Volatility Connectedness Research Articles

Connectedness of non-fungible tokens and conventional cryptocurrencies with metals

Employing the vector auto-regression based on generalized forecast error variance decomposition, this paper investigates the connectedness of non-fungible tokens (NFTs) with precious and industrial metals and compares the results with those for conventional cryptocurrencies (CCCs). Our study scrutinizes separately the total static and the net dynamic spillovers of returns and volatilities from March 2018 to August 2021. We evidence that both, the total return and total volatility connectedness indices for the NFTs-metals framework are below the respective indices for the CCCs-metals framework, indicating new avenues for hedging and harvesting diversification benefits of NFT exposures. We provide empirical evidence that the NFTs are distinct from the CCCs not only in terms of the volatility spillovers, but in terms of the return spillovers too. In addition, we observe the decoupling in the net volatility spillovers between the precious and non-precious metals due to the COVID-19 meltdown. COVID-19 makes precious metals transmit volatility while industrial metals continue acting as net receivers of volatility shocks. Optimal weight and hedge ratios are presented for NFT-metal and crypto-metal pairs. These findings provide potential implications for investors and policy makers.

Decomposed oil price shocks and GCC stock market sector returns and volatility

This study investigates dynamic mean and tail-based connectedness between decomposed oil price shocks (demand shock, supply shock, and risk shock) and Gulf Cooperation Council (GCC) stock returns and volatility at the aggregate and sectoral levels of stock data. The sample period is January 13, 2012 - January 14, 2022, covering calm and turbulent periods. The results of mean-based connectedness show generally low levels of connectedness over the full sample period for both return and volatility, despite some time-variation and irregularity in the patterns of connectedness across stock sectors. Total, directional, and pairwise connectedness measures surge significantly during Phase 1 of COVID-19, highlighting the pandemic's influence on the oil shocks–GCC stocks nexus. However, Phase 2 of COVID-19 displays a gradual reduction in return and volatility connectedness, which could be attributed to fiscal stimulus and COVID19 relief packages adopted by policymakers to contain the adverse impact of the virus on the economy. Quantile-based connectedness measures reveal evidence of heterogeneity in the impacts of oil shocks across the various quantiles of stock sector returns and volatility. Unlike supply shock, demand shock is a net transmitter of spillovers, irrespective of the quantiles. Volatility connectedness is stronger at the high volatility state than the moderate and low volatility states for all sectors, but strongest for the industrials sector. The results indicate that modelling oil shocks and GCC stock sector returns and volatility should concentrate on the most influential oil shocks (e.g. demand shock) affecting the lower and upper quantiles of sector returns and upper quantiles of sector volatility, especially for the industrials. The findings have implications for improving portfolio risk management and regulatory procedures, which should be necessary to address spillover effects from decomposed oil shocks in the stock markets of oil-exporters such as GCC countries.

Transitory and permanent shock transmissions between real estate investment trusts and other assets: Evidence from time‐frequency decomposition and machine learning

AbstractWe evaluate asset returns and volatility connectedness using the time‐frequency connectedness model and machine learning approaches. Using 48 years of monthly indices of equity real estate investment trusts (EREITs), mortgage real estate investment trusts (MREITs), stocks, commodities, and bonds, we find that shocks to EREIT, and MREIT returns have a transitory impact on other assets. However, asset volatility connectedness among assets occurs at lower frequencies as markets slowly process pricing information. Therefore, shocks to EREIT and MREIT decay gradually and spill over to the other three assets for long periods. We also find that the intensity of the time‐frequency connectedness of returns and volatility varies with business cycles and significant domestic and global non‐recession events. We attribute the dominance of real estate investment trusts (REITs) in destabilising the financial system through long‐term volatility transmission to the heavy linkage of REITs to highly illiquid underlying direct real estate markets and high REITs leverage, making them more sensitive to real estate fundamentals, monetary shocks and macroeconomic risks than stocks and bonds. The result of the algorithm‐based machine learning model broadly supports the dominance of EREITs in the transmission of returns and volatility and shows that commodities have more explanatory power in the transmission of volatility than in returns. The empirical findings have implications for strategic and tactical asset allocation and policy design for market stability.

Integration between asset management tokens, asset management stock, and other financial markets: Evidence from TVP-VAR modeling

Using TVP-VAR modeling, we investigate return and volatility connectedness between asset management tokens and the largest asset management stock as well as other traditional assets. We find asset management tokens offer diversification opportunity in a portfolio comprising traditional assets. Net shock receivers are asset management tokens, while net shock transmitters are asset management stock and other assets. A dynamic analysis of system-wide spillover reveals periodic waves with varying degrees of connectedness. Additionally, we calculate the optimal weights and hedging ratios for asset management token pairs and other financial markets. Results are particularly helpful for policymakers, hedge funds, and portfolio managers.

Asymmetric and time-frequency volatility connectedness between China and international crude oil markets with portfolio implications

This paper tries to examine asymmetric and time-frequency volatility connectedness between the Chinese crude oil futures market and international oil benchmarks. To this end, we separate the realized volatility as bad or good volatility and decompose the aggregate volatility connectedness among these oil markets into the short-, medium-, and long-term components. Our results first show that these crude oil markets are highly connected, whereas the Chinese crude oil futures market is a net receiver in the volatility system. Second, the spillover effect caused by bad volatility is significantly different from that of good volatility, revealing significant asymmetry in the volatility spillovers. Third, the volatility spillovers in the short-term frequency band account for the most of total volatility spillovers. Finally, our results prove that the volatility connectedness information among different oil markets helps design trading strategies and shed light on the arbitrage opportunities in the Chinese new crude oil futures market.

Dynamics of the return and volatility connectedness among green finance markets during the COVID-19 pandemic

This paper examines the return and volatility connectedness among green finance markets including the green bonds, clean energy and socially responsible stocks, especially focusing on the connectedness changes induced by the COVID-19 pandemic. Specially, by employing the TVP-VAR extended joint connectedness approach, five representative time series, i.e., S&P Green Bond index (GBI), S&P Global Clean Energy index (GCEI), S&P Global 1200 ESG index (ESGI), S&P Global 1200 Carbon Efficient index (CEI) and S&P Global 1200 Fossil Fuel Free index (FFFI), are used to measure the connectedness among the markets over the sample period spanning from 1 January 2014 to 31 December 2021. The empirical results show that GBI is the main net receiver of return spillovers, followed by ESGI, CEI and FFFI, whereas GCEI is the main net transmitter of return spillovers during the full sample period. The dynamic total connectedness of five indices' returns is strongly fluctuating and especially exhibits a significant spike after the outbreak of COVID-19 pandemic. Interestingly, the findings of volatility connectedness indicate that ESGI, CEI, and FFFI are net transmitters of volatility spillovers during the full, pre-COVID-19 and post-COVID-19 periods. In addition, the network connectedness analysis highlights the role of GCEI in facilitating the transmission of financial contagion during the full and pre-COVID-19 periods, while that during the post-COVID-19 period shows that GBI receives more spillovers from others, indicating that the connections of the five indices tend to be stronger during market downturn periods caused by extreme events. Our results provide implications for investors and policymakers.

Volatility connectedness between global COVOL and major international volatility indices

This research explores dynamic connectedness amongst financial markets using the novel financial risk measure, global common volatility (COVOL) (Engle and Campos-Martins, 2023) and four major asset price implied volatility measures using a TVP-VAR framework. Considering several major international crises, results show that COVOL is a shock receiver while also identifying that VIX is a dominant risk driver of the pricing of risk transmission for the global financial system. The fluctuations of connectedness between COVOL and each implied volatility indices are highly dependent on periods of exceptional stress across international financial markets.

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.

Integration and risk transmission in the market for crude oil: New evidence from a time-varying parameter frequency connectedness approach

In this study, we introduce a novel time-varying parameter vector autoregressive frequency connectedness approach to obtain refined measures of the frequency transmission mechanism and dynamic integration among six well-established crude oil benchmarks. The period of investigation ranges from May 14th, 1996 to December 3rd, 2020 and focuses on the differences between short-term (1–5 days) and long-term (6–100 days) crude oil volatility connectedness. Findings are suggestive of relatively strong co-movements among crude oil volatility over time. For most part of the sample period, connectedness occurs in the short-run; nonetheless, starting approximately in 2010, long-run connectedness gains much prominence until at least the end of 2015. Long-run connectedness is also prevalent at the beginning of 2020 caused by the COVID-19 pandemic. We opine that periods of increased long-run connectedness relate to deeper changes in the market for crude oil that bring about new dynamics and associations within the specific network.

Exchange Rate and Stock Prices Volatility Connectedness and Spillover during Pandemic Induced-Crises: Evidence from BRICS Countries

This paper investigated exchange rate and stock price volatility connectedness and spillover in Brazil, Russia, India, China, and South Africa (BRICS) during pandemic-induced crises. We first extracted volatility using the Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) model. Then volatility connectedness and spillover were investigated by using (Diebold and Yilmaz, International Journal of Forecasting, 28(1), 57–66, 2012) method. We find that exchange rate volatility and stock return volatilities are connected during pandemic-induced crises. The study also finds volatilities spillover among countries in the sample. Russia has strong volatility connectedness with India in these financial markets. The direction of volatility spillover is from Russia to India. Similarly, Brazil has strong volatility connectedness with South Africa and the direction volatility spillover is from Brazil to South Africa. Finally, China has a weak volatility connection with the remaining BRICS countries. Thus, the volatility transfer in these financial markets and across BRICS countries has economic implications.

Extreme return and volatility connectedness among real estate tokens, REITs, and other assets: The role of global factors and portfolio implications

This paper examines extreme return and volatility connectedness among real estate tokens, REITs, and other assets while accounting for global uncertainties’ effect on connectedness and portfolio implications. The results indicate that the S&P 500 and REITs are the only assets with connectedness in a normal market, while extreme quantile results indicate higher network transmission. There is also evidence of a time-varying upsurge in connectedness, suggesting an event dependency effect. The results also indicate a significantly positive impact from all global uncertainty factors on a bear market. Finally, real estate tokens were found to be the cheapest hedge for oil and Bitcoin.

Price connectedness in U.S. ethanol terminal markets

This article shows, for the first time, the degree of price volatility connectedness across the major regional ethanol markets in the U.S. Connectedness measures are based on forecast error variance decompositions that inform which prices drive system dynamics. We pay special attention to volatility spillovers to and from Chicago, as it is equipped with one of the largest terminals in the U.S. and is widely regarded as the center of ethanol price discovery in the country. Ethanol prices in the Chicago terminal electronic trading platform are also suspected of being manipulated over the 2017‐2019 period. We use Diebold and Yilmaz (2012 and 2014) and a rolling window approach to study the dynamics of price volatility connectedness over time. Using daily data from 2013 to the beginning of 2021, we find that Chicago is the market that generates the most innovations to other market prices. In contrast, Chicago receives the least amount of innovations from all other markets, placing Chicago at the center of price dynamics. We find that price connectedness measures are correlated with market fundamentals, policy, and concentration in the Chicago terminal electronic trading platform, with the latter being associated to an increase in the relevance of Chicago as a central market.

Volatility connectedness among the Indian equity and major commodity markets under the COVID-19 scenario

In this paper, the dynamic relationship between the volatilities of both the Indian equity market and six major commodity markets is analyzed during the COVID-19 pandemic. We employ the time-varying parameters vector autoregression model and wavelet coherence approach to assessing market connectedness. The results reveal a significant increase in volatility correlation and spillovers between the Indian equity market and the six major commodity markets after the outbreak of COVID-19. Furthermore, it was found that after the COVID-19 outbreak, the volatility from the commodity markets rapidly spilled over to the Indian equity market. Similar evidence is also suggested by the wavelet coherence and confirms that the high level of contagion mainly occurs in the medium and long term. We further incorporate our evidence with hedging ratio and minimum portfolio connectedness weight. The results uncover that copper and crude oil are useful assets for Indian equity investors to conduct hedging and construct the portfolio.

Determinants of financial stability and risk transmission in dual financial system: Evidence from the COVID pandemic

Existing literature on spillovers and connectedness between Islamic and conventional financial markets overlooked the fundamental role played by money markets in volatility spillovers and risk transmission across markets. That being so, this paper aims at investigating the dynamic co-movements and volatility spillovers across Islamic and conventional financial markets in a dual financial system over the period from January 3, 2007 to June 30, 2021. To this end, the DECO-GJR-GARCH model and the volatility spillover approach were applied. Furthermore, the ARDL model was utilised to explore the key determinants of co-movements and risk transmission across Islamic and conventional financial markets. This not only allowed us to study the interconnectedness and volatility spillovers between financial sectors under different market conditions but also enabled us to highlight the key role played by the money markets. Empirical results show that markets have significant responses to any new relevant information. While both conventional stock and money market are the main transmitters of shocks to other markets, the Islamic money market is a net recipient. Furthermore, the volatility spillovers across conventional and Islamic financial markets became stronger during the COVID-19 epidemic. The study also finds that global uncertainties have a significant and negative impact on the dynamic co-movements, but not on volatility connectedness among the underlying markets. These findings have important implications for many stakeholders including portfolio managers, investors, and policymakers in terms of diversifying their portfolios and enhancement of financial stability during times of black swan events and negative shocks such as the COVID-19 pandemic.

Quantile connectedness between oil price shocks and exchange rates

Oil is an energy resource and a driver of global economic activities. The increasing need for oil amplifies its trade and places pressure on the current account balance, which causes exchange rate fluctuations. We transcend the mean-based connectedness measures to explore the oil shocks-exchange rates nexus from an asymmetric perspective. With daily data from 07-03–1996 to 22-08-2022, we analyse the quantile dynamic spillovers between oil price shocks and exchange rates of oil-exporting and oil-importing economies. We show that shock sizes shape the system returns and volatility connectedness, with lower-tailed and upper-tailed shocks having a greater influence on the system connectedness than shocks modelled at the conditional median. By demonstrating asymmetry, the findings emphasise that for a detailed comprehension of the oil shocks-exchange rates connectedness under extreme shocks, it is necessary to go beyond mean-based connectedness metrics. The implications of our findings are important for investors, policymakers, and practitioners.

Dynamic connectedness and network in the high moments of cryptocurrency, stock, and commodity markets

This study examines the connectedness in high-order moments between cryptocurrency, major stock (U.S., U.K., Eurozone, and Japan), and commodity (gold and oil) markets. Using intraday data from 2020 to 2022 and the time and frequency connectedness models of Diebold and Yilmaz (Int J Forecast 28(1):57–66, 2012) and Baruník and Křehlík (J Financ Econom 16(2):271–296, 2018), we investigate spillovers among the markets in realized volatility, the jump component of realized volatility, realized skewness, and realized kurtosis. These higher-order moments allow us to identify the unique characteristics of financial returns, such as asymmetry and fat tails, thereby capturing various market risks such as downside risk and tail risk. Our results show that the cryptocurrency, stock, and commodity markets are highly connected in terms of volatility and in the jump component of volatility, while their connectedness in skewness and kurtosis is smaller. Moreover, jump and volatility connectedness are more persistent than that of skewness and kurtosis connectedness. Our rolling-window analysis of the connectedness models shows that connectedness varies over time across all moments, and tends to increase during periods of high uncertainty. Finally, we show the potential of gold and oil as hedging and safe-haven investments for other markets given that they are the least connected to other markets across all moments and investment horizons. Our findings provide useful information for designing effective portfolio management and cryptocurrency regulations.

Returns and volatility connectedness among the Eurozone equity markets

AbstractThe rising degree of integration among different countries around the world calls for the examination of cross‐country connectedness across equity markets. Moreover, the interconnection among some countries – bound by their common economic policies, treaties and agreements, such as Eurozone countries – is stronger than among others. Strong inter‐country ties may cause an intense connectedness among their financial systems. This study examines the returns and volatility connectedness among the equity markets of the Eurozone countries. Using the TVP‐VAR model, we document strong connectedness among their stock markets. The net transmitters of shocks are the most developed Eurozone stock markets, while Lithuania, Slovenia and Slovakia are among the most vulnerable to risks from the more developed Eurozone economies. Thus, for any event that triggers risk transmission across the Eurozone equity markets, equity investors in less developed countries will be more vulnerable to risks from the nine more developed economies.

Time-frequency volatility connectedness between fossil energy and agricultural commodities: Comparing the COVID-19 pandemic with the Russia-Ukraine conflict

This paper uses the TVP-VAR frequency connectedness approach to compare the volatility connectedness induced by the COVID-19 pandemic and the Russia-Ukraine conflict. Both shocks induce increased connectedness, but the pandemic shock is stronger. High-frequency and medium-frequency connectedness dominate during the early stage of the pandemic, while low-frequency connectedness dominates during the conflict. Moreover, fossil energy is the risk transmitter in the early phase of the pandemic, while agricultural commodities become the transmitter during the conflict. We should take precautions against risks contagion from fossil energy and agricultural commodities to the post-conflict economy, and prevent inflation and economic slowdown.

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.

How does the Russian-Ukrainian war change connectedness and hedging opportunities? Comparison between dirty and clean energy markets versus global stock indices

The unexpected Russian invasion of Ukraine created greater uncertainty about unrestricted access to fossil commodities. Therefore, in response to the growing challenges of energy security and climate change, renewable energy could open up new energy sources and investment opportunities for market participants. The main goal of this research is to investigate the volatility spillovers of dirty and clean energy markets versus global stock indices, in situations of rising geopolitical risk. To reveal crucial changes in shock transmission during the period from August 1, 2014 to May 27, 2022, we used volatility connectedness indices based on the novel methodology proposed by Diebold and Yilmaz (2012, 2014, 2015), as well as structural breaks. Furthermore, our study investigates the advantages and disadvantages of heterogeneous diversification in green energy for hedging strategies. Optimal weights and hedge ratios are calculated for portfolio diversification and risk management. We find that clean energy indices generally show lower risk than global equity markets; however, the cost of hedging in renewable energy assets is higher compared to non-renewable energy indices.