Search

This study examines the link between stocks and decentralized finance (DeFi) in terms of returns and volatility. Major G7 exchange-traded funds (ETFs) and various highly traded DeFi assets are considered to ensure the robustness of the empirical experiment. Specifically, this study applies the vector autoregression generalized autoregressive conditional heteroskedasticity (VAR-GARCH) model to examine the information transmission of these two markets on a two-way basis and the dynamic conditional correlation (DCC)-GARCH model to assess the bivariate correlation structure between each DeFi and ETF pair. The volatility spillover analysis proves a contagion effect occurred between different geographic markets, and even between markets of different natures and typologies, during the most turbulent moments of the COVID-19 crisis and the war in the Ukraine. Our results also reveal a weak positive correlation between most DeFi and ETF pairs and positive hedge ratios that approach unity during turbulent times. In addition, DeFi assets, except for the Bazaar (BZR) Protocol, can offer diversification gains when included in financial investment portfolios. These results are particularly relevant for portfolio managers and policy-makers when designing investment strategies, especially during periods of financial crisis. [ABSTRACT FROM AUTHOR]

In the study, the existence of volatility spillovers between stock, foreign exchange, crude oil, and precious metals markets is investigated for Turkiye. Daily data covering the period January 1, 2013--January 1, 2023 are analyzed using Diebold and Yılmaz Connectivity Analysis. In the study, the BIST100 index, USD/TL and EUR/TL exchange rate, Brent crude oil price in dollar terms, and spot gold and spot silver prices in dollar terms are analyzed. Findings of the study show that the directional volatility spillovers from others to Brent are the smallest, and the directional volatility spillovers from others to EUR are the largest. On the other hand, the directional volatility spillovers from USD to others are the largest spillovers, and the directional volatility spillovers from Brent to others are the smallest. Moreover, the net volatility spillovers from USD to others are the largest, and the net volatility spillovers from BIST100 to others are the smallest. [ABSTRACT FROM AUTHOR]

Abstract This study examines the link between stocks and decentralized finance (DeFi) in terms of returns and volatility. Major G7 exchange-traded funds (ETFs) and various highly traded DeFi assets are considered to ensure the robustness of the empirical experiment. Specifically, this study applies the vector autoregression generalized autoregressive conditional heteroskedasticity (VAR-GARCH) model to examine the information transmission of these two markets on a two-way basis and the dynamic conditional correlation (DCC)-GARCH model to assess the bivariate correlation structure between each DeFi and ETF pair. The volatility spillover analysis proves a contagion effect occurred between different geographic markets, and even between markets of different natures and typologies, during the most turbulent moments of the COVID-19 crisis and the war in the Ukraine. Our results also reveal a weak positive correlation between most DeFi and ETF pairs and positive hedge ratios that approach unity during turbulent times. In addition, DeFi assets, except for the Bazaar (BZR) Protocol, can offer diversification gains when included in financial investment portfolios. These results are particularly relevant for portfolio managers and policy-makers when designing investment strategies, especially during periods of financial crisis.

The emergence of Covid-19 in late 2019 rapidly shattered the Asia-Pacific region (APR), a bastion of economic dynamism, and it became the epicenter of the global health crisis. This unprecedented pandemic not only triggered a public health catastrophe but also unleashed a financial storm, exposing vulnerability within the region's interconnected economies. This study identifies the factors driving volatility spillovers within Asian-Pacific financial markets during the initial wave of the Covid-19 pandemic (January 2020–February 2021). We analyze the interplay of pandemic transmission dynamics, government interventions, central bank policies, and socioeconomic variables. Our findings reveal a robust and persistent association between the rising number of Covid-19 cases per million and volatility spillovers. We introduce three novel determinants—the number of intensive care unit beds, population density, and the proportion of the elderly population—which significantly impact volatility transmission in response to new cases. Stringent government measures, such as travel bans and lockdowns, mitigate volatility spillovers. Conversely, central bank policies increase volatility spillovers. These insights contribute to a deeper understanding of financial market dynamics in the context of global health emergencies. This knowledge equips policy makers in the APR with valuable tools for navigating future crises.

Abstract This paper examines the dynamics of the asymmetric volatility spillovers across four major cryptocurrencies comprising nearly 61% of cryptocurrency market capitalization and covering both conventional (Bitcoin and Ethereum) and Islamic (Stellar and Ripple) cryptocurrencies. Using a novel time-varying parameter vector autoregression (TVP-VAR) asymmetric connectedness approach combined with a high frequency (hourly) dataset ranging from 1st June 2018 to 22nd July 2022, we find that (i) good and bad spillovers are time-varying; (ii) bad volatility spillovers are more pronounced than good spillovers; (iii) a strong asymmetry in the volatility spillovers exists in the cryptocurrency market; and (iv) conventional cryptocurrencies dominate Islamic cryptocurrencies. Specifically, Ethereum is the major net transmitter of positive volatility spillovers while Stellar is the main net transmitter of negative volatility spillovers.

This paper examines the dynamics of the asymmetric volatility spillovers across four major cryptocurrencies comprising nearly 61% of cryptocurrency market capitalization and covering both conventional (Bitcoin and Ethereum) and Islamic (Stellar and Ripple) cryptocurrencies. Using a novel time-varying parameter vector autoregression (TVP-VAR) asymmetric connectedness approach combined with a high frequency (hourly) dataset ranging from 1st June 2018 to 22nd July 2022, we find that (i) good and bad spillovers are time-varying; (ii) bad volatility spillovers are more pronounced than good spillovers; (iii) a strong asymmetry in the volatility spillovers exists in the cryptocurrency market; and (iv) conventional cryptocurrencies dominate Islamic cryptocurrencies. Specifically, Ethereum is the major net transmitter of positive volatility spillovers while Stellar is the main net transmitter of negative volatility spillovers. [ABSTRACT FROM AUTHOR]

This paper investigates the volatility spillover and connectedness among the stock markets of G7, BRICS countries, and other countries where COVID-19 is more severe. For this investigation, we perform static and rolling-window analysis to measure volatility spillovers using the spillover index approach and LASSO-VAR for estimating high-dimensional VARs. We also examine the network connectedness at different periods. Our findings indicate that the recent COVID-19 pandemic intensifies volatility spillovers, supporting the financial contagion effects. Furthermore, the United States, Spain, and Russia markets are net volatility transmitters for most of the period before and during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Abstract This study investigates volatility spillovers and network connectedness among four cryptocurrencies (Bitcoin, Ethereum, Tether, and BNB coin), four energy companies (Exxon Mobil, Chevron, ConocoPhillips, and Nextera Energy), and four mega-technology companies (Apple, Microsoft, Alphabet, and Amazon) in the US. We analyze data for the period November 15, 2017–October 28, 2022 using methodologies in Diebold and Yilmaz (Int J Forecast 28(1):57–66, 2012) and Baruník and Křehlík (J Financ Economet 16(2):271–296 2018). Our analysis shows the COVID-19 pandemic amplified volatility spillovers, thereby intensifying the impact of financial contagion between markets. This finding indicates the impact of the pandemic on the US economy heightened risk transmission across markets. Moreover, we show that Bitcoin, Ethereum, Chevron, ConocoPhilips, Apple, and Microsoft are net volatility transmitters, while Tether, BNB, Exxon Mobil, Nextera Energy, Alphabet, and Amazon are net receivers Our results suggest that short-term volatility spillovers outweigh medium- and long-term spillovers, and that investors should be more concerned about short-term repercussions because they do not have enough time to act quickly to protect themselves from market risks when the US market is affected. Furthermore, in contrast to short-term dynamics, longer term patterns display superior hedging efficiency. The net-pairwise directional spillovers show that Alphabet and Amazon are the highest shock transmitters to other companies. The findings in this study have implications for both investors and policymakers.

This paper analyzes the returns and volatility connectedness between oil prices and Eurozone sector returns during the global financial crisis. We employ the TVP-VAR frequency connectedness approach with daily data of Brent prices and 18 Eurozone supersector indices from 15 November 2014 to 24 November 2023. Our results show a high average connectedness of the returns and volatilities. Industrial Goods are the largest transmitter contrariwise Media supersector is the largest receiver of shocks on returns. The same finding is for volatility, the result shows that Industrial Goods and Services transmit the highest risk in contrast, the Media has the highest receiver volatility indices. The timevarying connectedness (TCI) of returns and volatilities in both show a drastic increase in March 2020. This increase is a result of COVID-19. Whereas, there has been no rise in connectivity following Russia's invasion of Ukraine. Our result highlighted that Brent was a net receiver of volatility shocks during the Russian invasion of Ukraine. [ABSTRACT FROM AUTHOR]

This study investigates the volatility and return spillovers between Private Equity Buyouts (PE) and Venture Capital (VC), the equity market, precious metals, real estate, and the Dollar index, which has been widely ignored in the literature. We analysed daily data from 2 January 2004 to 29 December 2022 using Diebold and Yılmaz's (2012) framework. Our data covers the global financial crisis and the COVID-19 period and is rich enough to examine the linkages between the mentioned financial markets thoroughly. PE's higher connectedness with the equity market than VC’s is the main finding of this research. Besides, PE and VC have low connectedness to precious metals, real estate, and the Dollar index. In the sample period, VC is a net receiver, while PE is a net transmitter of volatility and return spillover. An exciting finding is that during the COVID-19 pandemic, VC experienced lower volatility spillover than PE from the broad market proxied by S&P 500. Investors and portfolio managers can benefit from our results to better diversify their portfolios. [ABSTRACT FROM AUTHOR]

We explore evolving research trends and hotspots in financial contagion through keywords co‐occurrence and co‐citation network analyses. 2,071 articles have been collected from Web of Science Core Collection database from 2005 to 2021 and been analyzed by using bibliometric methods. The results indicate a tremendous growth in research on financial contagion, especially following the Global Finance Crisis. The current research mainly focuses on understanding the causes and consequences of past financial crises and recessions, examining the network effects of banks and other important financial institutions on risk contagion, developing new systematic approaches to modelling financial contagion, and providing empirical evidences for financial contagion among various asset classes and across different countries and regions. We find that there is still no consensus regarding the causes and measures of financial contagion, however, new promising perspectives have emerged to expand research in this area. We also propose several future directions for studies on financial contagion based on the research gap identified in this review. [ABSTRACT FROM AUTHOR]

This study investigates volatility spillovers and network connectedness among four cryptocurrencies (Bitcoin, Ethereum, Tether, and BNB coin), four energy companies (Exxon Mobil, Chevron, ConocoPhillips, and Nextera Energy), and four mega-technology companies (Apple, Microsoft, Alphabet, and Amazon) in the US. We analyze data for the period November 15, 2017–October 28, 2022 using methodologies in Diebold and Yilmaz (Int J Forecast 28(1):57–66, 2012) and Baruník and Křehlík (J Financ Economet 16(2):271–296 2018). Our analysis shows the COVID-19 pandemic amplified volatility spillovers, thereby intensifying the impact of financial contagion between markets. This finding indicates the impact of the pandemic on the US economy heightened risk transmission across markets. Moreover, we show that Bitcoin, Ethereum, Chevron, ConocoPhilips, Apple, and Microsoft are net volatility transmitters, while Tether, BNB, Exxon Mobil, Nextera Energy, Alphabet, and Amazon are net receivers Our results suggest that short-term volatility spillovers outweigh medium- and long-term spillovers, and that investors should be more concerned about short-term repercussions because they do not have enough time to act quickly to protect themselves from market risks when the US market is affected. Furthermore, in contrast to short-term dynamics, longer term patterns display superior hedging efficiency. The net-pairwise directional spillovers show that Alphabet and Amazon are the highest shock transmitters to other companies. The findings in this study have implications for both investors and policymakers. [ABSTRACT FROM AUTHOR]

This study examines received and transmitted volatility spillovers of Credit Default Swap (CDS) and Asset-Swap Spread (ASW) for Brazil and Turkey. The empirical analysis is implemented using two country-based (stock markets and exchange rates) and two global (volatility index and global economic activity index) variables to account for the impact of integration into global markets. Empirical results suggest that both countries display distinctive features in their spillover networks. While exchange rates and the stock market figure prominently in Brazil as a source of spillovers, for Turkey, the primary element in spillovers appears to be credit risk indicators. Time-varying analysis results show that the European Debt Crisis of 2010-2011 and the global liquidity crunch of 2018-2019 are two critical periods in volatility spillovers that occurred toward credit risk indicators. Brazil displays more sensitivity to the developments of the pandemic than Turkey, likely due to its dependence on global economic activity and energy prices. Finally, for both countries, the leading variable in spillovers to credit risk indicators during financial turbulence episodes appears to be foreign exchange markets. This result highlights both economies’ fragility and vulnerability to foreign exchange market-based shocks. Thus, we suggest effective and solid measures in this regard. Otherwise, those shocks could potentially induce a higher cost of financing in both economies due to the negative impacts on CDS and ASW spreads.

The act of modeling and forecasting stock market volatility has become essential to risk management practice; it has become one of the most prevalent subjects in financial econometrics and has been mainly and continuously used in the valuation of financial assets and the Value at Risk, as well as the pricing of options and derivatives. The purpose of this paper is to contrast the FIGARCH model in the prospect of establishing the best algorithm to forecast PSI 20 index (PSI stands for Portuguese Stock Index). This study analyzed PSI 20 index to identify the behavior of the Portugal stock market in terms of volatility and then evaluated the forecasting ability of GARCH family models using Portugal PSI 20 index sample data for the long period from May 2010 - August 2023 (which is more than 13 years in daily data). There are 3396 daily observations. The results indicated that the PSI 20 index’s volatility is asymmetric. The present empirical investigation also seeks to illustrate the potential for investment returns as well as the associated risk. Our findings may have implications for risk management in Portugal, as well as a deeper understanding of the PSI-20 Portugal stock market volatility dynamics, given the scarcity of prior such studies.

Oil consumption not only makes up a large percentage of the overall operating expenses for the marine shipping industry, besides that, the tanker sector is a major carrier of global oil supply, which magnifies the relevance of oil market for the shipping industry. In this backdrop, the following study examines the volatility transmission between marine shipping industry’s tanker and dry cargo market and oil market using daily data from May 2006 to August 2021 by employing spillover index methodology. The empirical results suggest pronounced spillovers for the tanker market while lower spillovers are observed for dry cargo market, indicating the well-integrated tanker market in comparison to dry cargo sector and oil market. The volatility in oil prices contributed higher spillovers in the tanker market, and remained a net contributor. The volatility in oil prices is a significant source of the volatility transmission during periods of the sudden drop in oil prices coupled with the higher volatility in oil market, and is a net receiver during stable periods. The period of higher spillovers lasts longer for the tanker sector as compared to dry cargo sector. In the particular case of dry cargo market, the smaller (larger) the size of the vessels, the greater (lower) are the spillovers observed (From and To). Hedging turns out be irrelevant during turmoil periods, as the comovement between shipping and oil market becomes stronger. The spillovers are pronounced during the period of financial crisis, COVID-19 and 2014–2016, owing to the significant fluctuations in oil prices and a troubled period for marine shipping industry.

This paper extends the literature on the relationship between oil price shocks and financial markets by examining the effect of supply and demand oil shocks on emerging energy markets, stocks of emerging markets, and gold and exploring the impact of unpredictable oil events on the degree of connectedness among these markets. We show that the effect of supply oil price disturbances drives volatility spillovers in emerging markets with prominent medium- and long-term effects, unlike demand oil price unanticipated changes, particularly during turbulent periods such as the 2008 subprime crisis, the COVID-19 pandemic, and the 2015 oil price crash. These volatility spillover effects are influenced by a marked relationship between supply oil disturbances and emerging energy markets. We also expose that the COVID-19 pandemic volatility spillover consequences in emerging markets are unprecedented compared to the 2008 financial crisis. This can be attributed to the different nature of the related oil price disturbances and financial crises. Overall, the findings highlight the role of crude oil supply shocks as drivers not only of volatility dynamics in energy and equity emerging markets but also of financial connectedness patterns in these economies. [ABSTRACT FROM AUTHOR]

This study examines the volatility spillover between the US and China's soybean futures markets, and between China's soybean, soybean oil, and meal futures markets. A synchronization technique is used to overcome the bias from differences in the closing time of two exchanges. On the basis of BEKK‐GARCH and DCC‐GARCH on the data from January 2010 to April 2023, our results indicate that: First, there is a one‐way spillover from the US to China's No.1 soybean futures and a two‐way spillover between the US and No.2 soybean futures. Second, after 2018, the volatility spillovers of No.1 soybean futures declined, while that of No.2 increased significantly. Third, the dynamic conditional correlations confirmed our results that the spillover between No.2 soybean and soymeal, and between No.2 soybean and soyoil futures increased significantly. Our findings demonstrate the leading role of US soybeans in cross‐border trading and the increasing role of No.2 soybeans in cross‐country and cross‐commodity spillover. [ABSTRACT FROM AUTHOR]

This study investigates the time‐varying connectedness between subsectoral clean‐energy stocks and fossil fuel energy commodities (crude oil, natural gas, and coal) over the period of December 2013–January 2023 employing the Diebold and Yilmaz approach and the dynamic conditional correlation generalized autoregressive conditional heteroscedasticity model. According to the findings, oil transmits the highest volatility spillover shocks to biofuels, and the least to the fuel cell industry. Both natural gas and coal transmit the highest volatility spillover shocks to energy storage, and the least to geothermal and green information technology, respectively. The study also finds strong and time‐varying volatility connectedness among clean‐energy assets and fossil fuels, significantly affected by global extreme events, such as the COVID‐19 pandemic and the Russia–Ukraine conflict. Additionally, the study provides time‐varying and mean optimal hedge ratios with optimal portfolio weights for investors. The empirical results are robust, and important portfolio and policy implications based on empirical findings are provided. [ABSTRACT FROM AUTHOR]

A growing literature has employed the existing generalized spillover measures to measure the connectedness – or market integration – of cryptocurrencies. This method, while useful, does not properly control for the cross-correlations of the cryptocurrencies when computing aggregate spillovers from all others to any given cryptocurrency, whereas the joint spillover method of Lastrapes and Wiesen (2021) does. This paper further describes the novel multivariate conditioning sets employed by the joint spillover method. By employing these two techniques and evaluating the differences in the results, we demonstrate that controlling for the cross-correlations of cryptocurrencies matters for measuring aggregate spillovers and the overall connectedness of the cryptocurrency market. Using data on ten of the most traded cryptocurrencies, we find that the generalized spillover index overestimates overall connectedness by over nine percentage points relative to the new joint spillover index. This difference varies temporally and across cryptocurrencies. [ABSTRACT FROM AUTHOR]

The main aim of this research study is to conduct an empirical analysis regarding the behavior of the Asian stock markets in under the impact of turbulent events based on a case study for Japan. The analyzed period selected for this study covers the sample period from September 2006 until September 2023, including daily observations. Moreover, the sample period also covers the turbulent period of certain extreme events such as the global financial crisis of 2007-2008 and the COVID-19 pandemic. This empirical research study makes an obvious contribution to the existing literature on the long-term behavior of Asian stock markets.

Volatility spillover informs whether the information in one market impacts the information in another. This paper examines whether oil market volatility spills over to the equity markets of selected SAARC countries. The study uses data from February 2013 to September 2019 to obtain updated evidence about the transmission of global oil price volatility to the equity markets of the SAARC member countries. The bivariate EGARCH model is used to test for volatility transmission from the oil market to the stock market. It is found that oil price shocks do not significantly impact equity market volatility, except in Bangladesh. Policymakers can use these findings when making policy decisions.

Abstract How does stablecoin design affect market behavior during turbulent periods? Stablecoins attempt to maintain a “stable” peg to the US dollar, but do so with widely varying structural designs. The spectacular collapse of the TerraUSD (UST) stablecoin and the linked Terra (LUNA) token in May 2022 precipitated a series of reactions across major stablecoins, with some experiencing a fall in value and others gaining value. Using a Baba, Engle, Kraft and Kroner (1990) (BEKK) model, we examine the reaction to this exogenous shock and find significant contagion effects from the UST collapse, likely partially due to herding behavior among traders. We test the varying reactions among stablecoins and find that stablecoin design differences affect the direction, magnitude, and duration of the response to shocks. We discuss the implications for stablecoin developers, exchanges, traders, and regulators.

The main aim of this research study is to conduct an empirical analysis regarding the behavior of the Asian stock markets in under the impact of turbulent events based on a case study for Japan. The analyzed period selected for this study covers the sample period from September 2006 until September 2023, including daily observations. Moreover, the sample period also covers the turbulent period of certain extreme events such as the global financial crisis of 2007-2008 and the COVID-19 pandemic. This empirical research study makes an obvious contribution to the existing literature on the long-term behavior of Asian stock markets. [ABSTRACT FROM AUTHOR]

This paper examines the interconnectedness among European equity REITs (Real Estate Investment Trusts) due to increased financialization of the real estate sector and European economic integration. It uses two models, Diebold and Yilmaz's generalised variance decomposition and Barunik and Krehlik's time-frequency dynamics framework. The study covers a sample of 42 Pan-European REITs over a 15-year period from 2004 to 2018 and finds that the connectedness among REITs is influenced by the geographical location and performance of commercial real estate sub-sectors. The dynamic analysis shows that the source of shocks does not determine the persistence, but rather how the markets interpret the shocks during high-frequency intervals. The paper concludes that the connectedness structure among REITs reflects uncertainty interaction, with some effects observed mainly at high frequency levels, and few unexpected shocks found in the long-term stability of REIT returns. [ABSTRACT FROM AUTHOR]

The act of modeling and forecasting stock market volatility has become essential to risk management practice; it has become one of the most prevalent subjects in financial econometrics and has been mainly and continuously used in the valuation of financial assets and the Value at Risk, as well as the pricing of options and derivatives. The purpose of this paper is to contrast the FIGARCH model in the prospect of establishing the best algorithm to forecast PSI 20 index (PSI stands for Portuguese Stock Index). This study analyzed PSI 20 index to identify the behavior of the Portugal stock market in terms of volatility and then evaluated the forecasting ability of GARCH family models using Portugal PSI 20 index sample data for the long period from May 2010 - August 2023 (which is more than 13 years in daily data). There are 3396 daily observations. The results indicated that the PSI 20 index's volatility is asymmetric. The present empirical investigation also seeks to illustrate the potential for investment returns as well as the associated risk. Our findings may have implications for risk management in Portugal, as well as a deeper understanding of the PSI-20 Portugal stock market volatility dynamics, given the scarcity of prior such studies. [ABSTRACT FROM AUTHOR]

AbstractThe interconnection of stock markets offers valuable insights into the broader dynamics of global financial markets. This study uses the Diebold and Yilmaz index model to analyze and measure volatility spillovers and interconnectedness among APEC stock markets. The objective is to identify major transmitters of volatility spillovers and assess the magnitude of different crisis cycles. The results show that the US is the major contributor (69.54%) to volatility spillovers in APEC stock markets, followed by Canada (52.92%) and Mexico (37.09%). These three economies are part of the highly integrated regional bloc, say, North American Free Trade Agreement (NAFTA). New Zealand has the highest net inflow of spillovers, while spillovers account for 32.86% of the error variance across APEC equity markets. Moreover, notable spikes in volatility spillovers have been observed as a result of various events, including the Chinese stock bubble, the Global Financial Crisis (2007–2008), European debt crises, the Chinese stock market crash, the cryptocurrency crash, the COVID-19 pandemic, and the Russia-Ukraine conflict. The study’s findings imply that policymakers should enhance economic integration and cooperation within APEC countries to manage volatility spillovers effectively. The research highlights market interactions for a large sample, aiding in identifying investment opportunities and risk management strategies.

The interconnection of stock markets offers valuable insights into the broader dynamics of global financial markets. This study uses the Diebold and Yilmaz index model to analyze and measure volatility spillovers and interconnectedness among APEC stock markets. The objective is to identify major transmitters of volatility spillovers and assess the magnitude of different crisis cycles. The results show that the US is the major contributor (69.54%) to volatility spillovers in APEC stock markets, followed by Canada (52.92%) and Mexico (37.09%). These three economies are part of the highly integrated regional bloc, say, North American Free Trade Agreement (NAFTA). New Zealand has the highest net inflow of spillovers, while spillovers account for 32.86% of the error variance across APEC equity markets. Moreover, notable spikes in volatility spillovers have been observed as a result of various events, including the Chinese stock bubble, the Global Financial Crisis (2007–2008), European debt crises, the Chinese stock market crash, the cryptocurrency crash, the COVID-19 pandemic, and the Russia-Ukraine conflict. The study's findings imply that policymakers should enhance economic integration and cooperation within APEC countries to manage volatility spillovers effectively. The research highlights market interactions for a large sample, aiding in identifying investment opportunities and risk management strategies. [ABSTRACT FROM AUTHOR]

Copyright of Comparative Economic Research is the property of Wydawnictwo Uniwersytetu Lodzkiego and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper examines the dynamics of volatility spillovers among five major tourism stock indices during the Covid-19 period. Our paper enriches the current literature as it is the first paper to investigate the volatility spillovers among major global tourism stock indices by adopting Diebold and Yilmaz (2012. Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66.), and Barunik and Krehlik (2018. Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk. Journal of Financial Econometrics, 16(2), 271–296.) time and frequency domain methods. Results suggest that total spillovers of the tourism stock indices rose significantly during the pandemic. Turkey and Italy are net volatility spillover transmitters, and others are net volatility spillover receivers. Findings of this study also indicates that the effect of volatility transmission among tourism stock markets is temporary (short-lasting). The results suggest that short-term investors and portfolio managers should avoid investing in the tourism indices in the short term. [ABSTRACT FROM AUTHOR]

How does stablecoin design affect market behavior during turbulent periods? Stablecoins attempt to maintain a "stable" peg to the US dollar, but do so with widely varying structural designs. The spectacular collapse of the TerraUSD (UST) stablecoin and the linked Terra (LUNA) token in May 2022 precipitated a series of reactions across major stablecoins, with some experiencing a fall in value and others gaining value. Using a Baba, Engle, Kraft and Kroner (1990) (BEKK) model, we examine the reaction to this exogenous shock and find significant contagion effects from the UST collapse, likely partially due to herding behavior among traders. We test the varying reactions among stablecoins and find that stablecoin design differences affect the direction, magnitude, and duration of the response to shocks. We discuss the implications for stablecoin developers, exchanges, traders, and regulators. [ABSTRACT FROM AUTHOR]

We study the impact of COVID-19 on the pairwise dependence between three indices, the COVID-19 Media Coverage Index, MSCI World Semiconductor Index, and the MSCI World Energy Index, as well as investigate the respective volatility spillovers. We find intervals of weak, moderate, and strong coherence between the Media Coverage Index and returns and volatility of semiconductor and energy sector companies. Low coherence intervals indicate a diversification potential of investments in these sectors and in their volatility-based products during periods of systemic crises such as the financial turmoil induced by COVID-19. Our results provide evidence that after the escalation of the pandemic in early 2020, the energy sector cedes its leading role in terms of volatility to the semiconductor industry. We report on appealing hedging attributes related to the decoupling between the trends in the global semiconductor industry and the global energy sector accelerated by the COVID-19 triggered crisis. [ABSTRACT FROM AUTHOR]

This paper examines volatility transmission across 10 major sectors in Iranian stock market over the period 10/11/2009 to 10/04/2022 using time-varying parameter vector autoregressive (TVP-VAR). Our findings show that first; the total connectedness index is approximately 54 percent, indicating that volatility spillovers across the Iranian major sectors are substantial. Second; among these 10 sectors, “investment” and “base metal” act as net transmitter of risks while “medicine”, “oil product” and “cement” sectors are the greatest receivers of risk. Third; the evidence reveals the presence of lead-lag effect in the investigated network. The greatest stock market sectors play the role of volatility transmitter to other sectors, while the relatively small sectors have no risk spillovers on major sectors. This paper can provide regulatory suggestions for policymakers and risk management for investors.

The relationship between corn and ethanol markets has become a popular topic and has been investigated in various studies. However, examining the co-volatility spillover between corn and ethanol markets remains neglected in the literature. This paper aims to fill this gap by analyzing the co-volatility spillover between corn and ethanol markets in the world’s largest ethanol producers and consumers, including the United States, Brazil, and China. To achieve this purpose, we utilize the Bayesian BEKK-GARCH(1,1) model to estimate the degree of co-volatility of corn and ethanol returns. Our empirical results indicate a significant bidirectional volatility spillover between corn and ethanol in all countries. We also find that the co-volatility between corn and ethanol returns is not stable and fluctuates over time, particularly in 2016 and 2020, which correspond to the 2010s oil glut and the COVID-19 pandemic, respectively.

Copyright of Wieś & Rolnictwo is the property of Instytut Rozwoju Wsi & Rolnictwa, Polska Akademia Nauk and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The global lockdowns including movement restrictions during COVID‐19 pandemic impacted the hospitality business negatively and by extension the trading of related stocks such as travel & tourism stocks. Owing to the long standing hedging potential of gold, we examine whether this potential can be extended to the travel & tourism stocks in order to hedge against the associated risks caused by the current pandemic. Using daily data from January 2016 to July 2020 and constructing optimal portfolio strategies, we find that gold serves as a very strong hedge and safe haven for travel & tourism stocks, most especially in the pandemic period. This conclusion validates the inclusion of gold in the diversified portfolio of travel & tourism stocks in order to improve the risk‐adjusted return performance for investors in the sector particularly during COVID‐19 pandemic. [ABSTRACT FROM AUTHOR]

With the accelerated pace of financial globalization and the gradual increase in linkages among financial markets, correctly identifying and describing the risk spillover and network diffusion in the financial system is extremely important for the prevention and management of systemic risk. Based on this, this paper takes the equity markets of 17 countries around the world from 2007 to 2022 as the research object, measures the volatility spillover effect of global financial markets using R-Vine Copula and the DY spillover index, constructs the volatility spillover network of global financial markets, discovers the spillover and diffusion pattern of global financial market risks, and provides relevant suggestions for systemic risk management. It is found that (1) there are certain aggregation characteristics in the network diffusion of global financial market volatility spillover; (2) developed European countries such as the Netherlands, France, the UK, and Germany are at the center of the network and have a strong influence; (3) Asian countries such as China, Japan, and India are at the periphery of the network; and (4) shocks from crisis events enhance the global financial market volatility spillover effect. Based on the above findings, effective prevention of global financial market risk volatility spillover and network diffusion and reduction in systemic risk need to be carried out in two ways. First, by focusing on the financial markets of key countries in the network, such as the Netherlands, the UK, France, and Germany. The second approach is to mitigate the uneven development in global financial markets and reduce the high correlation among them. [ABSTRACT FROM AUTHOR]