Risk Spillovers Research Articles

Risk spillover effect of resident leverage on corporate debt

Using panel data from 2008 to 2019, this study analyzes the risk spillover effect of resident leverage on the corporate sector. Thus, the results indicate that increasing resident leverage does not create a more favorable macroeconomic environment for an enterprise to deleverage. Instead, it worsens the debt risk of the enterprise through mechanisms such as weakening corporate solvency, changing the corporate debt maturity structure, and enhancing the financial trend.

Can ESG Integration Enhance the Stability of Disruptive Technology Stock Investments? Evidence from Copula-Based Approaches

This paper provides an investigation into the dependence structure among different disruptive technology sectors driving the Fourth Industrial Revolution and scrutinizes the impact of ESG integration on shaping investments in different tech stock sectors in the presence of ESG consideration, represented by the ESG stock index, versus without specific ESG consideration, represented by the general stock index. The results show that (i) C-vine outperforms R-vine and D-vine when modeling the dependence structure of tech sectors. Intelligent infrastructure is the most crucial sector, with substantial reliance on smart transportation and advanced manufacturing. (ii) ESG integration reduces dependence, especially tail dependence, between tech sectors and the stock market, which benefits the future security sector the most and future communication the least. (iii) ESG integration mitigates risk spillover between tech sectors and the stock market, particularly benefiting final frontiers and intelligent infrastructure. The decrease in downside spillover is more significant compared to upside scenarios. For downside risk, spillover from tech sectors to stock indices is more reduced than the reverse, while the opposite holds for upside risk. These sectoral findings offer insights for market participants in financial market investments, financial regulators in risk management, and listed companies in ESG disclosure.

Green intent or black smoke: Exploring investor sentiment on sustainable development

AbstractThe connections among fossil fuels, green bonds, and investors have undergone a substantial alteration due to the daunting difficulties posed by climate change risks and energy problems. This study employs quantile connection approaches to the dynamic spillover. The results indicate that extreme quantiles exhibit a higher degree of connectivity compared to the average quantile. In severe circumstances, risk spillover primarily emanates from fossil fuels, whereas investor sentiment (IS) is more vulnerable to the impact of related market hazards. The green bond (GBI) experiences a transition in its function, alternating between being a transmitter and a receiver. To summarise, comprehending the interrelation among these variables offers fresh perspectives for investment decision‐making and policy development to facilitate the shift towards sustainable energy and tackle the climate emergency.

High–low volatility spillover network between economic policy uncertainty and commodity futures markets

AbstractBased on the formation and evolution of systemic risk, we study the high‐low volatility spillovers between economic policy uncertainty (EPU) and commodity futures and identify the source of risk accumulation and risk outbreak, as well as the corresponding contagion mechanisms. Upon comparing topological characteristics on each volatility layer, our results demonstrate that high and low volatility spillover networks have different network characteristics and evolution behaviors. At the system level, high volatility spillovers are relatively stronger than spillovers in in low volatility network, while the risk propagation efficiency in the low volatility network is higher. At the market level, EPU is not only an important risk‐emitter but also a risk‐recipient most of the time. Additionally, compared with high volatility network, low volatility network characteristics have greater predictive ability for risk spillover among commodity futures, which means that it contains additional information and provides early warning signals for financial stress.

Consumer Confidence, Uncertainties, and Risk of the UK Travel and Leisure Industry

This study examines the impact of changes in consumer confidence and uncertainty related to economic policy, financial markets, and the crude oil market, on the returns and risk of the UK travel and leisure stock index. Using monthly data from November 2005 to February 2021 and applying quantile regressions and copula-based conditional value-at-risk (CoVaR) measures, the results are as follows. First, consumer confidence and uncertainties significantly impact the travel and leisure index returns across various quantiles, however, the impact is stronger at the left tail than the right tail; furthermore, the sign and magnitude of the impact differ across the various uncertainty measures. Second, there are significant upside and downside extreme risk spillovers from the extreme movements in the consumer confidence and uncertainty indices to travel and leisure index returns, with evidence of an asymmetric impact. Third, the results are influenced by the COVID-19 pandemic and global financial crisis. These findings have implications for market participants, such as portfolio managers, individual and institutional investors, and policymakers in the UK travel and leisure industry.

Do internal and external risk spillovers of the food system matter for national food security?

The COVID-19 pandemic and the Russia-Ukraine war raise concerns about food security, particularly in interconnected and vulnerable food systems. However, existing literature focuses mainly on food supply-chain linkages and less on systemic risk spillovers, namely system-wide risk contagion among food companies. We estimate countries' internal and external risk spillovers using the “Vector Auto-Regressive (VAR) for Value-at-Risk (VaR)” approach with an Elastic Net penalty and the stock returns of 528 food companies, and analyze their impacts on national food security using country-level panel data. Results reveal that both risk spillovers significantly threaten food security, especially for countries with low food self-sufficiency and high import concentration levels. Beyond non-financial channels like higher food consumer prices, fewer food imports, and lower food quality, these impacts also rely on financial channels (reduced credit flows to agriculture). Our study highlights enhancing food security for governments by monitoring and reducing risk contagion among food companies.

Measuring crisis from climate risk spillovers in European electricity markets

This paper studies how climate risks spill over to European electricity markets across time and frequency domains using the connectedness network approach. By introducing three climate risk measures—the climate policy uncertainty index, climate physical risk index, and climate concern index—the empirical results reveal the vulnerability of European electricity markets to volatile climate policies and extreme climate crisis events. Overall, the spillover effects in the climate–electricity nexus are primarily concentrated in the medium- and long-term frequency domains, indicating that the impact of climate risk shocks is persistent. Compared with the impact of climate physical risks and climate concern shocks, the spillovers from climate policy uncertainty shocks to the electricity market are higher and more persistent. These findings highlight the need to consider the heterogeneous impacts of climate risks on electricity markets at different frequency bands.

Risk dynamics in energy transition: Evaluating downside risks and interconnectedness in fossil fuel and renewable energy markets

Amidst rising concerns over climate change, the global shift from oil-powered vehicles to lithium-powered electric vehicles marks a critical pivot in the energy sector. This transition holds profound implications for the traditional dominance of oil in the energy market. This study aims to investigate the risk dynamics between the fossil fuel sector, represented by the crude oil, and the renewable energy sector, symbolized by lithium, focusing on the risk spillover and interconnectedness. The study employs a two-step approach that combines the conditional autoregressive value-at-risk (CAViaR) and time-varying parameters vector-autoregression (TVP-VAR). The study spans from January 2011 to August 2023, focusing on extreme market events like the COVID-19 pandemic and the Russia-Ukraine conflict. Findings reveal a strong tail-risk connectedness between the lithium stocks of the same country, and during extreme market events such as the COVID-19 pandemic and the Russia-Ukraine conflict, there is a strong transmission of tail risk across the lithium stocks of different countries. Moreover, a strong bidirectional tail-risk connectedness is observed between crude oil and lithium stocks. The study has important implications for portfolio managers, fund managers and investors with respect to portfolio optimization and asset allocation. Also, the findings have important implications for financial risk management with respect to energy transition from fossil fuels to renewable energy.

Time-frequency extreme risk spillovers between COVID-19 news-based panic sentiment and stock market volatility in the multi-layer network: Evidence from the RCEP countries

This study extends extant discussions on regional integration by exploring risk spillovers between news-based panic sentiment and stock market volatility among Regional Comprehensive Economic Partnership (RCEP) members during the COVID-19 pandemic. We innovatively estimate quantile-based spillover indices in both time and frequency domains and construct the multi-layer network. Both static and dynamic risk spillover patterns in the "RCEP panic-stock network" are outlined. It is found that risk spillovers are predominantly transmitted from the "panic-layer network" towards the "volatility-layer network". Besides, regression analyses are employed to investigate whether general features of COVID-19 media reporting affect the spillovers of panic sentiment at the country level. The results show that the magnitude of panic spillovers tend to be positively associated with overall media coverage and negatively with overall media sentiment, especially at the middle and lower quantiles.

Extreme co-movements between decomposed oil price shocks and sustainable investments

This paper investigates the extreme co-movements between three types of decomposed oil price shocks, e.g., supply shock, demand shock, and risk shock, and sustainable investments, using the generalized extreme value - autoregressive conditional Fréchet - tail quotient correlation coefficient (GEV-AcF-TQCC) analytical framework. The empirical results have identified that there are regular extreme co-movements between the three types of oil shocks and sustainable investments under extreme market conditions, especially, during the 2014–2016 oil crisis, the COVID-19 pandemic and the event of negative oil prices in 2020, according to the dynamic tail quotient correlation coefficient (TQCC) method. Specifically, the upside and downside trends of supply shocks, the downside trend of demand shocks, and the upside trend of risk shocks act as transmitters of the tail risks between oil prices and sustainable investments. The results also have demonstrated that the tail risk indexes for both the upside and downside trends of decomposed oil price shocks and sustainable investments have time-varying and asymmetric characteristics. Additionally, the static TQCC results have validated that among the three types of oil shocks, demand shocks exhibit the most pronounced tail risk spillover effects on sustainable investments, followed by supply and risk shocks, whose tail risk spillovers are close to each other. A series of alternative analyses ensure the robustness of the findings presented in this paper, which can offer valuable guidance and insights to policymakers and financial investors.

Exploring the asymmetric influence of economic policy uncertainty on the nonlinear relationship between exchange rate and carbon prices in China

Our objective is to investigate the impact of economic policy uncertainty (EPU) on the risk spillover effect between exchange rates and carbon prices. First, we employ the time-varying parametric vector autoregression (TVP-VAR) method to assess the dynamic nonlinear risk spillover effect between four exchange rates and China's carbon price for the period from September 2, 2013, to April 29, 2022. Our findings reveal a significant time-varying spillover effect between exchange rates and carbon prices. Among them, carbon prices and the EUR/CNY exchange rate predominantly act as risk contributors, and a pronounced correlation is observed among various exchange rates. Furthermore, the magnitude of risk spillover and interdependence intensifies significantly in response to major events. Second, we employ quantile-to-quantile regression (QQR) to examine the impact of EPU on risk spillover. Our results indicate that the influence of EPU on risk spillover exhibits is characterized by marked asymmetry and heterogeneity. At high levels of EPU, EPU has a substantial positive impact on risk spillover. However, when the risk spillover is already elevated, the effect of EPU tends to diminish. Based on these findings, we propose several policy recommendations, including prudent treatment of exchange rate adjustments, fostering stability in carbon prices, and the enactment of robust economic policies.

Tail risk transmission from the United States to emerging stock Markets: Empirical evidence from multivariate quantile analysis

This paper explores the transmission of risk from the United States equity market to the equity markets of the BRICS countries using a multivariate quantile process. The focus is on the contagion effect at the extreme quantiles, both upside and downside. In addition, a pseudo-impulse-response function (PIRF) analysis is conducted to investigate the responses of the five emerging stock markets to a shock in the US market. We conduct an empirical study against the backdrop of the COVID-19 event and the Russia-Ukraine conflict, finding that risk spillovers between the US stock market and the five emerging stock markets are significantly enhanced during the COVID-19 period. Moreover, a shock in the US market produces a stronger and more persistent negative effect at the downside quantiles compared to upside quantiles. However, we find little evidence of cross-market risk spillovers among the investigated variables during the Russia-Ukraine conflict period. We also discuss the implications of these findings for investors and policymakers in terms of portfolio holdings and policy coordination.

Do macroprudential policies reduce risk spillovers between energy markets?: Evidence from time-frequency domain and mixed-frequency methods

Preventing volatility spillovers between energy markets is essential for maintaining financial stability. Macroprudential policies play an invaluable tool in financial risk monitoring and help to reduce the incidence of systemic risk. However, the effectiveness of macroprudential policies on risk spreads in the energy system is still unclear. This article applies the TVP-VAR (time-varying parameter vector autoregression) spillover methods to capture the risk connectedness between energy markets in the time and frequency domains, and constructs an asymmetric GARCH-MIDAS-MPP model to investigate the influence of macroprudential policies on volatility overflows of the energy system. The results suggest that there are strong risk links between global energy markets and long-term risk resonances play a dominant role. Time-varying risk overflows occur throughout the energy sector, and market turbulence amplifies these risk communications. Whether on a time or frequency horizon, the oil market represents the largest emitter of fluctuation transmissions, while the fuel oil market stands out as the biggest recipient of risk diffusion. We do not observe that macroprudential policies can significantly reduce the average and long-run risk premiums of the energy system. Conversely, our results reveal that macroprudential policies intensify short- and medium-term risk spreads between global energy markets. This paper provides some insight into energy market risk contagion, which is conducive to the improvement of macroprudential policies for energy market risk management.

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.

Sectoral uncertainty spillovers in emerging markets: A quantile time–frequency connectedness approach

This study investigates the sectoral expected uncertainty connectedness in emerging markets across different frequencies and quantiles using the novel quantile time–frequency connectedness approach of Chatziantoniou et al. (2022a). The employed dataset spans from January 1st, 2003 to October 4th, 2022, encompassing 10 key sectors. The findings reveal a robust and notable interconnection among these sectors, with a substantial total connectedness index of 91.01%. We also note that the largest proportion of the sectoral total connectedness is associated with long-term spillovers. Consumer Cyclicals emerges as the primary source of net risk transmission. Conversely, the Communications & Networking and Healthcare appear to be the greatest net receivers of shocks at the median level. Furthermore, we find that the degree of interconnectedness substantially varies over time, frequency, and quantile, and by economic events. In addition, we find suggestive evidence of asymmetric sectoral uncertainty connectedness effects as the uncertainty spillovers are higher during turbulent market conditions than normal market conditions. A positive relationship between uncertainty measures and sectoral connectedness is also observed during periods of smooth and normal market conditions. Besides, we also conduct different portfolio analyses illustrating the importance of risk diversification to reduce investment uncertainty. This has important implications for international investors and policymakers in forming optimal investment portfolios reducing adverse risk spillovers.

Decomposing risk spillover effect in international stock market: A novel intertemporal network topology approach

This paper investigates the intertemporal risk effects in global stock markets using a novel network topology based on relative importance analysis. The rolling time window approach identifies dynamic and asymmetric risk spillovers. The results reveal complex and asymmetric intertemporal risk spillovers in international stock markets. Europe and America are the main risk transmitters. Countries in the forecast period, receive more risk from the international stock market. Major events that generate stock market turbulence will dramatically increase intertemporal risk spillovers. These findings have implications for risk management and the stability of the international stock market.

Quantile connectedness between China’s new energy market and other key financial markets

ABSTRACT This study utilizes data from the China Securities Index for the period from September 2017 to September 2022 and employs the quantile VAR model’s connectedness measurement method to examine the static and dynamic quantile connectedness between China’s new energy sector and other financial markets. The research findings reveal a significant correlation between China’s new energy market and other financial markets. During stable market periods, China’s new energy market exhibits strong predictive power over changes in other financial markets and acts as a net transmitter of systemic return shocks. The new energy, aviation, and agriculture sectors have a substantial impact on other financial markets. Extreme shocks significantly influence spillover effects, with total connectedness levels increasing with extreme downward and upward shocks. Furthermore, in the rolling window analysis, the total risk spillover index exhibits pronounced fluctuations during extreme market conditions, indicating that changes in investor sentiment and market expectations lead to greater market volatility and more significant information transmission effects. The new energy industry demonstrates predictable risk transmission characteristics, typically acting as a net transmitter of systemic risk in both normal and extreme market conditions.

The dynamic connectedness between renewable energy market and environmental protection industry based on time and frequency perspective

Renewable energy promotes the sustainable development of the environmental protection industry (EPI) and the economy. Meanwhile, the EPI provides various technologies and services for renewable energy, which is an important guarantee for the renewable energy market. This paper combines the DY and BK spillover indexes to discuss the cross-market risk contagion effect between EPI and renewable energy market from the perspective of time-frequency spillover. The results show that: (1) The spillover effect between the EPI and renewable energy market is cyclical from the perspective of frequency domain, and the total market spillover is dominated by high-frequency spillover. And the risk contagion has the characteristics of time-varying and vulnerability from the perspective of time domain. (2) The net spillover effect shows that the EPI plays the role of a net exporter in different frequency domains, the solar energy and the hydro market play more roles as risk receivers, and the role of the wind energy market is frequently converted. (3) The risk spillover network structure shows that EPI acts as an important node in the cross-market risk contagion path. Driven by EPI, the short-term risk transmission follows the path of “EPI-biomass energy-other four renewable energy markets”, and the medium and long-term follows the path of “EPI-wind energy-other four renewable energy markets”.

Cross-exchange crypto risk: A high-frequency dynamic network perspective

Cross-exchange crypto trading presents inherent risks, particularly for centralized exchanges. Investors observe exacerbating crypto volatility and counterparty risk and would like to quantify these elements of crypto trades. The multiple exchanges require a multivariate view on the structures of risk spillover across exchanges. Here, a Multivariate Heterogeneous AutoRegression (MHAR) model is designed and analyzed, accommodating the stylized facts of crypto markets, including 24/7 trading and the long-memory effect on return variations. The proposed MHAR approach clearly reveals the intensity of interconnectedness among exchanges during extreme events, e.g., the Bitcoin market. Additionally, one observes extremely volatile eigenvector centralities of Futures Exchange Ltd (FTX), suggesting potential implications for its bankruptcy. Furthermore, portfolios that account for the dynamics of partial correlations or eigenvector centralities offer promising results in terms of risk measures.

Bank leverage and systemic risk: Impact of bank risk‐taking and inter‐bank business

AbstractIn order to prevent and resolve systemic risk more effectively through deleveraging policy, this research takes China A‐share listed commercial banks from 2011 to 2021 as samples, calculates the systemic risk spillover through the conditional value at risk model, re‐estimates the leverage ratio with reference to the “Administration Measures for the Leverage Ratio of Commercial Banks (revised)”, and evaluates the influence of the leverage ratio on systemic risk. The results show that a high leverage ratio increases systemic risk spillover, and under this increase state‐owned commercial banks have the greatest contribution. Further research presents that a better leverage ratio enhances the systemic risk spillover by improving bank risk‐taking and encouraging inter‐bank business expansion. In addition, over different periods of economic development the influence of the leverage ratio on systemic risk exudes different characteristics. During an economic upswing, the leverage ratio's impact on systemic risk significantly drops.