindering the investment process can be minimized through the mechanisms under consideration to support investors from the state in the implementation of export-oriented projects. The conditions limiting the use of the analyzed tools to increase the investment activity of exporters are indicated. The results of the study can be used by potential investors when choosing a state program to stimulate investments in fixed capital of exporters of non-energy commodities.

Impacts of international trade on global inequality of energy and water use

We are not on track to meet the SDGs by 2030 despite considerable efforts. Sino-US trade war and the COVID-19 pandemic raise the tide of trade protection that may also go against SDGs. To explore how international trade affects SDGs, this study quantifies the impacts of international trade on global energy and water inequality by constructing resource-Gini-coefficients in terms of reserve, production, and consumption. We find that international trade alleviates global inequality in energy use, in which direct energy trade reduces the inequality significantly while nonenergy commodity trade aggravates it slightly. However, international trade has a pretty minor impact on improving global water inequality. The developing economies suffer a large amount of embodied energy and water outflows. For example, BRICS exported 712.3 Mtoe of embodied energy and 130.5 billion m3 of virtual water to the rest of the world, exceeding the sum of energy/water use in Germany and France. The developed economies, especially the USA and EU, outsource energy- and water-intensive commodities to reduce domestic energy shortage and water stress, roughly corresponding to India's energy use and two times of water use of South Africa.

The Impact of Energy Commodity Prices on Selected Clean Energy Metal Prices

The United Nations Framework Convention on Climate Change Paris Agreement has been announced as a crucial step towards combating the global threat of climate change. In the light of ambitious plans for further renewable energy sources development, high demand for nonenergy materials critical for RES is greatly expected. In conclusion, future energy security will be surely based on nonenergy commodities critical for them. As this article directly relates to issues related to new technologies and energy security in new form, the main purpose of this study is to examine the impact of energy commodity prices, namely crude oil, natural gas and coal prices on selected metal prices such as aluminium, chromium, cobalt, copper, lead, nickel, silver, tin, or zinc, both before and over the Paris Agreement period. We are looking for new insights in terms of relationships between traditional fossil fuels and metals used in clean energy technologies potentially established or strengthened shortly after the Paris Agreement was adopted. Currently, the analyses of the impact of institutional conditions such as global agreements (institutional factors) on the emerging or strengthening of relationships between energy and nonenergy resources are very limited. Hence, an autoregressive distributed lag and error correction model are employed.

Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks

The worldwide economy has experienced several changes in energy and nonenergy prices. This has motivated academics, investors, and policymakers to analyze the relationships between energy and nonenergy commodity markets. In this study, a novel approach of quantile coherency is used to examine the dependence structure between energy and nonenergy commodity pairs at different frequencies and quantiles in their joint return distribution over the period 1960:M1–2019:M10. Overall, the empirical findings illustrate evidence of a low significant dependency between energy and nonenergy commodity markets across different frequencies and quantiles. In addition, our findings show that some nonenergy commodity markets have a neutral relationship with global energy commodity markets.

How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics

Carbon allowances are a new class of financial instrument which aim to assist in limiting the extent and impact of global warming and climate change. The feedback mechanism in the “Carbon-Energy-Finance” system makes the information connectedness dynamics more complex since we add equity, bond and non-energy commodity assets into the system. Using modified error variance decomposition and network diagrams, we quantify and systematically analyze how the European carbon market connects with information from a wide range of other markets. Our results indicate: (i) the nature of information spillover changes over time, with system-wide return connectedness being higher and more variable than the volatility interdependence; (ii) both the oil and carbon markets closely connect with equity and non-energy commodity markets rather than bond markets; (iii) we identify three structural breaks in carbon volatility and their implication for carbon-finance linkages; (iv) financial risk-type macroeconomic factors make greater contributions to system-wide connectedness than commodity factors. These findings have economic implications for investors, portfolio managers and policymakers. • Directional and dynamic connectedness in“Carbon-Energy-Finance”system is explored. • Network connectedness exhibits substantial time variation. • Structural breaks in Carbon return impact how it connects to the system. • System-wide spillovers are determined by financial risk-type macroeconomic factors. • EUA is a better diversifier than oil given its modest linkage with financial asset.

Volatility Spillovers Arising from the Financialization of Commodities

This paper examines whether the proliferation of new index products, such as commodity-tracking exchange-traded funds (ETFs) amplified the volatility transmission channel introduced by financialization. This paper focuses on the volatility spillover effects among crude oil, metals, agriculture, and non-energy commodity markets. The results show financialization has an impact on the volatility of commodity prices, predominantly for non-energy commodities. However, the impact on volatility is not symmetric across all commodities. The analysis of index investment and investors’ positions in futures markets shows that when a relationship exists it is generally negatively correlated with the realized volatility of non-energy commodities. Using realized volatility in Tang and Xiong’s (2012) difference-in-difference model provides estimates that are inconsistent with the original findings that non-energy commodities traded as a part of indices have experienced higher volatility. The results are similar to the index investment and futures market analysis where increased participation by investors through new investment products has put download pressure on realized volatility.

Globalized energy-water nexus through international trade: The dominant role of non-energy commodities for worldwide energy-related water use

The increasing energy demand in future will inevitably escalate pressures on water resources, as energy production needs huge amounts of water inputs. Globalization has resulted in the geographic separation between the source of water inputs for energy production and the sink of its final consumption, making it crucial to factor global supply chain effect into water-energy nexus management. Therefore, this paper investigates water use for energy from source of exploitation to sink of final consumption along global supply chains based on embodiment accounting method. In total, the energy-related water use embodied in international trade is in magnitude about 80% of global total energy-related water use in 2011. It should be noted that non-energy commodities contribute more than four fifths of energy-related water use embodied in international trade and global final consumption. China serves the largest exporter of energy-related water use while EU28 is the biggest receiver. From a perspective of global supply chains, two thirds of USA direct energy-related water use sinks into final consumption from rest of the world, and over a quarter of that embodied in Mainland China's final consumption is from USA, showing the tight relation between them on global supply chains. Findings highlight the urgent need to consider international trade (i.e., energy and non-energy commodity trade) and global supply chain effects for water-energy nexus policy-making to ensure the sustainable water supply for energy development.