Volatility Spillovers Research Articles

Energy firms in China towards resilience: A dynamic quantile connectedness approach

Α comprehensive understanding of the energy and technology sectors is imperative for the implementation of effective climate and industrial policies. This study investigates the quantile interconnectedness between the top five energy equities and the top five technology equities, listed on the Shanghai Stock Exchange 50 Index (SSE50), based on market capitalization. Employing the Quantile VAR methodology, we uncover significant interconnectedness across various quantiles of the return distribution for both energy and technology equities. This implies that price fluctuations within one sector can have a significant effect on the other. Furthermore, our analysis reveals directional connectedness, where energy equities consistently influence technology equity prices throughout the entire period of investigation. Additionally, a heightened degree of interconnectedness is observed during periods of extreme market movements, i.e. in the upper and lower tails of the return distribution. This suggests a more integrated system during stressed conditions, where all equities under investigation exhibit a magnified influence on each other, potentially leading to amplified volatility spillovers. These findings provide valuable insights for investors, portfolio managers, and policymakers, enabling them to develop more informed investment strategies and construct robust risk management frameworks.

Financial Interdependencies: Analyzing the Volatility Linkages between Real Estate Investment Trusts, Sukuk, and Oil in GCC Countries

This study investigates the financial interconnections among Real Estate Investment Trusts (REITs), sukuk (Islamic bonds), and oil in Gulf Cooperation Council (GCC) nations. The study sample comprises S&P GCC Composite Equity Real Estate Investment Trusts (REITs) Shariah, the S&P GCC Bond and Sukuk Index, and the OPEC crude oil basket on a daily basis. The duration of coverage spans from 2014 until the beginning of 2024. The TVP-VAR methodology is utilized to examine the interrelationship among the assets. The results indicate that Real Estate Investment Trusts (REITs) and oil are sources of volatility transmission, whereas sukuk is a recipient of volatility within the network. Examining the net pairwise directional linkages of two assets, namely REITs and oil markets, reveals that they transfer their volatility to the sukuk market. Moreover, a reciprocal relationship exists between REITs and oil regarding volatility spillover. It means that REITs act as transmitters to the oil markets during specific periods, while the influence is reversed at other times. This study implies that portfolio managers and investors can discern the volatility patterns of assets in order to enhance their risk-management techniques. For policymakers, comprehending the interdependence of certain asset classes provides valuable knowledge for formulating regulations that might stabilize the financial system and foster economic growth. From a research and academic perspective, this study enhances understanding of the interconnections between different financial asset classes and pricing dynamics in financial markets.

Volatility spillover effect between cryptocurrency and stock market using MGARCH Bekk model

This paper explores the volatility spillover effects between the cryptocurrency market and the Pakistan Stock Exchange (PSX). Utilising data from January 1, 2019, to April 5, 2024, sourced from Investing and Yahoo Finance, the study employs the Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MGARCH) BEKK model to assess the dynamic interactions between these markets. Stationarity tests confirmed the non-stationarity of time series data at their levels, which became stationary after first differencing, ensuring robust econometric analysis. The results indicate significant volatility spillovers from major cryptocurrencies, such as Bitcoin and Ethereum, to the PSX, highlighting a solid interconnectedness between these markets. This suggests that digital asset volatility significantly influences traditional financial systems. The study concludes that integrating cryptocurrencies into global financial markets introduces risks and opportunities for investors and policymakers. The findings underscore the need for market participants to account for these volatility interactions in their risk management strategies. Additionally, policymakers must consider these interlinkages to maintain financial stability. This research contributes to the literature on financial market volatility by emphasising the importance of understanding the impact of emerging digital currencies on traditional stock markets.

Volatility Spillover and Connectedness Between SME and Main Markets of India and China

Volatility Spillover and Connectedness Between SME and Main Markets of India and China

Are Indian markets insulated from the impact of cryptocurrencies? Unveiling the volatility linkages through multi‐index dynamic multivariate GARCH analysis

AbstractThis paper investigates the dynamic relationships between the volatility of Bitcoin and major Indian stock market indices. Employing a dynamic conditional correlation–generalized autoregressive conditional heteroskedasticity (DCC‐GARCH) model, we explore how volatility shocks and information flow influence the correlations between these asset classes. Our findings reveal a key characteristic: volatility spillovers tend to be short‐lived, indicated by a relatively low DCC‐GARCH parameter (dcca1). This suggests that while a surge in volatility in one market might lead to a temporary increase in correlation with the other, this heightened correlation is unlikely to persist for extended periods. However, the model also highlights a high DCC‐GARCH parameter (dccb1), signifying that the correlations themselves are responsive to new information. This implies that volatility linkages can adjust rapidly in response to market events or economic data releases. To enhance accessibility for a broad audience, we translate these findings into economic intuitions. We illustrate how the model can be interpreted through real‐world examples, such as the impact of sudden policy changes in India or global market flash crashes. By understanding the short‐lived nature of volatility spillovers and the responsiveness of correlations, investors in the Indian markets can make more informed decisions when considering the potential influence of Bitcoin's volatility while contributing to a deeper understanding of the dynamic interactions between cryptocurrency and traditional financial markets in the Indian context.

Volatility Spillover Effect of NCDEX Spot and Futures Prices in Spices

This research is an attempt to assess the volatility in spot and futures prices in spices on NCDEX. Spot price and futures price Volatility is prominent indicators of the commodity futures market to protect the interest of beneficiaries and to hedge sharp price fluctuations in commodity markets. The study tested price patterns using data with 1777 observations for FY2015 to FY2022 daily spot and futures price series of near month contracts. VECM test and EGARCH were computed to examine spot and futures prices for three selected spices, namely jeera (cumin), turmeric and coriander. The results revealed that Turmeric and Coriander had significant bidirectional relationship and Jeera had significant unidirectional relationship between futures and spot market prices. Higher half-life (days) values of futures prices indicates more stability than spot prices of selected spices. Higher asymmetric effect value of spot market indicates higher volatility impacts because of noisy shocks than futures market.

Cross-border ESG rating dynamics: An in-depth connectedness analysis of portfolio returns and volatilities in the USA and Canada

This study uses a time-varying parameter vector autoregression (TVP-VAR) model to examine the dynamic relationship between rating changes and portfolio returns in the US and Canada across the environmental (E), social (S), governance (G) and total ESG assessment pillars. The analysis includes both return and volatility spillovers and covers the period from March 2009 to October 2022. The study reveals a fluctuating pattern of connectedness, influenced by global financial events, such as the 2008 financial crisis. In particular, the US shows higher levels of connectedness. Rating changes, particularly in the ESG dimension, show stronger spillovers than returns, highlighting their importance in portfolio construction. The study further explores net connectedness profiles, identifying ESG rating changes as net transmitters. The results suggest that investors should prioritize rating changes over returns, highlighting the importance of considering ESG factors in portfolio management, especially the social criterion, to mitigate investment risks. The research contributes to the understanding of ESG dynamics in international equity markets and provides valuable insights for investors and market regulators.

The Volatility Spillover Between ESG and Stock Return in the Selected Countries of G7

The primary focus of this study is to analyse the impact of volatility spillover among Environmental, Social, and Governance (ESG) and stock returns in the group of seven (G7) countries. The study reveals that 62.80% of the shock to one index spreads to all other indices, including ESG, on average. Additionally, the study indicates that the TSX (Canada) and Dow Jones (United States) stock returns play a vital role as transmitters of shocks.

Research on Volatility Spillover in the International Crude Oil Futures Markets

Research on Volatility Spillover in the International Crude Oil Futures Markets

Volatility Spillover of Crude Palm Oil (CPO) Commodity between Spot and Futures Market in Indonesia

The development of trade globalization has led to the expansion of market interactions between countries, specifically for Crude Palm Oil (CPO) commodities. This study aims to determine the volatility of CPO prices between the Medan spot market and the futures market consisting of the Jakarta futures market, Malaysia futures market, and the Rotterdam forward market. The daily data on CPO prices in each market from January 2016 to December 2020. The data analysis method uses the GARCH model (1.1). The results showed a volatility transmission from the entire futures market to the Medan spot market. Thus, the CPO commodity futures market influences price volatility and the price formation process in the Medan spot market. Therefore, CPO commodity market players must be alert to the information occurring in the futures market to determine investment strategies.

Volatility Spillover Effect from Energy Markets to Foreign Exchange Markets: The Case of Central and Eastern European and Eurasian Countries

Volatility Spillover Effect from Energy Markets to Foreign Exchange Markets: The Case of Central and Eastern European and Eurasian Countries

Heterogeneity, Jumps and Co-Movements in Transmission of Volatility Spillovers Among Cryptocurrencies

Abstract We analyze properties identified in the price volatility of Bitcoin and some of the leading cryptocurrencies namely Litecoin, Ripple, and Ethereum. We employ Heterogeneous Autoregressive models (HAR) in both a univariate and multivariate level of analysis. First, the significance of heterogeneity and jumps is examined, considering the ability of several univariate HAR models, to predict realized volatility of cryptocurrencies. Second, we examine the relevance of realized volatility jumps and covariances in the transmission of volatility spillovers among cryptocurrencies. We perform a comparative spillover analysis of the multivariate HAR models in two versions, considering variances only and covariances as well. Our results indicate that covariances and jumps inclusion lead to an increase in spillovers. The time-varying spillover analysis indicates higher dependency between Bitcoin and the other cryptocurrencies mostly at short frequencies.

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.