Volatility Spillovers Research Articles

Risk spillovers between Chinese new energy futures and carbon-intensive assets: Asymmetric effect, time–frequency dynamics, and portfolio strategies

This study investigates the asymmetric time–frequency risk spillovers between Chinese new energy futures and carbon-intensive assets by using a time-varying parameter vector autoregressive connectedness approach. The results reveal that, in both the return and volatility spillover cases, industrial silicon futures and lithium carbonate futures generally are the net receivers of risk spillovers as regards the relationships with carbon-intensive sectoral stocks and fossil energy futures. In addition, there exists an asymmetric spillover effect, where spillovers based on bad news are higher than those based on good news. Meanwhile, return and volatility spillovers are extremely intensive in the short term as compared to the medium the long term. Finally, this study develops portfolio strategies by constructing bivariate and multivariate portfolios comprised of new energy futures and carbon-intensive assets. The bivariate portfolio analysis indicates that industrial silicon futures and lithium carbonate futures can well hedge against carbon-intensive sectoral stocks. The multivariate portfolio analysis shows that allocating the smallest share of petrochemical stocks and steel stocks can mitigate investment risks. These findings have important implications for investors and policymakers.

DYNAMIC VOLATILITY SPILLOVERS BETWEEN CURRENCIES OF ASEAN MEMBER COUNTRIES AND CHINA: EVIDENCE FROM TVP-VAR APPROACH

Driven by the importance of analyzing interregional volatility spillover effects, this study investigates dynamic volatility spillovers between the currencies of China– ASEAN Free Trade Area (FTA) member countries by applying the time-varying parameter vector autoregressive (TVP-VAR) connectedness approach to a sample spanning January 1, 2006, to October 31, 2022. The results show that (1) dynamic volatility connectedness varies over time and reaches peaks due to economic events, such as the 2008 global financial crisis (GFC) and the COVID-19 pandemic; (2) the Chinese yuan (CNY) market assumes more of a net receiving role for volatility spillovers after the 811 exchange rate reform, while the Singapore dollar (SGD) market assumes more of a net transmitting role for volatility spillovers in the whole sample period and (3) negative spillovers are dominant during the study period, except during the European debt crisis. Our findings can help China and ASEAN establish an exchange rate coordination mechanism to prevent the cross-country transmission of exchange rate risk.

Analysis of the effect of Regional Stock Market on the Jakarta Composite Index using Markov Regime Switching Regression

Purpose: In the current era of information, global stock market interconnections significantly influence investment decisions. Changes in one market rapidly affect others. The co-movement of stock markets presents challenges and opportunities for investors, whereas volatility spillovers complicate risk management and investment strategies. Research Methodology: This study examines the influence of the Nikkei 225, Straits Times Index, and Shanghai Composite Index on the Jakarta Composite Index across the pre-pandemic, pandemic, and post-pandemic phases. Results: Utilizing the hidden Markov model with regime-switching regression, this study identifies changes in market behavior due to economic shifts during the pandemic, revealing two regimes: synchronization and desynchronization. Limitations: Pre-COVID-19, the Jakarta Composite Index shows strong synchronization with the Nikkei 225 and Straits Times Index, while the Shanghai Composite Index has an insignificant impact. During the COVID-19 pandemic, frequent desynchronization occurred due to high uncertainty and volatility, with only the Straits Times Index significantly influencing the Jakarta Composite Index. Post-pandemic, synchronization between the JCI and regional markets strengthened again. This study highlights the consistent influence of the Nikkei 225 and Straits Times Index, while the Shanghai Composite Index remains insignificant. Contributions: This study contributes significantly to the understanding of regional stock market relationships and offers valuable insights for academia and practice.

Exploring the Spillover effects of tail risk fluctuations in the RMB exchange rate—The time-frequency and quantile connectivity perspective

This study constructs spillover indices from a volatility spillover network perspective using the Quantile Vector Autoregression (QVAR) model, capturing the RMB exchange rate's tail risk and time-frequency effects across varying shock sizes. Empirical results show that the QVAR-based spillover index more effectively captures the tail risk spillover effects across different quantiles. In the time domain, spillovers between RMB exchange rates are dynamic and particularly sensitive to extreme contingencies. In the frequency domain, RMB exchange rates demonstrate significant spillovers, primarily at low frequencies. During extreme upward events, dynamic observations show high-frequency spillovers surpassing low-frequency ones as dominant drivers in the tail spillovers of the RMB exchange rate. Additionally, the analysis of tail dependence indicators indicates a strong asymmetry in RMB exchange rate correlations, emphasizing market participants' heightened sensitivity to unfavorable shocks. These findings can serve as a reference for policymakers to strengthen risk management of the RMB exchange rate.

Financial market spillovers and investor attention to the Russia-Ukraine war

This study examines the impact of the Russia-Ukraine war on global commodity and financial markets by analysing the volatility and return spillovers of 26 assets across six different markets. We find significant increases in volatility spillovers after the invasion although increases in return spillovers were milder. Stock and currency markets were the leading spillover transmitters and receivers. Investor attention to the conflict played a large role in driving market spillovers, particularly in extreme quantiles. Meanwhile, uncertain market conditions seem to provide significant feedback to investor attention, resulting in amplified market risk. Our findings highlight the substantial effect of the Russia-Ukraine war on global market spillovers and the role of investor attention in shaping these dynamics.

Volatility Spillovers among the Major Commodities: A Review

Volatility Spillovers among the Major Commodities: A Review

Exploring interconnections and risk evaluation of green equities and bonds: fresh perspectives from TVP-VAR model and wavelet-based VaR analysis

PurposeThis study attempts to examine the time-varying volatility spillovers between environmentally sustainable assets and quantify the value-at-risk of the portfolios across various frequencies.Design/methodology/approachTo accomplish these objectives, this paper utilizes a connectedness index-based TVP-VAR model and applies the wavelet-based VaR ratio to daily data spanning from January 2018 to September 2023.FindingsThe empirical findings reveal a notable increase in the connectedness index between green stocks and green bonds during the COVID-19 crisis, signifying evidence of a contagion effect. The portfolio’s risk ratio also exhibited a sharp rise amid the pandemic, particularly over medium and long-term horizons, driven by increased spillover among green assets. Notably, our analysis indicates that green bonds influence the connectedness system between green stocks and the value-at-risk ratio, reducing volatility spillover and portfolio risk ratios across various investment horizons. These results highlight the role of green bonds as an effective diversification asset against the risks associated with green equities.Originality/valueThis research investigates the dynamic connectedness and value-at-risk ratio between eight green sectoral renewable energy and non-energy equities and green bonds. We put forward some portfolio implications for green investors with an environmental consciousness who desire to decarbonize their portfolios and mitigate environmental issues.

Realized Volatility Spillover Connectedness among the Leading European Currencies after the End of the Sovereign-Debt Crisis: A QVAR Approach

This paper examines the time-varying spillover effects and connectedness between the euro and other EU and non-EU currencies after the end of the sovereign-debt crisis. We employ the Quantile Vector Autoregression connectedness approach using intraday data for seven currencies (the euro, the British pound, the Swiss franc, the Polish zloty, the Hungarian forint, the Czech koruna, and the Norwegian krone) spanning from 1 January 2016 to 30 November 2022. The results indicate that, almost in all quantiles, the currencies of Eastern European Group countries (i.e., Czech Republic, Hungary, and Poland) are net contributors of information spillovers to other currencies, while currencies of non-EU countries (Switzerland, UK, and Norway) are net takers. Further, we find that the euro is the highest transmitter of net information spillovers to all other currencies until 2021. Interestingly, after 2021, the euro changes to net information spillover taker from all other currencies; highlighting that external shocks (e.g., COVID-19, the energy crisis) have significant risk spillover effects on the European currency market. Policymakers and market participants could benefit from knowing which currency drives developments to avoid unexpected consequences.

Return and volatility connectedness between agricultural tokens and us equity sectors

This study investigates the return and volatility interconnectedness between emerging digital assets, specifically agricultural tokens, and U.S. equity sectors using the TVP-VAR model. Analyzing data from August 7, 2020, to January 2, 2024, the findings indicate modest interconnections between agricultural tokens and U.S. sectors, with time-varying behavior. Notably, return interconnectedness is generally stronger than volatility, except at the sample period's outset, where volatility dominates. Return spillovers predominantly drive the connectedness system, though agricultural tokens uniquely act as net recipients of both return and volatility spillovers, while U.S. equity sectors mainly transmit spillovers. Optimal portfolio analysis, utilizing portfolio weights and hedge ratios, reveals that incorporating agricultural tokens offers portfolio diversification benefits and enhances hedging performance. Investors are advised to frequently adjust portfolios to maximize diversification and hedging gains. These findings provide significant portfolio implications for policymakers, market participants, and investors.

Volatility spillovers among economic policy uncertainty, energy and carbon markets—The quantile time-frequency perspective

As global uncertainty and trade tensions escalate, the world's economic stability faces growing risks. This study examines the volatility spillovers among economic policy uncertainty (EPU), energy, and carbon markets. We assume that returns in energy and carbon markets follow a Skew-t distribution and estimate volatility using an asymmetric EGARCH model. Then, we utilize methods developed by Diebold and Yilmaz (2012) and Barunik and Křehlík (2018), as well as a new quantile connectedness approach to investigate the directional and dynamic risk associations across different time frequencies and market environments. Our study first reveals that long-term volatility spillovers dominate normal periods, whereas medium-term spillovers become more pronounced in extreme cases. Second, EPU is a net receiver of risk in the short term but shifts to a risk transmitter in the medium and long term. Third, the solar energy market, a representative of new energy, drives spillover effects, while the carbon market is particularly susceptible to external influences. Fourth, the total risk spillovers exhibit a dynamic time-varying characteristic and are susceptible to extreme events. Finally, we observe an asymmetric distribution of risk spillovers among markets during extreme events. These findings offer valuable implications for policymakers and investors.

Risk connectedness between international oil and stock markets during the COVID-19 pandemic and the Russia-Ukraine conflict: Fresh evidence from the higher-order moments

Quantifying the connectedness across the oil and stock markets is vital for global asset allocation, systemic risk regulation, and prudent policy making. However, existing studies are mostly confined to return (first moment) and volatility (second moment) levels. This paper integrates the GARCHSK model with the TVP-VAR extended joint connectedness approach to examine higher-order moment risk connectedness between international oil and stock markets in both G7 and BRICS countries, thereby encompassing a wide range of global markets. This paper also discusses the impacts of geopolitical risks, acts, and threats on the total spillovers of volatility and higher-order moments based on the wavelet coherence method. Empirical results demonstrate that the risk spillovers between oil and stock markets are moment-dependent with the total kurtosis spillovers being stronger than the volatility and skewness spillovers. WTI, Brent, INE oil futures, and the Chinese and Japanese stock markets are consistent net receivers of spillovers whereas the remaining G7 stock markets are net transmitters. G7 and the Russian stock markets transmit significant net spillovers of higher-order moments to oil futures. The dynamic spillovers of volatility, skewness, and kurtosis are all time-varying and highly sensitive to the outbreak of major crisis events, especially the China-US trade war, the COVID-19 outbreak, and the Russia-Ukraine conflict. Driving factor analysis shows that the impacts of geopolitical risks, acts, and threats on total spillovers vary over time and across various frequency bands. Geopolitical risks strongly impact the total skewness spillovers during the crisis periods. Geopolitical acts exert a stronger influence on total kurtosis spillovers than geopolitical risks or threats. These findings can offer practical implications for cross-market investors, portfolio managers, market regulators, and policymakers.

Return and volatility spillovers between the raw material and electric vehicles markets

This paper investigates the return and volatility spillovers between the upstream electric vehicles (EV) battery raw materials market and the individual downstream EV producers. The study uses the daily stock returns of two lithium producers and a new model in the GARCH family to capture the jump component of volatility in the EV battery raw materials market. Return and volatility spillovers are studied using an EGARCH(1,1) model including the excess stock returns of lithium producers in the mean equation and their jump component intensity in the variance equation. The results indicate that jumps exist in the EV battery raw materials market and that there exist significant return spillovers between lithium and EV producers. However, this paper did not find any strong evidence of the existence of volatility spillovers between these two markets through lithium unexpected news.

Stock Returns and Volatility Cross-Spillover Effect Between Sri Lanka And Asian Stock Markets

Sri Lanka holds a pivotal position in the Indian Ocean, fostering significant economic ties with South Asia, the Middle East, and Africa. This study examines the financial linkages and stock market behavior between Sri Lanka and key Asian economies (India, China, Pakistan, and Japan) from 2015 to 2021. Using daily stock prices from Bloomberg.com, the analysis employs the EGARCH (1,1) model to assess return and volatility spillovers. Results reveal negative return spillovers from India to Sri Lanka and cross-volatility spillovers from India, China, Pakistan, and Japan to Sri Lanka. Conversely, Sri Lanka exhibits negative return spillovers to India and Pakistan and cross-volatility spillovers to China and Japan. Sub-analysis identifies structural breaks in December 2019, indicating shifts in spillover dynamics pre- and post-Covid-19. These findings offer insights for investors, policymakers, fund managers, and governments to optimize investment strategies, formulate stable policies, and enhance portfolio diversification.

Volatility spillover and dynamic correlation between Islamic, conventional, cryptocurrency and precious metal markets during the immediate outbreak of COVID-19 pandemic

PurposeThis paper aims to investigate the immediate effect of the outbreak of the COVID-19 pandemic by investigating volatility transmission and dynamic correlation between stock (conventional and Islamic) markets, bitcoin and major commodities such as gold, oil and silver at different investment horizons before and after 161 trading days of the outbreak of the COVID-19 pandemic.Design/methodology/approachThe MGARCH-DCC and maximum overlap discrete wavelet transform -based cross-correlation were used in the estimation of the volatility spillover and continuous wavelet transform in the estimation of the time-varying volatility and correlation between the assets at different investment horizons.FindingsThe authors observed a sudden correlation breakdown following the COVID-19 shock. Oil (Bitcoin) was a major volatility transmitter before (during) COVID-19. Digital gold (Bitcoin), gold and silver became highly correlated during COVID-19. The highest co-movement between the assets was observed at medium and long-term investment horizons.Practical implicationsThe study findings have a financial implication for day traders, investors and policymakers in the understanding of volatility transmission and intercorrelation in a bid to actively manage stylized and well-diversified asset portfolios.Originality/valueThis study is unique for its employment in estimating the time-varying conditional volatility of the investable assets and cross-correlations between them at different investment horizons, particularly before and after COVID-19 outbreak.

Navigating APEC Countries: TVP-VAR Insights into Developed and Emerging Stock Markets

The interdependence of stock markets provides important discernment into the behavior of the larger international financial markets. This study investigates magnitude and directional volatility spillover patterns among developed and emerging countries within the APEC bloc, utilizing the TVP-VAR model. The findings indicate that Russia (15.06%), Vietnam11.64%), and Thailand (11.57%) are identified as major transmitters, and Malaysia (-28.95%), Philippines (-9.28%), China (-9.53%) are major receptor of the volatility spillovers in APEC emerging countries. In APEC-developed countries, the United States (56.85%) and Canada (42.6%) are major transmitters, and Japan (-34.02%) and Australia (-53.54%) are identified as a major receptor of the spillover. Moreover, COVID-19 was the most significant crisis, with the highest volatility spillover identified in the APEC bloc's developed and emerging economies. The discoveries have substantial ramifications, offering valuable insights into optimal investment strategies by identifying patterns, magnitudes, and directions of economic volatility shocks.

The nexus between mineral, renewable commodities, and regional stock sectors during health and military crises

We examine the return and volatility spillover dynamics and their portfolio implications among regional stock super-sectors, mineral (Energy, Industrial, and Precious Metals), and renewable (Agricultural and Livestock) commodities. To this end, we apply the time-varying parameter-vector autoregressive (TVP-VAR) model to analyze the intersectoral-commodity linkages separately in four major regions (Europe, Eastern Europe, Asia Pacific, and North America). The empirical results show that stock market sectors dominate the spillover transmission mechanism, while commodities emerge as net recipients of shocks. Moreover, we find heterogeneous connectedness patterns between stock sectors and commodities, predominantly running from the Energy and Basic Resources stocks to the Energy and Industrial Metals commodities. Thus, energy commodities play a more vital role as a spreader of volatility shocks amid the COVID-19 pandemic and the wake of the Russia-Ukraine war. The optimal portfolio weights reflect two episodes of “flight to safety” towards all commodities except Energy, triggered by the pandemic and the war, as investors decrease their fund allocation to stocks in favor of commodities.

The impact of COVID-19 on global financial markets: A multiscale volatility spillover analysis

This paper presents a comprehensive multiscale analysis of volatility spillover mechanisms among diverse financial markets utilizing a novel combination of Normalized Adaptive Multivariate Empirical Mode Decomposition (NA-MEMD) and Time-Varying Parameter Vector Autoregressive (TVP-VAR) model. Our analysis spans Bitcoin, crude oil, gold, foreign exchange, emerging stock markets, and developed stock markets, examining their respective roles in global volatility transmission. Utilizing the NA-MEMD methodology and a time-varying volatility spillover index, we find that in the short-term, Bitcoin and crude oil primarily act as volatility receivers, while other markets serve as volatility transmitters. Over the long-term, gold and Bitcoin consistently act as volatility receivers, with Bitcoin and gold showing evident safe-haven effects, while the remaining markets primarily function as volatility transmitters. Particularly post-COVID-19, developed stock markets emerge as significant transmitters of volatility, largely directed towards the crude oil market. By evaluating and comparing risk transmission patterns among financial markets before and during the COVID-19 pandemic, our findings offer valuable insights that can assist policymakers and other stakeholders in managing financial uncertainty in times of global crises.

Research on the Volatility Spillover Effects of Real Estate Industry and Banking Based on VAR under the Influence of COVID-19 Pandemic

Affected by the COVID-19 pandemic, the volatility of the Chinese financial market has intensified. To study the impact of COVID-19 pandemic on the spillover effects of real estate and banking, selecting the daily closing price of the banking and real estate from December 22, 2016 to March 22, 2024 as research samples, this paper divides three sub-sample intervals into periods before the pandemic, during the pandemic control and in the post-pandemic era. Through the vector autoregressive (VAR) model, the difference in the spillover effects of the two industries in the three periods is compared. The main conclusion is that the impact of the epidemic is mainly reflected in the spillover effects of banking on real estate. Compared with the period before the pandemic, the negative impact of banking on real estate during the pandemic control lasted longer. In the post-pandemic era, the direction of the banking spillover effect on real estate has changed, which shows a stronger positive impact. Combined with the empirical results, this paper puts forward three policy recommendations. Banking can avoid risks and promote the common development of banking and real estate through credit support, financial innovation and risk management.

The Post-Internationalization Evolution of the Price Discovery Pattern in China’s Iron Ore Markets

Previous literature provided evidence of a negative impact of internationalization on the quality of China’s iron ore futures market within a 6-month window (i.e. June 1, 2018 to November 31, 2018), but little is known on the long-term impact. Using a longer, 4-year-7-month window from June 1, 2018 to December 30, 2022, we examine the market’s price discovery function, an important measure of market quality. We find significant structural break in China’s iron ore data series in August 2021, which largely coincide with a period of rising commodity prices to all-time high. Before the breaks, the price discovery function of China’s iron ore futures appears quite weak, with the spot market leading the futures market, which is consistent with the findings of Fan et al. During the post-break period, however, the futures market demonstrates a stronger price discovery function and takes over the leading role. The day-of-the-week effects in iron ore futures also seem to weaken post-break as well. Our GARCH model results exhibit significant bi-directional volatility spillover between the futures and spot markets.

Quantile time−frequency connectedness between energy and agriculture markets: a study during the COVID-19 crisis and the Russo−Ukrainian conflict

PurposeThis paper aims to examine the volatility connectedness between energy and agricultural commodities across different quantiles and time horizons.Design/methodology/approachThis study uses the quantile frequency connectedness approach on daily data spanning from January 2019 to November 2023.FindingsThe results indicate a sharp increase in total connectedness during the COVID-19 crisis and the Russian−Ukrainian conflict, suggesting that both the crisis and the war contribute to volatility spillover among energy and soft commodities. In fact, the findings suggest that, in the short term, the effects of the pandemic have a greater impact on dynamic risk spillover than those of the war. However, over the long term, the consequences of geopolitical tensions related to the war exert a more significant influence compared to the effects of the pandemic.Originality/valueThis study confirms that energy market prices and oil uncertainty play a significant role in explaining fluctuations in agricultural commodities across diverse timeframes, frequencies and quantiles. Particularly, at extreme quantiles, the results indicate that large shocks have a more pronounced impact than small shocks. These findings hold important implications for policymakers and market participants.