Dynamic Spillover Effects Research Articles

Time-Varying Spillover Effects Between Clean and Traditional Energy Under Multiple Uncertainty Risk: Evidence from the U.S. Market

The global energy landscape is undergoing an unprecedented transformation with the rapid development of clean energy and the continued significance of traditional energy creating a complex dynamic relationship. This study employs the TVP-QVAR-DY model to systematically examine the dynamic spillover effects between clean and traditional energy markets in the United States, focusing on the impacts of economic policy uncertainty (EPU) and geopolitical risk (GPR). The findings reveal (1) significant time-varying spillover effects between the two markets, with total spillover effects ranging from 30% to 50%, intensifying during extreme events; (2) increases in EPU and GPR exacerbate uncertainty in energy markets, particularly in the traditional energy sector, with spillover effects from crude oil to natural gas reaching 23.60% and vice versa at 24.30%; and (3) in the short term, the clean energy market is influenced by traditional energy, with spillover effects from oil to clean energy at 5.10%, while in the medium to long term it gradually becomes independent and inversely affects the traditional energy market, contributing 2.94% to oil spillovers. The results indicate that as the global energy transition deepens, the clean energy market is shifting from a risk receiver to a risk contributor. Based on these findings, the study proposes policy recommendations including accelerating energy structure transition, managing macroeconomic uncertainty risks, coordinating domestic and international energy markets, and leveraging market mechanisms.

Inclusive finance and sustainability: The dynamic spillover effects of uncertainties on access to credit

A firm's access to domestic credit is crucial in inclusive finance for businesses, particularly small and medium-sized enterprises, to invest and grow. Sustainable and inclusive economic growth requires a healthy private sector with access to financial resources. This paper explores how uncertainty from major economies (measured by Uncertainty Spillover indices) can limit domestic credit availability in the private sector. Analysing a panel dataset encompassing 100 developed and developing economies from 1996 to 2019, the research reveals that uncertainties stemming from China and the United States significantly reduce the availability of domestic financial resources. Uncertainties surrounding other G7 economies (Canada, France, Germany, Italy, Japan, and the United Kingdom) also exhibit a negative association; however, their effects are statistically insignificant. The robustness of these findings is confirmed across various empirical models and income classifications. Possible implications for inclusive finance and sustainable economic growth are also discussed.

Dynamic spillover effects and interconnectedness of DeFi assets, commodities, and Islamic stock markets during crises

Decentralized Finance (DeFi) assets, commodities, and Islamic stock market cointegration are affected by technological innovations, market dynamics, investor behavior, and crises. This study investigates the dynamics of returns and volatility for three DeFi assets, six commodities, and three Islamic stock markets from December 2019, to March, 2023, and identifies higher spillover effects during crises. Links among the Cross-DeFi, commodity, and Islamic markets significantly influence returns and volatility during crises. Notably, the commodities index emerged as a pivotal and substantial transmitter of risk during the Russian-Ukraine war crisis, with Emerging Markets (EM) being a key recipient. However, during the COVID-19 pandemic, livestock indices assume the role of prominent risk-return spillover receivers. The findings indicate robust returns and volatility interconnected between DeFi assets and Islamic markets with a moderate level of connectivity among commodity groups. WDI, ACWI, and EM explained 75 % of the variance observed during crisis episodes. This study formulates strategic portfolio management within and between connectedness among return volatilities by highlighting the stability of DeFi assets, the diversification potential in commodities, and a balanced option in Islamic markets. Our study provides a deep and insightful understanding of the stakeholders across markets during crises.

Spillover dynamics among commodities along the Chinese oil industrial chain: From the perspective of multidimensional networks

This paper investigates the dynamic spillover effects of major commodity prices within the Chinese oil industrial chain. By integrating the Granger causality test with the BEKK-GARCH model, a multidimensional spillover network is constructed to comprehensively analyze the price spillover relationships between commodities from 2013 to 2019. The study finds that crude oil price volatility is the primary driver of spillovers to other commodities within the industrial chain, with midstream commodities such as ethylene and benzene playing a critical intermediary role in the spillover process. Additionally, the spillover between commodities is generally bidirectional, with non-closed chain spillover patterns being more common. Based on these findings, the paper offers policy recommendations to mitigate the risks of price fluctuations, promoting the stable development of the oil market and the sustained growth of the national economy.

Contagion effect between fuel fossil energies and agricultural commodity markets and portfolio management implications

This study investigates the dynamic spillover effects between fossil fuels (Brent oil and natural gas) and major agricultural markets (maize, soybeans, and wheat) using a time-varying parameter vector autoregression (TVP-VAR) model. Additionally, we quantify the cumulative return of the investment portfolio, optimal weights, time-varying risk coverage, and hedging effectiveness of bivariate commodity portfolios using the Minimum Variance Portfolio (MVP), Minimum Correlation Portfolio (MCP), Minimum Connectedness Portfolio (MCoP) under bearish, tranquil, and bullish market conditions. The results show that maize and natural gas are the main net receivers of spillovers, whereas wheat and Brent oil are the main net transmitters of shocks to the network, respectively. Our findings of optimal weights in multivariate portfolio suggest more weights for agri-commodities against fossil fuels in all three modes of market. In addition, the optimal weights of bivariate portfolio analysis show that the most optimal portfolio which has the highest HE value is related to natural gas pairs with agri-commodities. Moreover, depending on the status of the market; in an average and bearish modes, the highest optimal weight is related to maize/natural gas. However, in the bullish market, the highest optimal weights are related to natural gas/Brent oil pair. Furthermore, the results of optimal bivariate hedge ratios show that natural gas/wheat (wheat/maize and vice versa) portfolio is the cheapest (the most expensive) investment strategy in all modes of market and based on MVP and MCoP approaches.

What drives the high-risk spillover of benchmark oil prices into China's LNG market?

The Russo-Ukrainian conflict and its reverberations on energy markets have heightened concerns regarding energy security. Against the backdrop of fluctuations in international oil prices, oil-gas linkage pricing severely jeopardizes the security of the Chinese gas market. Clarifying the mechanism of high-risk spillover of international oil prices to Chinese LNG is essential for the safe operation of gas. We examine the dynamic spillover effects of Brent, WTI, Dubai crude oil, and Chinese LNG prices using the dynamic connectedness based on TVP-VAR. We innovatively establish the BART-QCA framework to screen the conditions and identify pathways that exacerbate the high-risk spillover of international oil prices to Chinese LNG. The study finds that: (1) Chinese LNG prices are net recipients from the three primary crude oil prices. (2) four pathways exacerbate the high-risk spillover, confirming the situational characteristics of high-risk spillover. (3) The increase in global economic policy uncertainty and China's high external dependence on gas are essential conditions for the high-risk spillover. (4) three pathways mitigate the high-risk spillover. A clear global economic policy situation, reasonable control of public opinion, and the weakening of the US dollar help alleviate high-risk spillover. Accordingly, new policies should achieve scenario-based governance through cross-market and multi-sectoral synergies.

Green finance and renewable energy growth in developing nations: A GMM analysis

This research aims to examine the interrelationship between green finance and its influence on the renewable energy industry in a sample of 30 developing nations from 1990 to 2018. The main aim of this study is to investigate the interconnected effects between green bonds, investments in renewable energy, and carbon markets, with a specific emphasis on the influence of the banking system in shaping these interrelationships. To accomplish this objective, the Generalized Method of Moments (GMM) is utilized to examine the data and comprehend the intricate interrelationships among the variables. The emergence of green finance offers a favourable prospect for tackling environmental issues while concurrently fostering sustainable economic development. Nevertheless, the degree to which it impacts the adoption of renewable energy and carbon markets has yet to be thoroughly investigated, especially in developing nations. This study seeks to provide insights into the factors that influence the development of green finance and its implications for investments in renewable energy by examining a diverse group of 30 emerging countries. The findings of this research provide compelling revelations regarding the interdependence between green finance and its influence on the renewable energy industry. The results underscore the notable contribution of the banking sector in enabling the transfer of capital into sustainable energy initiatives via the utilization of green bonds. Furthermore, we have discovered dynamic spillover effects between green bonds, renewable energy investments, and carbon markets. These financial mechanisms have the potential to influence each other within the framework of sustainable development. A comprehensive comprehension of the complex interconnections among green finance, renewable energy, and carbon markets is imperative for policymakers, investors, and financial institutions seeking to promote sustainable practices and efficiently allocate resources. This research adds to the expanding corpus of literature on green finance and offers significant implications for advancing a more environmentally friendly and sustainable future in developing nations.

Portfolio balance effect of the U.S. QE between commodities and financial assets in commodity-exporting countries

This study analyses the portfolio balance channel of the U.S. quantitative easing (QE) by assessing the dynamic spillover effect between commodities and financial assets in commodity-exporting countries during QE. This study integrates the generalized spillover index initially proposed by Diebold and Yilmaz (2012) for the fractional integration VAR model. Then, we estimate the multivariate framework of the Westerlund and Narayan (2015) (WN)-based predictive model to quantify the effect of the portfolio balance channel on the net pairwise spillover index from the U.S. to other countries. Our results show: first, for bond yields, that Asian and Pacific bond yields are impacted by both commodity price indices returns and the U.S. bond yields across the sample periods. However, mixed evidence is found for both Latin America and Others; second, for equity, dynamic net return spillovers contribute mixed evidence across regional groups during QE. The diverse results are partly explained by the average percentage of commodity exports to total exports of the country and the degree of close interrelationship between countries. Additionally, dynamic return spillover analyses show that most foreign exchange returns are negative net spillovers during QE, supporting the behavior of “commodity currencies.” Last, the WN-based predictability models show pronounced differences in predictability across the selected commodity-exporting countries.

Intra- and inter-sector spillover effects within a supply chain: Evidence from Taiwan electric motorcycle industry

This study adopts a TVP-VAR based connectedness approach to investigate dynamic spillover effects of stock return in the supply chain of Taiwan's electric motorcycle. The decomposition of spillovers into intra- and inter-sector parts finds that the intra-sector connectedness is larger than the inter-sector one. Our results further suggest the midstream sector as the main transmitter of shocks as taking either intra-sector or inter-sector effects into consideration. We also find that inter-sector spillovers diminish with the echelon distance in the supply chain. The results provide insights for investors in assessing how stock returns shocks transmitted in the supply chain.

Can carbon emission trading markets reduce the risks in traditional energy markets?

As the largest energy consumer in the world, China maintains a tightly interconnected energy market in the international arena. Therefore, it is necessary to explore the interdependence and spillover effects between the carbon emissions trading markets, traditional energy markets in China, and International markets. We explore changes in risk in the Chinese energy market with the introduction of the Chinese carbon market by employing the Vine Copula function to construct a vine structure and analyse the complex interdependence among markets. Moreover, we utilise the Time-Varying Parameter Vector Auto Regression and Diebold-Yilmaz Spillover Index (TVP-VAR-DY) method to examine the dynamic spillover effects of risk across various markets. Empirical analyses reveal a strong interdependence between the carbon emissions trading market and the traditional energy market. The Brent crude oil market occupies a central position within the system and significantly influences other markets. The carbon emissions trading market on the periphery has little impact on the system. Additionally, significant volatility spillover effects—observed between the carbon emissions trading market and traditional energy market systems—are closely correlated with economic conditions and extreme events, demonstrating time-varying characteristics. Furthermore, the Chinese carbon emissions trading market effectively reduces risk spillover in traditional Chinese energy markets from international markets during periods of risk contagion, particularly during times of high volatility, which can offer policymakers a novel path for risk management and provide investors with new avenues for investment hedging strategies.

Spillover effects of economic policy uncertainty among the US and BRIC countries: based on time and frequency domain perspectives

ABSTRACT This study examines the static and dynamic spillover effects of economic policy uncertainty (EPU) among US and BRIC countries. We investigate their connectedness both in the time and frequency domains using the spillover index approach and frequency domain decomposition methods. Our results indicate that the countries have significant time-varying characteristic spillover effects, and most of EPU connectedness is generated in the short-term. Furthermore, US domestic emergencies will bring about a sharp increase in spillover indices; in most cases, the US is the major transmitter and receiver of uncertainty spillover while Russia delivers and receives the lowest spillover. These results have implications for policymakers and investors with different time horizons.

Research on the spatial effect of digital economy development on urban carbon reduction

Cities are one of the main sources of regional carbon emissions, and reducing urban carbon emission is the key to reducing emissions. The digital economy has transformed the economic operation mode, and it is a significant approach to support the “dual carbon goals” (carbon peaking and carbon neutrality). This article considers the externalities of the digital economy and carbon emissions. And we use spatial econometric models to analyze the effectiveness of digital economy in empowering carbon emissions reduction. Besides, we explore the static and dynamic spillover effects, and use spatial Durbin panel quantile model to analyze the digital economy’s heterogeneity on carbon emissions. Research has shown that the digital economy has a remarkable carbon reduction effect, and the conclusion remains valid after considering robustness tests such as replacing the weight matrices, calculation methods, and proxy variables. The analysis of static and dynamic spillover effects indicates that the degree of the digital economy’s impact on carbon emissions are significantly different. Heterogeneity analysis shows that as the digital economy develops from a low level to a high level, its impact on carbon emissions also shifts from positive promotion to negative suppression. This paper proposes a policy reference to help the development of digital economy and promote carbon neutrality in the face of severe environmental challenges.

Can NFTs hedge the risk of traditional assets after the COVID-19 pandemic?

Our study analyzes the dynamic spillover effects between the NFT market, Bitcoin market, oil market, gold futures market, S&P 500 stock index, bond market, and US dollar index over three time periods: the full sample period (2017/6/23–2022/9/2), before the COVID-19 outbreak (2017/6/23–2020/1/12), and after the COVID-19 outbreak (2020/1/13–2022/9/2) by employing the DCC-GARCH-based connectedness model. Furthermore, we apply the DCC-GARCH-t-Copula model, Risk Parity Portfolio (RPP) model, and Minimum Connectedness Portfolio (MCoP) model to evaluate the bilateral dynamic hedge ratios, portfolio weights, and the multivariate portfolio performance of these financial assets, respectively. Our findings suggest that NFTs are a source of volatility spillovers during both periods and that the COVID-19 outbreak accelerates the speed and intensity of volatility spillovers from NFTs to traditional financial markets. Moreover, most of the volatility spillovers from NFTs are caused by own shocks, which implies that NFTs are not susceptible to financial risk contagion. The results of bilateral portfolio analysis show that NFTs can effectively hedge other traditional financial assets when used as long positions. The results of multivariate portfolio analysis demonstrate that NFTs can also reduce investment risk despite their smaller weighting. In the two months after the COVID-19 outbreak, MCoP slightly outperforms RPP, although RPP outperforms MCoP in general.

Dynamic spillover effects between EU economic sanctions against Russia, oil prices, and share prices of energy companies in third countries: evidence from China and the USA.

This study establishes a comprehensive suite of sanction indices and employs the time-varying vector autoregressive dynamic spillover index (TVP-VAR-DY) model, to examine the spillover effects of EU economic sanctions against Russia on oil prices and share prices of third-country energy companies, as well as takes China and the USA as examples for analysis. The findings indicate that sanctions targeting the energy sector are the primary drivers of volatility in oil prices and energy company stock prices. The impact on Chinese energy firms' stock prices is more pronounced, while the effects on their American counterparts are more enduring. The indirect impact of EU sanctions on Russia on China is greater than that of the USA. Both direct and indirect sanctions exhibit comparable spillover effects on oil and stock prices. Direct sanctions have better explanatory power for stock price fluctuations, while indirect sanctions have better explanatory power for oil price fluctuations.

Spillover effects between fossil energy and green markets: Evidence from informational inefficiency

This paper builds an indicator of the market inefficiency degree by quantifying the extent of the market deviation from an efficient status. From a novel perspective of informational inefficiency, we further model the dynamic spillover effects between fossil energy and green markets by using a time-varying parameter vector autoregressive (TVP-VAR) model. Our findings indicate that the market inefficiency degree and its spillovers exhibit evident time-varying dynamics and are sensitive to extreme events. The international crude oil benchmarks serve as the most significant information transmitter and receiver in the spillover network of market inefficiency. Within green-related markets, carbon market demonstrates the strongest correlation with the fossil energy markets. Additional analyses involving consideration of economic policy uncertainty reassure the robustness of our findings.

Dynamic spillover effects of renewable energy efficiency in the European countries.

Renewable energy has gained significant attention due to the growing concern for environmental sustainability and the high reliance on energy imports in European countries. In this study, we use a two- stage approach to assess renewable energy efficiency (REEF) of European countries. Initially, we employ the data envelopment analysis (DEA) method to quantify the efficiency of renewable energy. Subsequently, we investigate the factors influencing REEF between 2005 and 2020. Our findings reveal a generally high level of REEF across European countries, but some countries have become worse in this regard (e.g., France, Ukraine, Russia, Belgium, Germany, Norway, and Serbia). In order to find the causes of these changes, we considered the explanatory variables of gross domestic product (GDP), energy price, renewable energy consumption, information and communications technology (ICT), and industrial value added in a spatial system generalized method of moments (spatial SYS-GMM) model. The findings provide confirmation of the spatial spillover effects of REEF within European countries. The strongest positive effect is related to energy prices. In simpler terms, as energy prices rise, the efficiency of renewable energy has increased in European countries. Additionally, ICT and renewable energy consumption have positive impacts, too. But GDP and industrial value added, have decreasing effects. Based on these findings, we put forth several policy suggestions aimed at enhancing the efficiency of renewable energy in European countries.

Dynamic correlations between Bitcoin, carbon emission, oil and gold markets: New implications for portfolio management

<abstract> <p>In this paper, we aim to uncover the dynamic spillover effects of Bitcoin environmental attention (EBEA) on major asset classes: Carbon emission, crude oil and gold futures, and analyze whether the integration of Bitcoin into portfolio allocation performance. In this study, we document the properties of futures assets and empirically investigate their dynamic correlation between Bitcoin, carbon emission, oil and gold futures. Overall, it is evident that the volatility of Bitcoin, as well as other prominent returns, exhibit an asymmetric response to good and bad news. Additionally, we evaluate the hedge potential benefits of these emerging futures assets for market participants. The evidence supports the idea that the leading cryptocurrency-Bitcoin can be a suitable hedge instrument after the COVID-19 pandemic outbreak. More importantly, our analysis of the portfolio's performance shows that carbon emission futures are diversification benefit products in most of the considered cases. Notably, incorporating carbon futures into portfolios may attract new investors to carbon markets for double goals of risk diversification. These findings also provide insightful evidence to investors, crypto traders, and portfolio managers in terms of hedging strategy, diversification and risk aversion <sup>[<xref ref-type="bibr" rid="b19">19</xref>,<xref ref-type="bibr" rid="b20">20</xref>,<xref ref-type="bibr" rid="b21">21</xref>,<xref ref-type="bibr" rid="b22">22</xref>,<xref ref-type="bibr" rid="b23">23</xref>,<xref ref-type="bibr" rid="b24">24</xref>,<xref ref-type="bibr" rid="b25">25</xref>]</sup>.</p> </abstract>

Research on dynamic spillover effect of stock market volatility in Beijing-Tianjin-Hebei region

To enhance economic cooperation in the Bohai Sea and Beijing-Tianjin-Hebei region, China introduced the Beijing-Tianjin-Hebei integration plan in 2014. Over the past decade, coordinated development has established a solid foundation, emphasizing economic and spatial structure optimization. The region’s development has now achieved comprehensive, qualitative, and profound progress. Recognizing economic integration as crucial, this study analyzes the 2020-2023 stock data of listed firms in the region, utilizing the DY spillover index to examine sectoral volatility spillover effects, both statically and dynamically. Results reveal bidirectional, asymmetric spillovers, with heterogeneous spillover levels. Industry, raw materials, and information technology are key spillover sectors, significantly influencing others and inducing synchronization. Property and finance sectors are primarily recipients, influenced by others. Energy and communication services exhibit strong bidirectional spillovers. Volatility spillover strength is influenced by factors such as inter-sector correlation, market risk, macroeconomic changes. Studying these factors helps grasp volatility spillover patterns and understand sectoral volatility-factor relationships.

Quantile time-frequency connectedness among G7 stock markets and clean energy markets

The rapid growth of clean energy markets as a distinct asset class has attracted significant investor attention. This study examines the interdependence between G7 stock markets and clean energy indices, specifically Renewable Energy Generation (REG), Energy Efficiency (EE), Advanced Materials (AM), and Clean Fuels (CF). Using a state-of-the-art volatility connectedness network and Maximum Overlaps Discrete Wavelet Transform (MODWT), we investigate the quantile time-frequency connectedness among the markets. Our findings reveal strong volatility linkages among all markets, with the exception of Clean Fuels, which has the least connection. We also observe higher dynamic spillover effects under extreme market conditions than normal conditions, with the US market being the most important transmitter of spillovers under bullish markets. Additionally, we highlight the importance of considering the time-varying nature of connectedness, emphasizing the heterogeneity between short-run, medium-run, and long-run transmission. Our study's implications suggest that investors should consider the dynamic nature of spillovers and connectedness when constructing portfolios containing clean energy and G7 stock market assets. The results also imply that the US market's performance has a substantial impact on other markets under bullish conditions, and that Clean Fuels may present an attractive investment opportunity for diversification purposes due to its relative independence.

Spillover effects from China and the United States to Key Regional Emerging Markets: A dynamic analysis

While a limited number of studies have employed wavelet techniques to distinguish between market interdependence and contagion within the context of market co-movement, many of them have primarily relied on conclusions derived from multivariate wavelet analysis. In contrast, this paper introduces a complementary approach based on the univariate wavelet technique, specifically the Maximal Overlap Discrete Wavelet Transform (MODWT). This approach entails assessing the correlation between key market series that have been decomposed into both the time and frequency domains. The proposed technique is applied to evaluate the co-movement and dynamic spillover effects from two prominent advanced markets, namely China and the United States, to six major emerging economies across different regions. The findings obtained through various wavelet techniques consistently support the notion that interdependence is the predominant characteristic in terms of shock spillovers and stock market co-movement between the selected advanced and key emerging markets. Furthermore, the results indicate that both the US and China cycles are synchronized with those of the key emerging economies. These insights are of significant importance for investors and asset managers, offering valuable guidance for asset diversification and portfolio allocation strategies during both tranquil and turbulent periods.