Search Results (61)

Using a time-frequency and quantile connectedness approach, our study examines the complex return spillovers dynamics between BRICS Plus stock markets, the volatility index (VIX), and the global geopolitical risk index (GPRD). By employing advanced models such as TVP-VAR, quantile connectedness, and spectral decomposition, we demonstrate how these markets interact across different market conditions and periods. Our results indicate that the VIX consistently acts as the dominant net transmitter of shocks, especially during periods of heightened uncertainty such as the COVID-19 pandemic, the Russian-Ukraine conflict, and the Trump-era U.S.-China trade tensions. In contrast, the GPRD functions predominantly as a net receiver of shocks, indicating its potential role as a hedge during geopolitical crises. BRICS Plus markets exhibit heterogeneous behavior: Brazil, South Africa, and Russia frequently emerge as net transmitters, while China, India, Egypt, Saudi Arabia, and the UAE primarily act as net receivers. Spillovers are strongest at the extremes of the return distribution and are mainly driven by short-term dynamics, underscoring the importance of high-frequency reactions over persistent long-term effects. These findings highlight the asymmetric, nonlinear, and state-dependent nature of global financial contagion, offering important insights for risk management, asset allocation, and macroprudential policy design in emerging market contexts. Full article

This paper investigates the frequency dynamics of financial and macroeconomic connectedness by measuring tail-risk and uncertainty for two emerging African economies, namely Morocco and Tunisia, over the quarterly period Q2-2010 to Q4-2024. We employ a quantile connectedness approach, which, unlike traditional mean-based methods, leads to capturing asymmetries, tail-risk dependencies, and state-dependent spillovers, and to providing early warning signals of systemic stress and financial uncertainty. Our results reveal a stark divergence between the two stock markets in their roles in transmitting and absorbing shocks. The Moroccan stock market acts as a net transmitter, occasionally driving macroeconomic conditions and propagating uncertainty throughout the system. In contrast, the Tunisian stock market acts as a net receiver, with macroeconomic fundamentals, particularly GDP and money supply. These findings highlight how structural differences in emerging markets affect the transmission of shocks and offer actionable insights for policymakers, regulators, and investors to manage financial risks and uncertainty. Full article

This paper investigates the return spillover dynamics among carry trade, stock, foreign exchange, and commodity markets to identify their roles as net transmitters or receivers of shocks under varying market conditions. Employing a Quantile Vector Autoregressive (QVAR) framework within the network-connectedness approach, the analysis captures asymmetric and state-dependent relationships across these markets. In addition, the study examines the influence of U.S. monetary and economic policy uncertainties on the total return spillovers among these markets across different market regimes, using the quantile-in-causality technique. The empirical results reveal that market influence shifts with changing conditions, while total interconnectedness intensifies during periods of elevated uncertainty, particularly throughout the bear market with the total connectedness index reaching 69.97%. Moreover, U.S. Monetary Policy Uncertainty (MPU) exerts varying effects on total connectedness depending on the prevailing market regime, with a pronounced effect at 0.50 quantile, representing stable market regime with no effect at extreme market conditions. These findings offer valuable insights for policymakers and investors, especially regarding the timing of asset allocation and investment decisions under different states of market uncertainty. Full article

This paper investigates the relationship between cryptocurrencies and other financial assets, with a particular focus on the dynamics of information flow between developed and emerging markets. To achieve this objective, the study applies a combined methodology of spillover index analysis and network topology based on graph theory. The analysis covers key cryptocurrencies (Bitcoin and Ethereum), stocks, and conventional currencies over the period November 2017 to September 2022, and distinguishes between short-term and long-run dynamics. The empirical findings show that in the short run, Bitcoin and Ethereum predominantly act as net shock transmitters, whereas in the long run, stocks and conventional currencies, together with Bitcoin and Ethereum, become the principal conveyors of spillover shocks. The network topology analysis corroborates these results by revealing the centrality of these assets in the spillover structure. By integrating spillover and network approaches across different markets and time horizons, this study contributes to the literature by providing a more nuanced understanding of how cryptocurrencies interact with traditional financial assets under varying market conditions. Full article

This study analyzes how sectoral stock volatility in the GCC region responds to global financial uncertainty shocks originating from the U.S. (CBOE VIX), Europe (VSTOXX-50), Bitcoin investors’ Sentiment Indices (BSI), and disaggregated global Financial Stress Indicators (FSI) by using both the “Frequency” and “Time” domain TVP-VAR based connectivity approaches. The “Time” and “Frequency” domain TVP-VAR results indicate that the Energy, Financials, Materials and REIT sectors experience the highest shock spillover from the U.S. and European equity market uncertainty (VIX and VSTOXX-50) for the overall and long-term investment horizons. Whereas, all the five disaggregated global financial stress indicators and BSI transmit higher shocks spillovers towards the sectoral stock conditional volatility of Energy and Materials sectors for the overall and long-term investment horizons. Furthermore, the “Frequency” domain TVP-VAR approach shows that overall shocks spillovers are higher in long-term and intensified during the COVID-19 period. The Energy, Materials, and REIT sectors’ high sensitivity to U.S.VIX and Euro.VSTOXX-50 shocks calls for sector-specific hedging—such as sectors remain least susceptibility to long-term U.S. and European equity risk shocks such as Utility. Over the long-term and overall investment horizons, the Energy and Material sectors’ position as the main shock recipient from all five global financial stress components and the BSI underscores its role as a volatility hub. Policymakers should enforce stress tests and capital buffers for energy and material focused firms, while proactive liquidity management and commodity hedging are vital during global financial stress and BSI spikes to limit funding and operational risks. 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

The FTX collapse marked a significant shock to global crypto markets, prompting concerns about systemic contagion. This paper investigates the dynamic connectedness between cryptocurrencies, DeFi tokens, and tech stocks, focusing on the systemic impact of the FTX collapse. We decompose total, internal, and external connectedness across asset groups using a time-varying parameter VAR model. The results show that post-FTX, Bitcoin and Ethereum intensified their roles as core shock transmitters, while Tether consistently acted as a volatility absorber. DeFi tokens exhibited heightened intra-group spillovers and occasional external influence, reflecting structural fragility. Tech stocks remained largely insulated, with reduced cross-market linkages. Network visualizations confirm a post-crisis fragmentation, characterized by denser internal crypto-DeFi ties and weaker inter-group contagion. These findings have important policy implications for regulators, investors, and system designers, indicating the need for targeted risk monitoring and governance within decentralized finance. Full article

In this study, we investigate the return propagation mechanism, hedging effectiveness, and portfolio performance across several common agricultural commodities, crude oil, and S&P 500 index, ranging from July 2000 to June 2024 by using a time-varying parameter vector autoregression (TVP-VAR) connectedness approach and three common multiple assets portfolio optimization strategies. The empirical results show that, the total connectedness peaked during the 2008 global financial crisis, followed by the European debt crisis and the COVID-19 pandemic, while it remained relatively lower at the onset of the Russia-Ukraine conflict. In the transmission mechanism, commodities and S&P 500 index exhibit distinct and dynamic characteristics as transmitters or receivers. Portfolio analysis reveals that, with exception of the COVID-19 pandemic, all three dynamic portfolios outperform the S&P 500 benchmark across major global crises. Additionally, the minimum correlation and minimum connectedness strategies are superior than transitional minimum variance method in most scenarios. Our findings have implications for policymakers in preventing systemic risk, for investors in managing portfolio risk, and for farmers and agribusiness enterprises in enhancing economic benefits. Full article

This paper examines the firm-level carbon intensity of 83 constituent stocks in the Hang Seng Index, constructs two distinct indexes from the 20 firms with the highest and lowest carbon intensities, and analyzes the connectedness of their annualized daily volatilities with four key external factors over the past 15 years. Our findings reveal that low-carbon stocks—often represented by high-tech and financial firms—tend to exhibit higher volatility, reflecting their more dynamic business environments and greater sensitivity to changes in revenue and profitability. In contrast, high-carbon companies, such as those in the utilities and energy sectors, display more stable demand patterns and are generally less exposed to abrupt market shocks. We also find that oil price shocks result in greater volatility spillovers for low-carbon stocks. Among external influences, the U.S. stock market and Treasury yield exert the most significant spillover effects, while crude oil prices and the U.S. dollar–Chinese yuan exchange rate act as net volatility recipients. Full article

To examine the spillover of tail-risk information across global stock markets, we select nine major stock markets for the period spanning from June 2014 to May 2024 as the sample data. First, we employ effective Rényi transfer entropy to measure the tail-risk information spillover. Second, we construct a Diebold–Yilmaz connectedness table to explore the overall characteristics of tail-risk information spillover across the global stock markets. Third, we integrate wavelet analysis with effective Rényi transfer entropy to assess the multi-scale characteristics of the information spillover. Our findings lead to several key conclusions: (1) US and European stock markets are the primary sources of tail-risk information spillover, while Asian stock markets predominantly act as net information receivers; (2) the intensity of tail-risk information spillover is most pronounced between markets at the medium-high trading frequency, and as trading frequency decreases, information spillover becomes more complex; (3) across all trading frequencies, the US stock market emerges as the most influential, while the Japanese stock market is the most vulnerable. China’s stock market, in contrast, demonstrates relative independence. Full article

In the globalized economic system, environmental, social, and governance (ESG) factors have emerged as critical dimensions for assessing non-financial performance and ensuring the long-term sustainable development of businesses, influencing corporate behavior, investor expectations, and regulatory landscapes. This article applies the VAR-DY network analysis method to construct a large-scale financial volatility spillover network covering all Chinese stocks. It explores the risk transmission paths among different ESG-rated groups and analyzes the patterns and impacts of risk transmission during extreme market volatility. The study finds that as ESG ratings decrease from AAA to C, the network’s average shortest path length and average connectedness strength decreases, indicating that highly rated companies play a central role in the network and maintain their ESG ratings through close connections, positively affecting market stability. However, analyses of the 2015 Chinese stock market crash and the COVID-19 pandemic show a general increase in volatility spillover effects. Notably, the direction of risk spillover in relation to ESG ratings was opposite in these two events, reflecting differences in the underlying drivers of market volatility. This suggests that under extreme market conditions, traditional risk management tools need to be optimized by incorporating ESG factors to better address risk contagion. Full article

This study examines the interconnectedness of African stock markets during three major global crises: the 2008 Global Financial Crisis (GFC), the COVID-19 pandemic, and the Russia–Ukraine conflict. We use daily stock index data from 2007 to 2023 for ten African countries and apply a Time-Varying Parameter Vector Autoregressive (TVP-VAR) model. The results reveal that volatility connectedness among African markets intensified during all three crises, peaking during the COVID-19 pandemic followed by the 2008 GFC and the Russia–Ukraine conflict. Short-term connectedness consistently exceeded long-term connectedness across all crises. South Africa and Egypt acted as dominant transmitters of volatility, highlighting their systemic importance, while Morocco showed increased influence during the COVID-19 pandemic. These findings suggest that African markets are more globally integrated than previously assumed, making them vulnerable to external shocks. Policy implications include the need for stronger regional financial cooperation, the development of early warning systems, and enhanced intra-African investment to improve market resilience and reduce contagion risk. Full article

This study aims to reveal the network connectedness between the volatilities of Emerging and Growth-Leading Economies (EAGLEs) stock exchanges with the frequency-based TVP-VAR connectedness approach. Connectedness results were obtained in short (1–5 days) and long (5-inf) period frequencies among the volatilities obtained with the Garman–Klass volatility estimator. According to the dynamic TCI results, connectivity peaked during the COVID-19 and Russia–Ukraine War periods. BVSP is the most dominant transmitter of the network and spreads the most effect to the emerging markets. As a result of the pairwise metrics, SSE has the lowest values and is positioned as a relatively independent market in the network. In particular, SSE has almost no connection with BIST in the short term, while it has a more significant effect on BIST in the long term. Moreover, the connectedness metrics show that MOEX is in a neutral position in the network and is largely affected by its internal dynamics. Full article

This study examines the volatility and hedging effectiveness of commodities, specifically gold and oil, on the Indian stock market, focusing on both aggregate and sectoral indices. Data have been collected from 1 January 2021 to 31 December 2024 to cover the post-COVID-19 period. Utilizing the Asymmetric Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroskedasticity (ADCC-GARCH) model, we analyze the volatility spillovers and time-varying correlations between commodity and stock market returns. The analysis of spillover connectedness reveals that both commodities exhibit limited and inconsistent hedging potential. Gold demonstrates low and stable spillovers in most sectors, indicating its diminished role as a reliable safe-haven asset in Indian markets. Oil shows relatively higher but volatile spillover effects, particularly with sectors closely tied to energy and industrial activities, reflecting its dependence on external economic and geopolitical factors. This study contributes to the literature by providing a sector-specific perspective on commodity–stock market interactions, challenging conventional assumptions of hedging efficiency of gold and oil. It also emphasizes the need to explore alternative hedging mechanisms for risk management in the post-crisis phase. Full article

Using a sample of S&P 500 stocks, this paper examines the investor sentiment spillover network between firms and assesses how the sentiment connectedness in the network impacts stock price crash risk. We demonstrate that firms with higher sentiment connectedness are more likely to crash as they spread more irrational sentiment signals and are more sensitive to investor behaviors. Notably, we find that the effect of investor sentiment on crash risk mainly stems from sentiment connectedness among firms rather than firms’ individual sentiment, especially when market sentiment is surging or declining. These findings remain robust after controlling for other determinants of crash risk, including stock price synchronicity, accounting conservatism, and internal corporate governance strength. Our results underscore the importance of sentiment connectedness among firms and provide valuable insights for risk management among investors and regulatory authorities involved in monitoring risk. Full article