Return and volatility spillovers among global assets: Comparing health crisis with geopolitical crisis

This study investigates the dynamic mechanism across equity, cryptocurrency, and commodity markets before and during health and geopolitical crisis (Covid-19 and the Ukrainian war). We apply the (TVP-VAR) based extended joint connectedness methodology, to understand return and volatility connectedness of financial markets for 2010–2023 period. The empirical results indicate that spillovers were particularly high during the Covid-19 and Russia-Ukraine war. First, health and geopolitical risks considerably impact the return and volatility system. Second, the value of total joint connectedness during the COVID-19 period was greater than during Russia-Ukraine war crisis. Also, evidence suggests that Commodity markets, received the highest shocks from other markets after Russia-Ukraine war and wheat was the main commodity receiving chocks from both health and geopolitical crisis. Our findings indicate that spillover channels differ depending on the type of crisis. Specifically, low-frequency components are the main transmission channels during the health crisis, whereas high-frequency components are the main transmission channels during the geopolitical crisis. Finally, results indicate that, cryptocurrency markets played some minor role in transmitting risks between markets. Our results are important in understanding how assets affect return and volatility spillover during geopolitical and health crises and are of particular importance to policymakers, market regulators, investors, and portfolio managers.

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.

Analyzing the Stock Volatility Spillovers in Chinese Financial and Economic Sectors

By regarding the Chinese financial and economic sectors as a system, this article studies the stock volatility spillover in the system and explores its effects on the overall performance of the macroeconomy in China. The recent outbreak of COVID-19, U.S.-China trade friction, and three historical financial turbulences are involved to distinguish the changes in the spillover in these distinct crises, which has seldom been unveiled in the literature. By considering that the stock volatility spillover may vary over distinct timescales, the spillovers are disclosed through innovatively constructing the multi-scale spillover networks, followed by connectedness computation, based on variational mode decomposition (VMD) and generalized vector autoregression (GVAR) process. Our empirical analysis first demonstrates the different levels of increases in the total sectoral volatility spillover and changes in the roles of the sectors in the system under the aforementioned crises. Besides, the increases in the sectoral spillover in the long-term are verified to negatively impact the macroeconomy and can thereby act as warning signals.

Asymmetric volatility spillover among global oil, gold, and Chinese sectors in the presence of major emergencies

The volatility of international crude oil and gold markets has affected stock markets through several economic channels, and the impact tends to be more evident with the appearance of emergencies. However, the volatility linkages between commodities and Chinese sector stocks in the presence of emergencies are understudied. To examine the asymmetric relationship and time-varying connectedness between commodities and Chinese sector stocks, this paper first employs GJR-GARCH to capture the realized volatility of international oil, gold, and Chinese sector stocks. Secondly, we decompose the realized volatility of international oil and gold into bad and good volatility and then employ the TVP-VAR-DY approach to obtain the connectedness index. The final result shows asymmetric volatility spillover among oil, gold, and Chinese sector stocks. During the COVID-19 outbreak, the gold good volatility transmission is intenser than bad volatility. Thirdly, the analysis is also carried out under different subperiods. They include three international events: the global financial crisis and the European debt crisis, the oil crisis, and COVID-19. The result reveals heterogeneity exists in the impact of international oil and gold on the Chinese sector stocks under different emergencies. These findings are of great significance for policymakers to improve the sector management under the impact of different emergencies and for investors to design diversified portfolios according to the commodity-sector risk spillover effects. © 2023 Elsevier Ltd

Hidden causality between oil prices and exchange rates

This work investigates the interactions between oil prices and exchange rates of 6 typical oil importers (China, Japan, and India) and exporters (Canada, Russia, and Saudi Arabia) from 2006 to 2022. We employ a novel method to capture their causal interactions, namely pattern causality, and compare the results to that based on the volatility spillover method. The empirical analysis supports most existing findings that oil prices are bidirectional correlated with exchange rates. However, unlike previous studies that only investigate positive and negative causalities, we highlight dark causality as a more complex interaction. Moreover, dark causality suggests that successive increases (decreases) in oil prices tend to drive the exchange rates of oil exporters to act in an oscillatory manner rather than in a purely positive or opposite trend, and vice versa. Furthermore, we also reveal that dark causality shows dominance during crises, e.g., the global financial crisis, the European debt crisis, the epidemic of COVID-19, and the Russia-Ukraine conflict. Revealing three types of causalities between oil prices and exchange rates helps policymakers develop more diversified macroeconomic policies. Moreover, the newly identified dark causality can be a useful indicator for investors to risk management. © 2023

Dynamic spillover between traditional energy markets and emerging green markets: Implications for sustainable development

This study employs the time-varying vector parameter autoregression model and Diebold-Yilmaz (2012, 2014) spillover approach to explore the static, net, dynamic and directional spillover effects between China's traditional energy and emerging green markets and the impact of the COVID-19 outbreak on spillover effects. Spillover networks are constructed to observe structural changes in the directional spillover of each target financial market before and after the pandemic's outbreak. Changes in hedging indicators of portfolios composed of two types of markets before and after the outbreak of COVID-19 are compared to provide directional guidance for investors to choose portfolios in the post-pandemic era. We found that the outbreak of the pandemic had a considerable impact on the volatility of various spillover effects of the studied markets. The total spillover level of the system increased rapidly by 18% in the early stages of the pandemic. Green bond was the largest net recipient of volatility spillovers in the whole system, followed by crude oil, while new energy was the largest net contributor of volatility spillovers in the whole system, followed by clean energy. After the outbreak, the hedging effectiveness of portfolios with long positions in traditional energy markets and short positions in emerging green markets improved significantly. In particular, a portfolio with long positions in the crude oil market and short positions in the green bond market is the best risk-hedging portfolio. © 2023 Elsevier Ltd

The impact of pandemic on dynamic volatility spillover network of international stock markets.

Since the beginning of the twenty-first century, several pandemics, including SARS and COVID-19, have spread faster and on a broader scale. Not only do they harm people's health, but they can also cause significant damage to the global economy within a short period of time. This study uses the infectious disease EMV tracker index to investigate the impact of pandemics on the volatility spillover effects of global stock markets. Spillover index model estimation is conducted using the time-varying parameter vector autoregressive approach, and the maximum spanning tree and threshold filtering techniques are combined to construct the dynamic network of volatility spillovers. The conclusion from the dynamic network is that when a pandemic occurs, the total volatility spillover effect increases sharply. In particular, the total volatility spillover effect historically peaked during the COVID-19 pandemic. Moreover, when pandemics occur, the density of the volatility spillover network increases, while the diameter of the network decreases. This indicates that global financial markets are increasingly interconnected, speeding up the transmission of volatility information. The empirical results further reveal that volatility spillovers among international markets have a significant positive correlation with the severity of a pandemic. The study's findings are expected to help investors and policymakers understand volatility spillovers during pandemics.

Complex network analysis of volatility spillovers between global financial indicators and G20 stock markets.

This paper analyses the dynamic transmission mechanism of volatility spillovers between key global financial indicators and G20 stock markets. To examine volatility spillover relations, we combine a bivariate GARCH-BEKK model with complex network theory. Specifically, we construct a volatility network of international financial markets utilising the spatial connectedness of spillovers (consisting of nodes and edges). The findings show that spillover relations between global variables and G20 markets vary significantly across five identified sub-periods. Notably, networks are much denser in crisis periods compared to non-crisis periods. In comparing two crisis periods, Global Financial Crisis (2008) and COVID-19 Crisis (2020) periods, the network statistics suggest that volatility spillovers in the latter period are more transitive and intense than the former. This suggests that financial volatility spreads more rapidly and directly through key financial indicators to the G20 stock markets. For example, oil and bonds are the largest volatility senders, while the markets of Saudi Arabia, Russia, South Africa, and Brazil are the main volatility receivers. In the former crisis, the source of financial volatility concentrates primarily in the USA, Australia, Canada, and Saudi Arabia, which are the largest volatility senders and receivers. China emerges as generally the least sensitive market to external volatility.

Exploring the Time-varying Connectedness and Contagion Effects among Exchange Rates of BRICS, Energy Commodities, and Volatilities

This paper investigates the total and net directional connectedness of the energy market and currency market amid volatilities (local and international) of BRICS for the period May 7, 2012 to March 31, 2022. The Time-varying parameter Vector Autoregression (TVP-VAR) connectedness approach is specifically employed. We reveal that the average value of the total connectedness index (TCI) is 46.91%, for the specific network of energy commodities, currency rates, and volatilities. Also, from the averaged dynamic connectedness, the global energy commodity index demonstrated the most transmitter of shocks. Conversely, BRICS currency markets (except for Brazilian Rubble) and most implied energy volatilities and realised exchange rate volatilities were net receivers of shocks. Moreover, the total connectivity indices were seen to vary significantly during the study sample period with strong susceptibility to crisis periods, especially, the COVID-19 pandemic. We advocate that most volatilities were consistent net transmitters across time as indicated by the net directional connectedness. The findings imply that in a network of energy commodities, exchange rate, and volatilities, risk minimisation is elated to boost investors' confidence across time.

Directional predictability and volatility spillover effect from stock market indexes to Bitcoin: evidence from developed and emerging markets

PurposeThis paper aims to quantify the volatility spillover impact and the directional predictability from stock market indexes to Bitcoin.Design/methodology/approachDaily data of 15 developed and 15 emerging stock markets are used for the period March 2017–December 2021.;The author uses vector autoregressive (VAR) model, Granger causality test and impulse response function (IRF) to estimate the results of the study.FindingsEmpirical results show a significant unidirectional volatility spillover impact from emerging markets to Bitcoin and only six stock markets are powerful predictors of Bitcoin return in the short term. Additionally, there is no a difference between developed and developing markets regarding the directional predictability however there is difference in the reaction of Bitcoin return to shocks in the emerging markets compared to developed ones.Originality/valueThe paper proposes different econometric techniques from prior research and presents a comparative analysis between developed and emerging markets.

Volatility Spillovers Among the Three Places Across the Taiwan Strait: Evidence from a BEKK‐CARR Approach

This study introduces a new BEKK‐CARR model to explore the volatility spillover effects among mainland China, Hong Kong, and Taiwan stock markets during the COVID‐19 pandemic. We also extend the approach of Diebold and Yilmaz (2009, 2012) to infer a brand‐new volatility spillover index to discuss the bi‐directional volatility transmission. Our results show that the trading information flow among these three markets has changed significantly as a result of the COVID‐19 pandemic. The strength of volatility spillover is increasing during this momentous period. The Hong Kong stock market plays a pivotal role in volatility transmission. The values for half‐lives by exogenous shocks keep relatively low during the pandemic period. A reasonable explanation is that the trading information transmissions among stock markets are quicker than in the non‐pandemic period.

The US-China trade war and the volatility linkages between energy and agricultural commodities

Any disruptive changes in the competitive environment, such as the U.S.-China trade war, may influence the price volatility of crude oil and agricultural commodities. This study examines the volatility linkage between crude oil and agricultural commodity markets in the context of the U.S.-China trade war and compares the impact of the trade war with that of other exogenous shocks. The results show that the volatility of soybeans exhibits the highest level of responsiveness to the U.S.-China trade war - which is not surprising given that the U.S. agribusiness trade to China is dominated by soybeans - followed by coffee and cotton. The sizes and dynamics of the impacts of shocks are largely commodity-specific. Notably, the trade war impacts most agricultural commodities more extensively than other exogenous shocks, including the global financial crisis and the COVID-19 pandemic and associated recession. These findings matter not only for the decision-making of investors and portfolio managers but also for commodity-exporting and importing countries because changes in the volatility dynamics of crude oil and agricultural commodities often impact export revenues and import expenditures and consequently feed through exports to the global supply chain under exogenous shocks such as the U.S.-China trade war. © 2023 The Authors

What Leads to the Changes of Volatility Spillover Effect Between Chinese and American Soybean Futures Markets?

This paper examines the volatility spillover between the soybean futures contracts traded in the US Chicago Board of Trade (CBOT) and China Dalian Commodity Exchange (DCE) through a normalized Copula–GARCH(1,1) - t model with structural changes. The structural change points are identified through a combination of Bayesian diagnosis with Z-test. The study finds that the volatility spillover exists between the DCE and CBOT soybean futures and weakens through time. We further identify seven structural change points in the volatility spillover relationship, suggesting it is going through significant structural changes. The changes are related to major social-political events including the trade conflict between China and the US, the COVID-19 pandemic and the Russia-Ukraine war. © 2023 Taylor & Francis Group, LLC.

Volatility spillover and connectedness among REITs, NFTs, cryptocurrencies and other assets: Portfolio implications

We investigate the return and volatility spillovers among NFTs, REITs, and other major financial assets from January 2019 to November 2022, using connectedness approaches. The findings indicate that total return and volatility connectedness increased during the COVID-19 and the Russia–Ukraine war. REITs partially maintained their historical independence from shocks from other assets, while NFTs emerged as the new portfolio diversifiers. Findings suggest that investors can use REITs or a combination of NFTs, OIL, GOLD, and REITs with other assets to hedge against volatile assets during periods of financial turmoil. These findings have significant implications for heterogeneous market participants aiming to identify optimal portfolio diversifiers. © 2023 Investment Analysts Society of South Africa.

Volatility spillover across Chinese carbon markets: Evidence from quantile connectedness method

The paper investigates the volatility spillover across China's carbon emission trading (CET) markets using the connectedness method based on the quantile VAR framework. The non-linear result shows strong volatility spillover effects in upper quantiles, resulting from major economic and political events. This is in accordance with the risk contagion hypothesis that volatility of carbon price returns is affected by the shocks of economic fundamentals and spills over to other pilots. Guangdong and Shanghai are the most significant contributors to volatility transmission because of their high liquidity and active markets. Hubei CET pilot has shifted from transmitter to receiver since the COVID-19 pandemic. Regarding the pairwise directional connectedness, geographical location and similar market attribute also matter in volatility transmission. This provides implications for policymakers and investors to attach importance to risk management given the quantile-based method rather than the average shocks. © 2023 Elsevier B.V.

Impacts of COVID-19 on dynamic return and volatility spillovers between rare earth metals and renewable energy stock markets

We examine the time-frequency co-movements and return and volatility spillovers between the rare earths and six major renewable energy stocks. We employ the wavelet analysis and the spillover index methodology from January 1, 2018 to May 15, 2020. We report that the COVID-19-triggered significant increase in co-movements and spillovers in returns and volatility between the rare earths and renewable energy returns and volatility. The rare earths act as net recipient of both return and volatility spillovers, while the clean energy stocks are net transmitters of return and volatility spillovers before and during the COVID-19 crisis. The solar and wind stocks are net transmitters/receivers of spillovers before/during the pandemic. The remaining markets shift from net spillover receivers to transmitters or vice versa;evidencing the effects of the pandemic. Our results show that cross-market hedge strategies may have their efficiency impaired during the periods of crises implying a necessity of portfolio rebalancing. © 2022 The Authors

Sectoral volatility spillovers and their determinants in Vietnam

Using the vector autoregression (VAR) connectedness approach, this paper investigates dynamic volatility spillovers across 14 sectors in Vietnam's stock market over the period 2012–2021. The study also explores the differences in sectoral spillovers before and after the outbreak of Covid-19 pandemic. Additionally, the paper also investigates the effects of the current pandemic and macroeconomic fundamentals on intersectoral connectedness in Vietnam. Our findings show that volatility transmission across sectors fluctuates significantly over the research period and spikes during the Covid-19 pandemic. The total spillover index is approximately 64.23 per cent, indicating that volatility spillovers across the Vietnamese sectors are substantial. The risks from the stock market appear to spread quickly and easily across sectors in Vietnam. Among these 14 sectors, food, fisheries, and oil and gas act as net senders of risks while real estate and pharmacy are the greatest receivers of risk. The findings also confirm that the commerce, transportation, manufacturing, and service sectors are more sensitive to the Covid-19 pandemic crisis than other sectors in Vietnam. Furthermore, the empirical results show that an increase in daily Covid-19 infections increases volatility spillover across sectors. Policy implications have emerged based on these findings from this paper for the Vietnamese government and other emerging countries.

Network evolution underneath the volatility spillover in traditional and clean energy markets

When facing volatility spillovers in energy markets, all players require risk mitigation strategies to insulate themselves from the same. To prevent energy markets from being strongly crashed by volatility spillovers, which even trigger financial crises, in this paper, we use network analysis as an aid to identify spillovers among the main nine energy markets. Specifically, we first measure the volatility spillovers among the main energy markets through a BEKK model. Based on this, influential markets are identified by using network analysis. The coal, wind and water energy markets should be paid close attention as they occupy vital roles in the volatility spillover network. Even though clean energy markets contribute more in terms of market stability, traditional energy markets are still important to ensure energy supply when experiencing extreme crashes caused by COVID-19. In this paper, we make the contributions to analysing volatility spillovers in multiple energy markets and identifying crucial energy markets in volatility spillover networks, then provide more market information that helps the government and policymakers effectively manage systemic risks caused by volatility spillovers. The effective risk management of crucial energy markets enhances economic recovery and stability, especially in the post-COVID-19 era.

Volatility Integration of Gold and Copper with Foreign Exchange Rates

Copper and Gold today are some of the key metals in the metals and mining space especially due to the external events happening such as Covid-19 pandemic and Russia-Ukraine war. Also, the rupee-dollar exchange rate is highly volatile currently. The study's goal is to determine how copper and crude oil's shock volatility and price volatility affect the exchange rates between the rupee and the dollar. The study tries to find the correlation and mutual association between the metals (copper prices and gold prices) and foreign exchange rate. In order to establish such a relationship, bi-variate GARCH models (VEC GARCH and BEKK GARCH) are applied to sample data of the copper price, gold price, and foreign exchange rate (rupee-dollar) taken from the period 2005 to 2020 to determine a mutual correlation and volatility spillover effect in the metals and forex markets. © 2022 IEEE.

Volatility connectedness of GCC stock markets: how global oil price volatility drives volatility spillover in GCC stock markets?

The study investigated the volatility connectedness of GCC stock market return and S&P global oil index returns using Diebold and Yilmaz (2012) method. The current study has also analyzed the possible impact of oil price volatility on net volatility spillover in GCC stock market returns pre- and post-COVID-19 period. The current study results suggest that the GCC stock markets have volatility connectedness with S&P Global Oil Index returns' volatility and across GCC stock markets. The GCC stock markets have greater volatility in their stock markets than volatility spillover from other GCC countries. Further investigation also suggests that global oil price volatility has a divergent causal impact on net spillover in GCC stock markets. Such results would enhance the understanding of GCC stock market connection, spillover, and economic channels through which GCC markets are connected.