Volatility Connectedness Research Articles

Dynamic Volatility Connectedness among Cryptocurrencies: Evidence from Time-Frequency Connectedness Networks

This study examines the time-varying connectedness among the realized volatilities of seven major cryptocurrencies between January 2020 and May 2022. To this end, we implement the time and frequency connectedness time-varying parameter vector autoregression (TVP-VAR) approaches. Our findings propose that (i) the COVID-19 pandemic significantly affected the dynamic connectedness; (ii) the total connectedness index hits its apex around the official announcement of the pandemic; (iii) in line with previous studies Ethereum, Bitcoin, and Link are the largest propagators/recipients of shocks; (iv) the tightest volatility interdependencies are related to the short-run.

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

ABSTRACT 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.

Time-frequency dependence and connectedness among global oil markets: Fresh evidence from higher-order moment perspective

Investigating the dependence and connectedness among global oil markets is of great significance for cross-market investors and regulators. However, most of the existing studies are confined to lower-order moments and the time domain. This paper is the first to examine the time-frequency dependence and connectedness among global oil markets from the higher-order moment perspective by applying the wavelet coherence method and the newly proposed time-varying parameter vector autoregression-based frequency connectedness approach. The empirical results demonstrate that higher-order moment dependence among oil markets is weaker than return and volatility dependence. In general, Dubai, Minas, and Tapis oil exhibit relatively higher wavelet coherence with Daqing oil at all moments. The lead-lag relationships are heterogeneous during most sample intervals. The total return and volatility connectedness indices are higher than the skewness and kurtosis. The return connectedness mainly occurs in the short term (1–5 days) whereas the volatility, skewness, and kurtosis connectedness occur in the long run (22-Inf days). West Texas Intermediate oil dominates the return, volatility, and skewness connectedness network while Dubai oil dominates the kurtosis connectedness network. Furthermore, the dynamic total, net, and net-pairwise connectedness indices are all time-varying and event-dependent with the higher-order moment connectedness illustrating more volatile features. Several practical implications are provided for various market agents.

Media coverage of COVID-19 and its relationship with climate change indices: A dynamic connectedness analysis of four pandemic waves

This study explores the impact of the COVID-19 media coverage index (MCI) on the return and volatility connectedness of five MSCI Climate Changes Indices (the USA, Emerging Markets (EMU), Japan, Europe, and the Asia Pacific). The sample period was from 11 March 2020–19 January 2022, divided into sub-samples based on four waves of the COVID-19 pandemic. Thus, we use the time-varying parameter vector autoregression (TVP-VAR) model besides the frequency-dependent connectedness network approach. The key findings are as follows. First, the results demonstrate that the MCI is a net receiver of shocks in all waves, and the highest level of connectedness occurs in the first wave. The findings concerning volatility are similar, with the majority of MSCI Climate Change Indices being net transmitters, potentially indicating the severity of the pandemic. Second, estimating the short-, medium-, and long-term return network connectedness indicates the dominance of strong-term connectedness suggesting the spread of shocks within a week. Our results are robust by replacing MCI with Panic Index (PI). These results have implications for investors and policymakers.

Volatility contagion between oil and the stock markets of G7 countries plus India and China

It is imperative to analyze over the potential risks persisting in the financial systems from time to time. In this connection, this study examines volatility spillover between crude oil price and stock prices of G7 plus India and China using Diebold and Yilmaz (2012) technique from Jan 4, 2005–June 9, 2021. Although, our results show high stock market returns volatility connectedness among the sample countries but we find no significant transmission between oil prices and stock markets for the whole sample. The sub-sample results indicate that the period marked by COVID-19 witnessed substantial bidirectional spillovers between oil market and stock market. Empirical results of this study is expected to offer important policy inputs for investors, and policymakers to devise cautious strategies concerning their investments during uncertainties.

The dynamic volatility connectedness of global financial assets during the Ebola & MERS epidemic and the COVID-19 pandemic

ABSTRACT We investigate the dynamic volatility connectedness of regional stocks, gold, Bitcoin, oil, and uncertainty index related to infectious diseases for the period from January 2014 to June 2022. We investigate the connectivity during Ebola & MERS periods, the normal period, the COVID-19 period and the full sample period. We find that the regional stock indices of the US, Europe, Africa and Latin America are net volatility transmitters whereas regional indices of Asia Pacific, Middle East and North Africa, and other assets like gold, oil and Bitcoin are net volatility recipients throughout the sample periods. By employing the TVP-VAR-based dynamic connectedness approach, we find the temporal evolution of system-wide total connectedness and pair-wise connectedness of financial assets to exhibit higher intensity of volatility spillover during the COVID-19 pandemic as compared to other sub-sample periods. We further observe, based on quantile connectedness approach, that the degree of dynamic connectedness is strong and significant across all the quantile spectrums only during the COVID-19 period. We observe that the safe haven characteristics of assets like gold, oil and Bitcoin diminish during the COVID-19 period due to strong dynamic connectedness with regional stock indices. Our findings have implications for policymakers, investors and portfolio managers in better risk management during periods of health epidemics and pandemics.

Portfolio diversification during the COVID-19 pandemic: Do vaccinations matter?

The COVID-19 vaccine rollout expects to mitigate the severe negative impacts of the pandemic on global financial markets. Our study provides supporting evidence for this expectation. We find robust evidence that vaccinations significantly reduce the cross-country stock volatility connectedness among G7 nations, suggesting that the diversification benefits of an international equity portfolio may be enhanced during the pandemic when vaccinations accelerate. We present two explanations for this result. First, the vaccine deployment improves stock market return and decreases individual stock market volatility. Second, the vaccine rollout helps a country’s stock market be more resilient to exogenous shocks. We further demonstrate that a global portfolio using a tactical allocation rule based on the intensity of vaccinations can outperform a buy-and-hold portfolio in terms of risk-adjusted returns.

Asymmetric volatility connectedness between cryptocurrencies and energy: Dynamics and determinants

We explore the dynamics and determinants of volatility connectedness between cryptocurrencies and energy. We employed a block dynamic equicorrelation model and a group volatility connectedness measurement to measure the cross-equicorrelation and volatility connectedness between cryptocurrencies and energy. We also adopted dynamic model averaging to identify the time-varying drivers. The results suggest that changes in cross-equicorrelation between the two groups were affected by influential global events and increased after the COVID-19 pandemic. Volatilities were transmitted in both directions between cryptocurrencies and energy, but the transmission from energy to cryptocurrencies is by far the strongest. The driver identification implies that the factors related to cryptocurrencies and global financial markets had important roles in explaining the volatility connectedness from cryptocurrencies to energy in some periods after the COVID-19 pandemic, but the effects were marginal. In contrast, factors such as electricity consumption, cryptocurrency turnovers, and VIX were important in affecting the volatility connectedness from energy to cryptocurrencies, and the effects depended on factors and changed over time.

Higher-order moment risk connectedness and optimal investment strategies between international oil and commodity futures markets: Insights from the COVID-19 pandemic and Russia-Ukraine conflict

This paper investigates the higher-order moment risk connectedness between West Texas Intermediate (WTI) oil futures, Brent oil futures, Chinese oil futures and commodity futures (agricultural, industrial metals, and precious metals) before and during the COVID-19 pandemic and following the outbreak of the Russia-Ukraine conflict, by combining ex-post moment measures and the novel time-varying parameter (TVP)-vector auto-regression (VAR)-based connectedness approach. Further, this paper depicts the dynamic overall and pairwise correlations between oil and commodity futures and constructs the hedging and optimal-weighted portfolio strategies using the DCC-GARCH t-Copula model. This paper also constructs the multivariate oil-commodity portfolio based on the newly proposed minimum connectedness portfolio approach and takes into account the higher-order moment risk connectedness. The empirical results demonstrate that the dynamic linkages between international oil and commodity futures are positive, time-varying, and have been greatly intensified by the outbreak of the 2018 China-US trade war, the 2020 COVID-19 pandemic, and the 2022 Russia-Ukraine conflict. The risk connectedness results are moment-dependent. The averaged total skewness and kurtosis spillovers are lower than the return and volatility connectedness. Brent (WTI) oil is the largest net transmitter of the return and volatility (skewness and kurtosis) risk spillovers. The dynamic total, net, and net-pairwise spillovers are all time-varying and highly reactive to major crises, especially the COVID-19 pandemic and the Russia-Ukraine conflict. Furthermore, the optimal-weighted portfolio shows a higher risk reduction than the hedging strategy. Finally, the minimum skewness connectedness portfolio shows relatively higher hedging effectiveness, while the minimum kurtosis connectedness portfolio offers the highest cumulative returns.

Return and Volatility Connectedness and Net Directional Patterns in Spillover Transmissions: East and Southeast Asian Equity Markets

Return and Volatility Connectedness and Net Directional Patterns in Spillover Transmissions: East and Southeast Asian Equity Markets

EXUBERANCE, ASYMMETRIC VOLATILITY AND CONNECTEDNESS IN FAN TOKENS

In this paper we provide an empirical investigation on some properties of fan tokens of football clubs. Fan tokens are collectible virtual tokens mainly minted on the Socios Blockchain (using the Chiliz cryptocurrency) providing the opportunity to influence club's decisions, unlocking VIP rewards and access to exclusive promotions, games, chat, and a "superfan recognition". Fan tokens are a financial innovation that allows football clubs to retain and, at the same time, monetise their fan base without making any changes to their corporate and ownership structure and without being subject to the legal constraints that the issue of financial products would entail. As fan tokens are immaterial tokens based on a cryptocurrency, in this paper we fill a gap in the literature by studying to what extent several properties of cryptocurrency carry over to fan tokens. In particular, we investigate whether fan tokens exhibit (a) periods of exuberance, (ii) asymmetric volatility response to price changes and (iii) volatility connectedness among themselves and the Bitcoin and Chiliz cryptocurrencies. Our findings suggest that episodes of exuberance characterise the dynamics of fan token prices, that there is some evidence of reverse asymmetric response of volatility to price changes, and that total connected ness among fan tokens is quite sizeable and that most of them exhibit a rich dynamic with multiple reversal in terms of (net) transmitters and (net) receivers of shocks to the entire set of assets.

Volatility Connectedness on the Central European Forex Markets

Volatility Connectedness on the Central European Forex Markets

Volatility Connectedness Between Global COVOL and Major International Volatility Indices

Volatility Connectedness Between Global COVOL and Major International Volatility Indices

Asymmetric volatility spillover between oil prices and regional renewable energy stock markets: A time-varying parameter vector autoregressive-based connectedness approach

<abstract> <p>The rapid expansion of renewable energy sources and their integration into the energy mix has generated scholarly interest in comprehending the interplay between renewable and conventional energy markets. This research aims to examine the (a)symmetric volatility spillover between the oil market and various regional renewable energy stock markets, namely the US, Europe and Asia. To achieve this objective, we employ the time-varying parameter vector autoregressive-based connectedness (TVP-VAR) approach, which allows analysing the interconnection and transmission of shocks between the different markets. Based on an analysis of daily data relative to the different regional renewable energy stock markets and international oil prices, the findings suggest the presence of a dynamic volatility connectedness between the green and brown energy stock markets. The extent of connectedness is contingent upon the specific regional renewable energy market under consideration. Moreover, the decomposition of the volatility series into <italic>good</italic> and <italic>bad</italic> volatility emphasizes an asymmetric pattern, which becomes more pronounced during periods of major events. On average, the oil market and the Asian renewable energy stock market are net receivers of volatility shocks. In contrast, the US and European renewable energy stock markets are net transmitters of shocks. Our findings provide investors with valuable insights for portfolio design and risk management decisions.</p> </abstract>

The pandemic emergency asset purchase and the sovereign bond market connectedness

We examined the extent to which the biggest euro area sovereign bond markets are connected during the 2017-2020 period. Accordingly, we used the recent Gabaue (2020)'s approach viewed as an alternative to Diebold and Yilmaz's volatility connectedness methodology. We find that such markets are considerably connected during the whole period and the spillovers are relatively time varying. The results also show that the Spanish bond market is the primary net transmitter of shocks, followed by the Italian bond market, while the markets for Germany and France are the main net receivers. Second, we highlight some contribution of ECB's asset purchase and other monetary policy announcements to bilateral spillovers. Also, some pronounced spillovers are found to be generated from the monetary policy in US. Finally, the effect differs widely across bilateral linkages in terms of sign and magnitudes. A likely explanation is that investors started discriminating more through markets.

Return and volatility connectedness between gold and energy markets: Evidence from the pre- and post-COVID vaccination phases

Using a two-step VAR asymmetric BEKK GARCH model, this research explores the asymmetric return and volatility connectedness between gold and several energy markets during three subperiods: pre-COVID, before vaccination, and after vaccination. Gold’s returns and volatility spillover are generally found to be time- and energy-dependent. In addition, the optimal weights, hedge ratios, and hedging effectiveness of energy commodity and gold pairs are calculated during the three subperiods. The results of optimal weights show that investors should increase their investment in energy commodities more than gold (energy commodities) during the after-vaccination period (the pre-vaccination period). Moreover, the hedging strategy would only be effective within the COVID-19 vaccination period, which could have implications for the strategic asset allocation of policy-makers and international investors. Finally, we examine the potential determinants of conditional correlations between gold and energy markets. VIX, EPU, and new confirmed cases are found to be the main predictors of correlations for most energy commodity–gold pairs during the examined period.

Scrutinizing commodity markets by quantile spillovers: A case study of the Australian economy

Notwithstanding Australia plays the lead role in exporting strategic commodities such as crude oil, natural gas, coal, Liquid Natural Gas (LNG), and iron ore, a scattering of researchers attempts to investigate the effects of exported commodities on stock and currency in Australia. In this academic research, our objective is to delve deeply into volatility connectedness among Brent oil, natural gas, coal, iron ore, LNG, stock, and currency markets in Australia. To that end, we adopt Ando et al. (2018) and Baruník and Křehlík (2018) techniques which are built upon Diebold and Yilmaz's (2012) framework for utilizing quantile- and frequency-based spillover analysis respectively. Finally, we used a recent approach developed by Chatziantoniou et al. (2022) for robustness purposes which combines quantile-spillover (due to Ando et al., 2018) and frequency-spillover (due to Baruník and Křehlík, 2018). This approach enables us not only to overcome the methodological shortcomings of prior studies but also to provide an insightful analysis regarding interrelationships across pivotal commodities. Our findings reveal that lower and upper quantiles show more satisfactory performance compared to the conditional mean. This implies that the usage of mean-based connectedness measures does not provide accurate results. More precisely, even though it provides a practical framework for gauging extreme spillovers, it overlooks certain quantiles. The framework, accordingly, undervalues the real effects of spillovers across the markets. What is more, the mentioned principal approach deploys Ordinary Least Square (OLS) framework to gauge the VAR. As a dire consequence, this framework prevents improving the efficiency of the model. We discern Brent oil, natural gas, and Australian stock are the most consequential net transmitters of shocks in this system. Plus, the total spillover index reveals a high level of strength in the return spillovers amid the assets. In terms of policy implications, we expect our outcomes to aid market participants in expanding their perceptions concerning price volatility shocks in these crucial markets. For investors, they are able to measure related risks during extreme positive or extreme negative conditions, leading investors to stabilize their portfolios during extreme conditions and hedging, and risk-pricing, at that. From the results of BK (2018), we comprehend total connectedness does not properly perform in long-horizon. This suggests investors should not hold the markets in short-horizon by reason of high volatility.

Connectedness between travel & tourism tokens, tourism equity, and other assets

We examine the return and volatility connectedness between travel & tourism tokens and other financial assets, including travel and tourism stocks, energy (WTI oil), cryptocurrency (bitcoin) and bonds, gold, the US dollar, using a generalized vector autoregressive framework. Findings show, in normal economic periods, only weak static spillovers between travel & tourism tokens and other assets. However, dynamic analysis reveals increased intensity of spillovers between travel & tourism tokens and other assets during COVID-19. Results are consistent with travel & tourism tokens offering diversification, including surprisingly to equity of the travel and tourism industry, during downturns that particularly impact tourism.

Forecasting Chinese macroeconomy with volatility connectedness of financial institutions

ABSTRACT Systemic risk emphasizes the impact on the real economy and is popularly measured by a network interconnectedness approach. We test, for the first time, whether the volatility connectedness of financial institutions is a significant predictor of Chinese macroeconomy. The connectedness is derived from volatility spillover networks and is measured by total connectedness introduced in Diebold and Yilmaz (2014), which reflects the effects of risk transmission and systemic risk in the financial system. Both in-sample and out-of-sample analyses show that an increase in total connectedness among financial institutions stably and strongly forecasts a slowdown in China’s economic activity over the next three to twelve months, when controlling for many factors. Furthermore, including the total connectedness into the regression models improves the macroeconomy forecasts accuracy. Our results are robust to alternative measures of total connectedness.

The impact of the Russia–Ukraine conflict (2022) on volatility connectedness between the Egyptian stock market sectors: evidence from the DCC-GARCH-CONNECTEDNESS approach

PurposeThis study investigates the impact of the Russia–Ukraine war (2022) on the volatility connectedness between Egyptian stock market sectors.Design/methodology/approachThis study employs the newest dynamic conditional correlation (DCC)-generalized autoregressive conditional heteroskedasticity (GARCH)-CONNECTEDNESS approach to examine volatility connectedness in a sample of ten sectors in the Egyptian stock market, namely banks, education, food, healthcare, industry, information technology, real estate, resources, transportation and travel, ranging from February 1, 2019 to May 31, 2022.FindingsThe findings show that connectedness among the Egyptian stock market sectors varies depending on the time. The average dynamic connectedness measure among sectors in Egypt is 73.24%. This average was 85.63% during the Russia–Ukraine War (2022). The author also shows that the transportation sector is the most significant net transmitter of volatility in the remaining sectors during the Russia–Ukraine War (2022).Practical implicationsThis study intends for policymakers to examine the co-movements, market variations and volatility spillover of stock markets, particularly during crises. Furthermore, the results help investors gain insight into diversifying the investors' portfolio assets to optimize profits.Originality/valueTo the best of the authors' knowledge, no study has investigated the implications of the war between Russia and Ukraine (2022) on sectoral interconnectedness within the stock markets in any country and discussion and empirical evidence from African countries are lacking. This study fills this gap in the literature. Additionally, the author uses the newest approach, the DCC-GARCH-CONNECTEDNESS approach, to describe the time-varying volatility spillover between economic sectors in Egypt.