Search Results (34)

This study explores the new insights into the integration and dynamic asymmetric volatility risk spillovers between Bitcoin, currency pairs (USD/ZAR, GBP/ZAR and EUR/ZAR), and traditional financial assets (ALSI, Bond, and Gold) in South Africa using daily data spanning the period from 2010 to 2024 and employing Time-Varying Parameter Vector Autoregression (TVP-VAR) and wavelet coherence. The findings revealed strengthened integration between traditional financial assets and currency pairs, as well as weak integration with BTC/ZAR. Furthermore, BTC/ZAR and traditional financial assets were receivers of shocks, while the currency pairs were transmitters of spillovers. Gold emerged as an attractive investment during periods of inflation or currency devaluation. However, the assets have a total connectedness index of 28.37%, offering a reduced systemic risk. Distinct patterns were observed in the short, medium, and long term in time scales and frequency. There is a diversification benefit and potential hedging strategies due to gold’s negative influence on BTC/ZAR. Bitcoin’s high volatility and lack of regulatory oversight continue to be deterrents for institutional investors. This study lays a solid foundation for understanding the financial dynamics in South Africa, offering valuable insights for investors and policymakers interested in the intricate linkages between BTC/ZAR, currency pairs, and traditional financial assets, allowing for more targeted policy measures. Full article

We examine the quantile-time-frequency connectedness of stock returns among BRICS and G7 markets over the period January 2000 to January 2024, employing the Quantile Vector Autoregression (QVAR) model. Our findings reveal that spillover effects intensify during periods of extreme market conditions, compared to more tranquil phases. Furthermore, the stock markets of France, Germany, the United States, the United Kingdom, Italy, and Canada emerge as primary sources of contagion, whereas the BRICS markets and Japan primarily act as recipients across all quantile regimes. The frequency-quantile decomposition reveals that short-term dynamics primarily drive the net transmission of shocks at both the median and upper quantiles, whereas long-term dynamics are dominant at the lower quantile, indicating more persistent effects during market downturns. Finally, we construct investment portfolios based on the Minimum Connectedness Portfolio (MCP) approach and evaluate them through average portfolio weights and Hedging Effectiveness (HE) ratios. The results demonstrate that G7-based portfolios tend to have lower average weights and higher hedging efficiency, implying greater diversification benefits and enhanced risk mitigation performance compared to BRICS-based portfolios. Full article

Energy raw materials are the basis of the economic system. From this emerges the need to examine in more detail how various uncertainty indices interact with the dynamic of spillover connectedness among energy markets. The TVP-VAR model is used to investigate connectedness among US, European, and Indian oil and gas markets and the S&P carbon allowances Eua index. Following this, the wavelet decomposition technique is used to capture the dynamic correlations between uncertainty indices (GPR and VIX) and connectedness indices. First, the results indicate that energy market spillovers are time-varying and crisis-sensitive. Second, the time–frequency dependence among uncertainty indices and connectedness indices is more marked and can change with the occurrence of unexpected events and geopolitical conflicts. The VIX index shows a positive dependence on total dynamic connectedness in the mid-long-term, while the GPR index has a long-term effect only after 2020. The analysis of the interdependence among the connectedness of each market and the uncertainty indices is more heterogeneous. Political tensions and geopolitical risks are, therefore, causal factors of energy prices. Given their strategic and economic importance, policy makers and investors should establish a risk warning mechanism and try to avoid the transmission of spillovers as much as possible. Full article

As the relationship between cryptocurrency mining activities and electricity consumption becomes increasingly close, the risk spillover effect is steadily drawing a lot of attention to the energy and cryptocurrency markets. For the purpose of studying the risk contagion between the cryptocurrency and energy market, this paper constructs a risk contagion network between cryptocurrency and China’s energy market using complex network methods. The tail risk spillover effects under various time and frequency domains were captured by the spillover index, which was assessed by the leptokurtic quantile vector autoregression (QVAR) model. Considering the spatial heterogeneity of energy companies, the spatial Durbin model was used to explore the impact mechanism of risk spillovers. The research showed that the framework of this paper more accurately reflects the tail risk spillover effect between China’s energy market and cryptocurrency market under various shock scales, with the extreme state experiencing a much higher spillover effect than the normal state. Furthermore, this study found that the tail risk contagion between cryptocurrency and China’s energy market exhibits notable dynamic variation and cyclical features, and the long-term risk spillover effect is primarily responsible for the total spillover. At the same time, the study found that the company with the most significant spillover effect does not necessarily have the largest company size, and other factors, such as geographical location and business composition, need to be considered. Moreover, there are spatial spillover effects among listed energy companies, and the connectedness between cryptocurrency and the energy market network generates an obvious impact on risk spillover effects. The research conclusions have an important role in preventing cross-contagion of risks between cryptocurrency and the energy market. Full article

This paper investigates the spillover effects and transmission networks of systemic risk within China’s national economic sectors under extreme conditions from both time and frequency domain perspectives, building upon the spillover index methodology and calculating the ∆CoVaR index for Chinese industries. The findings indicate the following: (1) Extreme-risk spillovers synchronize across industries but exhibit pronounced time-varying peaks during the 2008 Global Financial Crisis, the 2015 crash, and the COVID-19 pandemic. (2) Long-term spillovers dominate overall connectedness, highlighting the lasting impact of fundamentals and structural linkages. (3) In terms of risk volatility, Energy, Materials, Consumer Discretionary, and Financials are most sensitive to systemic market shocks. (4) On the risk spillover effect, Consumer Discretionary, Industrials, Healthcare, and Information Technology consistently act as net transmitters of extreme risk, while Energy, Materials, Consumer Staples, Financials, Telecom Services, Utilities, and Real Estate primarily serve as net receivers. Based on these findings, the paper suggests deepening the regulatory mechanisms for systemic risk, strengthening the synergistic effect of systemic risk measurement and early warning indicators, and coordinating risk monitoring, early warning, and risk prevention and mitigation. It further emphasizes the importance of avoiding fragmented regulation by establishing a joint risk prevention mechanism across sectors and departments, strengthening the supervision of inter-industry capital flows. Finally, it highlights the need to closely monitor the formation mechanisms and transmission paths of new financial risks under the influence of the pandemic to prevent the accumulation and eruption of risks in the post-pandemic era. Authorities must conduct annual “Industry Transmission Reviews” to map emerging risk nodes and supply-chain vulnerabilities, refine policy tools, and stabilize market expectations so as to forestall the build-up and sudden release of new systemic shocks. Full article

This study examines the dynamic interconnectedness between digital and traditional assets, with an emphasis on fiat currencies (such as JPY/USD and CHF/USD), cryptocurrencies (such as Bitcoin), and digital assets backed by gold (such as Tether Gold and Digix Gold Token) under various economic conditions. The study uses sophisticated techniques, including dynamic connectedness, quantile connectedness, and time-frequency connectedness analyses, to test non-linear and asymmetric interactions between various asset classes. The findings reveal that while cryptocurrencies, especially Bitcoin, frequently serve as net recipients of shocks during times of economic instability, gold and gold-backed assets are the primary shock transmitters. These findings highlight the increasing importance that digital assets play amid economic and geopolitical crises as well as their growing incorporation into the larger financial ecosystem. The study contributes to the literature on asset interconnection and provides implications for systemic risk management and financial stability; specifically, it offers insightful information for hedging and portfolio diversification techniques. Full article

Within the framework of high-frequency volatility modeling, this study investigates the realized volatility spillover dynamics across major cryptocurrencies over an extended period of time. Using a Time-Varying Parameter Vector Autoregression (TVP-VAR) model of the realized volatility (RV), this work constructs the Total Connectedness Index (TCI) and Pairwise Connectedness Index (PCI) to measure the intensity and direction of realized volatility transmission within this digital asset network. Our findings reveal a consistently high level of spillovers among these leading cryptocurrencies, with notable peaks during periods of global market turbulence. Notably, Ethereum emerges as the most influential volatility transmitter, challenging the traditional view of Bitcoin as a primary driver of volatility spillovers. This reflects Ethereum’s pivotal role in decentralized finance (DeFi), decentralized applications (dApps), and its growing trading activity, suggesting a shifting influence in the increasingly diversified cryptocurrency ecosystem. Full article

Since the implementation of unconventional monetary policies (UMPs) by the US in response to the global financial crisis (GFC) and the COVID-19 pandemic, there have been increasing concerns that these forward guidance and quantitative easing programmes have had spillover effects on global equity markets. We specifically question whether the implementation of these UMPs have had spillovers to African equities, which have been previously speculated to be decoupled from global markets and shocks. Time-varying-parameter (TVP) frequency connectedness and wavelet coherency methods were used to examine the dynamic time-frequency spillovers between daily time series of the US shadow short rate and African equities returns/volatility between 1 January 2007 and 31 March 2023. On one hand, the TVP frequency connectedness analysis reveals robust long-run spillovers from US monetary policy to African equity markets during specific periods: 2009, 2013, 2020, and 2021. These coincide with instances when the Federal Reserve announced their transition from conventional to unconventional monetary practices and vice versa. On the other hand, the wavelet analysis provides insights into the ‘sign’ of the spillovers, indicating mixed phase dynamics during UMPs responding to the GFC. In contrast, anti-phase or negative co-movements characterize UMPs implemented during the COVID-19 pandemic, implying that these policies increased both returns and volatilities to African equities. Altogether, we conclude that US UMP has increasing deteriorated market efficiency and amplified portfolio risk in African equities whilst during ‘normalization’ periods US monetary policy has little transmission effect. Full article

This study investigates dynamic risk spillover effects between renewable energy markets and Chinese green financial markets from a time-frequency perspective by utilizing weekly data from two types of markets with a span from January 2010 to August 2022. The results show that the total spillover and net spillover effects vary widely across time. Short-run spillover is more dominant than long-run spillover. In most cases, green finance markets play the role of risk receivers in the system, while renewable energy markets are the main risk transmitters in the short run and the main risk spillover contributors in the long run. Finally, we determine that the hedging effect of green finance assets in the renewable energy market may decrease after the COVID-19 pandemic. Full article

A wide range of statistical and econometric models have been applied in the extant literature to compute and assess the volatility spillovers among renewable stock prices. This research adds to the body of knowledge by analyzing the dynamic asymmetric volatility spillover between major NASDAQ OMX Green Economy Indices, including solar, wind, geothermal, fuel cell, and developer/operator. The novelty of the research is that it distinguishes between positive and negative volatility spillovers in a time-varying fashion and conducts a connectedness network analysis. To do so, the study implements the Time-Varying Parameter Vector Autoregression (TVP-VAR) approach, as well as the connectedness network. The empirical investigation is based on high-frequency data between 18 October 2010, and 2 April 2022. The main findings may be summarized as follows. First, the analysis reveals a shift in the dominance of positive and negative volatility transmission during the study period, which represents compelling evidence of dynamic asymmetric spillover in the volatility transmission between renewable energy stocks. Second, the connectedness analysis indicates that the operator/developer and solar sectors are the net transmitters of both positive and negative volatility to the system. In contrast, the wind, geothermal and fuel cell sectors receive shocks from other renewable energy stocks. The asymmetric spillovers between the renewable energy stocks are confirmed using the block bootstrapping technique. Finally, the dynamic analysis reveals a substantial impact of the COVID-19 outbreak on the interdependence between renewable energy stocks. The findings above are robust to different lag orders and prediction ranges. Full article

This paper aims to investigate the volatility spillovers among selected emerging economies’ sovereign credit default swaps (SCDSs), including those of Saudi Arabia, Russia, China, Indonesia, South Africa, Brazil, Mexico, and Turkey. Using data from January 2010 to July 2023, we apply the time-domain and the frequency-domain connectedness approaches.Empirical results show that (i) Indonesia, followed by China and Mexico, are the main transmitters of sovereign credit risk volatility. (ii) Among global factors, the volatility index (VIX), economic policy uncertainty (EPU), and global political risk (GPR) positively impacted spillover on lower and higher quantiles. The results offer critical insights for international investors, policymakers, and researchers, emphasizing the importance of risk-aware investment strategies and cautious policy formulation in the context of financial crises and political events. Full article

As climate change impacts energy consumption, investments in clean energy are now associated with increased levels of risk and uncertainty. Consequently, the management of risk for clean energy investors has garnered significant academic attention. This study was designed to explore the risk transfers among clean energy markets, how they respond to market volatility, and how exceptional events impact the risk spillover. This was performed by examining the risk spillover of and asymmetric connectedness between clean energy markets, green bonds, and other financial markets in China, in line with the connectedness framework and minimum spanning tree technique. The findings revealed that clean energy markets exhibit heterogeneity in terms of the direction and magnitude of net risk spillover, the types of hedging assets involved, and their response to market volatility. Exceptional events, such as the Russian–Ukrainian conflict and COVID-19 pandemic, have an impact on the spillover relationships. During stable market conditions, green bonds experience fewer spillovers from clean energy markets, whereas, in times of volatility, gold markets are subjected to fewer spillovers. In the time domain, the overall long-term spillover is stronger compared to the short and medium terms. In the frequency domain, there is a significant risk of low-frequency transmission. These findings hold practical implications for energy investors in portfolio construction and for policymakers in pursuing sustainability objectives. Full article

This study aims to provide important insights regarding the integrated structure of global factors and Pakistan’s leading sector-level indices by estimating the dynamic network and pairwise connectedness of the global crude oil index, MSCI index, European economic policy uncertainty index, and important sector-level indices of Pakistan based on QVAR using daily frequency over the period of 20 years from 2002 to 2022. The findings demonstrate high interconnectedness among global factors indices and Pakistan’s leading sector-level indices. The results of net directional connectivity showed that the EPEUI, WTI, and MSCI indices are the “net receivers” of volatility spillover. At the same time, the financial and energy sectors are the “net transmitter” of shocks. Connectedness is high amid financial upheavals. The research findings provide crucial insights for policymakers, businesses, portfolio managers, and investors. Full article

By using data from 2018 to 2022 and employing quantile VAR time-frequency and quantile VAR spillover models, this study investigates the spillover connectedness between global uncertainties, namely, geopolitical risk, economic policy uncertainty, and climate policy uncertainty, and seven leading global renewable energy indices. The results show strong total connectedness (82.87%) between renewable energy and uncertainty indices. DJRE, R&CE, MSCIEE, WRE_cpu, GEPU_C, and GEPU_P are found to be net receivers, and WRE to be net transmitters of spillovers. Additionally, the MSCIEE sector is the least connected, i.e., 2.51%, followed by the R&CE sector at 4.55%, while the ERE sector is the most connected one, i.e., 65.8%. We discover that the two market-based uncertainties have less impact than economic policy uncertainty (EPU), which has a significant impact. The conclusions have ramifications for decision-makers and investors in the renewable energy markets from the standpoint of sustainable development. The study reveals diversification avenues and recommends that investors consider MSCIEE and R&CE sectors for parking their funds because of lower risk, i.e., less connectivity and greater diversification. Full article

During the COVID-19 pandemic, when stress levels were heightened and social connections were threatened, a spike in green space visits was observed. Drawing upon the value–belief–norm (VBN) theory, which explains the influence of personal values and world view on perceived obligations to the environment and to action, relevant correlates were examined in relation to people’s psychological wellbeing in a bid to better elucidate this phenomenon. We aimed to explore the associations amongst a number of protective factors for psychological wellbeing and to examine the applicability of the VBN theory to wellbeing rather than environmental behaviour. Our research aim was to understand some of the correlates of the use of urban green spaces in Singapore during COVID-19. In total, 268 adult residents of Singapore completed an online survey measuring proximity/frequency of visits to green space, value orientations, nature connectedness, social connectedness, religious belief, spirituality and psychological wellbeing, along with sociodemographic variables such as age and gender. As predicted by the VBN theory, biospheric value orientation and spirituality were positively associated with nature connectedness. The nature connectedness association with psychological wellbeing was completely mediated by spirituality. Frequency of visits to nature was also positively associated with nature connectedness. Neither proximity to nature nor social connectedness were associated with nature connectedness. An altruistic value orientation was associated only with religious belief. Our results indicate that during uncertain times, people are drawing on either social or nature connections as coping mechanisms to fulfil psychological needs and enhance psychological wellbeing. Spirituality mediates this pathway for nature connectedness but not for social connectedness. Full article