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The expansion of the globalization process has increased the relationships among financial markets in different countries, which itself has motivated investors to move among them to make more profit. Given the situation in Iran after sanctions, the possibility of investing in well-known financial markets is facing with the risk of sanctions. The present study aims to evaluate the existence of volatility spillover among the financial markets of Iran and Islamic oil exporters countries. To this aim, a multivariate factor stochastic volatility (SV) model and stock price index data were used with daily frequency for the period 12/05/2008-02/19/2020. Based on the results, the main hypothesis that the volatility spillover among the financial markets of OPEC oil-exporting Islamic countries follows a common and uniform random trend is accepted for the United Arab Emirates, Saudi Arabia, and Qatar, but not for Iran and Nigeria. Therefore, diversifying the portfolio for Iranian investors in the financial markets of OPEC Islamic oil exporters can reduce the investment risk in the long run which make such economies an appropriate investment destination for Iranians due to the conditions of sanctions.

The study is an attempt to investigate the impact of crude prices on energy crops; Soyabean, Wheat and Sugarcane for India for the period Jan 2016-Dec 2020. The study mainly covered two dimensions; the spillover of volatility from crude to the energy crops and the asymmetric angle. The econometric tests employed under the study were GARCH(1,1), TGARCH(1) and AR(2)-EGARCH(1,1) Models. The results revealed that return on crude was impacting two crops; sugarcane and wheat while it had no impact on soyabean. The ‘T-GARCH’ results revealing asymmetry were statistically significant for all the three crops, however since soyabean did not have significant slope coefficient in Mean Equation, it was held that asymmetry held only for two crops viz. wheat and sugarcane and not for soyabean. Further coefficient of asymmetry for two crops was positive indicating that positive shock (fall in crude prices) impacted the crop volatility more than an equivalent negative shock (rise in crude prices). The results for spillover of volatility from crude to energy crops using AR(2)-EGARCH(1,1) Model showed that spillover from crude to both; sugarcane and wheat was statistically significant but coefficient in both crops had negative sign. Degree of volatility persistence was statistically significant for these two crops but its value was low implying that a shock to crude had a slow decaying impact on both these crops.

Although a plethora of studies exists on economic uncertainty and stock market returns, our study contributes to the literature by examining the interconnectedness between Twitter uncertainty index and stock return volatility in the G7 countries. Using the dynamic connectedness approach, our results indicate volatility spillover among indices, where on average, 39.71% of a shock that occurs on one index spills over to all other indices. Further, we find the DAX index (Germany) to be a major transmitter of shocks, whereas the S&P 500 index (United States), Twitter market uncertainty, and G7 average returns are net receivers of shocks. Our findings will help investors select optimal portfolios, and policymakers frame stabilizing policy. Our findings are also robust in case of the alternate model. [ABSTRACT FROM AUTHOR]

This paper investigates co-movements among the Chinese stock market, Shanghai International Energy Exchange (INE) crude oil futures and West Texas Intermediate (WTI) crude oil futures. We use Copula models to capture tail dependencies and employ the VAR-BEKK-GARCH model to examine the direction of volatility spillovers. We find that there are positively time-varying dependency relationships among the three markets. Compared with the corresponding upper-tail dependencies, the lower-tail dependencies were larger before the COVID-19 pandemic while relatively weaker after the breakout of the pandemic. Before the COVID-19 pandemic, there was only a statistically significant volatility spillover from WTI crude oil future market to the INE crude oil future market. After the breakout of the COVID-19 pandemic, there were statistically significant volatility spillovers in the two pairs of markets, namely, the WTI–INE and Chinese stock–WTI. However, we only find statistically significant evidence of unidirectional volatility spillover from the Chinese crude oil future market to the Chinese stock market during the pandemic. [ABSTRACT FROM AUTHOR]

Rubber is a traded commodity in the international market with considerable potential. The rubber industry is very essential in driving the economic activities of ASEAN-3 countries, namely Malaysia, Thailand and Indonesia. The close ties between the natural rubber (NR) markets in ASEAN-3 have led to the process of risk dissemination known as volatility spillover. In this regard, the paper aimed to investigate the spillover effect and dynamic correlation of NR price in ASEAN-3 using the Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) model with Baba, Engle, Kraft and Kroner (BEKK) formulation. The empirical result shows that there is a significant bidirectional volatility spillover between the volatility of Malaysian and Thailand NR, while there is only a unidirectional volatility spillover found from Malaysia to Indonesia. However, no volatility spillover was detected either from Thailand to Indonesia or vice-versa. Moreover, results from constant conditional correlation (CCC) found that the dependency on NR among ASEAN-3 was highly significant and positive, indicating the return relationship was moving in the same direction throughout the sample period. However, the result from dynamic conditional correlation (DCC) shows that although the degree of correlation is high among the region, there is a period whereby the level of correlation is low due to crises and unprecedented events like earthquakes and tsunamis. The results also found that the current period of NR volatility depends on its past volatility and any news or information greatly influences and affects the NR volatility in all ASEAN-3 countries. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the volatility spillover relationship between cryptocurrencies and stablecoins dynamically. Within the scope of the study, the daily closing price data of Bitcoin (BTC), Ethereum (ETH), BNB cryptocurrencies, and Tether (USDT) and USD Coin (USDC) stablecoins covering the period from January 1, 2019 to April 6, 2022 was analyzed using the Q-VAR model. Our results suggest that the volatility spillover between the cryptocurrency and stablecoins increased during the Covid-19 pandemic. Moreover, the direction and severity of volatility spillover between cryptocurrencies and stablecoins are affected by global events. While the relationship between cryptocurrencies and stablecoins themselves is strong, the relationship between each other is weak. Our findings suggest that global events influence the interaction between crypto-assets and that cryptocurrencies and stablecoins can be good diversifiers for each other. These findings have important implications for financial market regulators, portfolio investors, and academic research. [ABSTRACT FROM AUTHOR]

This study aims to examine whether there is a return and volatility spillover among energy commodities. As a result of different macroeconomic developments, return volatility in asset prices can spillover among commodities and affect each other's returns. The determination of the factors affecting the prices of energy commodities and the spillover among them is worth examining, especially for those who invest and are interested in the energy market. Within the scope of the study, the data regarding Brent Oil, Heating Oil, Natural Gas, and WTI between 01.01.2008-31.12.2020 are evaluated by VAR-EGARCH method. The results demonstrate that the information shocks, in which the returns of energy commodities interact in the short-term, spillover multidirectionally and asymmetrically in returns and volatility. It is determined that the natural gas return series is affected by the prices of other commodities, but it does not affect any energy commodities. As for the volatility spillover, there is unidirectional spillover from heating oil to natural gas series, but there is a multidirectional spillover among other commodities. [ABSTRACT FROM AUTHOR]

Novel Coronavirus (COVID-19) has prominently exaggerated the stock markets of the world. It has distraught the financial and economic constancy of the globe. The study scrutinized the non-linear behavior of well-known Chinese and Pakistani stock markets, i.e. the Shanghai Composite Index (SSEC) and the Karachi Stock Exchange (KSE-100 index). The analysis utilized the VAR-DCC-MEGARCH model to determine the returns transmission and volatility spillover pattern of these markets during the standard and COVID-19 era. These results inveterate, during normal circumstances, returns generated in the financial markets of Pakistan expressively control the return movements of SSEC. However, control of Chinese stock markets on Pakistan's stock markets in terms of returns remained insignificant. The research evaluated that volatility spillover between the KSE-100 index and SSEC was insignificant during the stable periods. Nonetheless, the statistics of volatility spillovers during the pandemic era confirmed that instability in the SSEC portentously upsurges the uncertainty of the KSE-100 index. Besides, the study reported a significant leverage effect for both markets during the pandemic era. The study revealed that SSEC is the best resort for Pakistani investors to diversify financial risk. [ABSTRACT FROM AUTHOR]

Fluctuations in the oil market can significantly influence various sectors of the economy, such as the stock markets of countries that rely heavily on oil revenues. Oil prices are one of the key influential external factors affecting the stock exchange index of oil-dependent Iran. This paper investigates the spillover effects of oil prices on Iran's stock exchange index weekly from March 2009 to March 2020. Using a time-series wavelet decomposition approach, a series of OPEC oil prices and Iran's total stock market index were decomposed into various time scales (4 levels) to analyze oil market spillover into the stock market using the multivariate GARCH TBEKK model. The results confirmed that volatility spillover from the oil to the stock market occurred in all the time scales (short, medium, and long term). However, the spillover in the long term is more pronounced than over the short, demonstrating that stock market volatility is strongly influenced by long-term exogenous oil price fluctuations. Hence, oil market shocks are one of the influential factors affecting stock market turbulence in Iran. [ABSTRACT FROM AUTHOR]

This study clarifies how risks spread across economic sectors and indicates the sectors that are the most affected to help investors with asset allocation and to support them in risk management. Although the Japanese stock market is one of the relatively large global stock markets, no studies have explored volatility spillovers among its sectors. Using the forecast error variance decomposition of the vector autoregressive model, this study examines the volatility spillovers among sectors classified on the Tokyo Stock Exchange. Our findings show that the pattern of volatility spillovers across sectors in the Japanese stock market differs between a few years preceding the coronavirus disease 2019 (pre-COVID-19), from 2014 to 2019, and during the COVID-19 period, in 2020. Although the energy resources and bank sectors are risk receivers in the pre-COVID-19 period, these sectors are risk transmitters during the COVID-19 period. We also find that volatility spillovers in the Japanese stock market are mainly driven by negative realized semivariance. These results are useful for asset allocation and risk management. [ABSTRACT FROM AUTHOR]

South Africa is a major commodity exporter, yet it is not clear what impact volatility in commodity prices has on the volatility of its currency. In this study, we examine whether a comprehensive sample of commodities (metals, grains and energy) transmit (or receive) volatility spillovers to (from) the rand exchange rate against the United States dollar for the period January 2000 to May 2022. This study uses the dynamic connectedness and volatility spillover approach of Diebold and Yilmaz (2012, 2014) and Gabauer (2020). Our findings highlight the rand as a net receiver of volatility from almost every commodity examined, with silver and palladium exhibiting the strongest volatility spillover onto the rand. From a transmission perspective, there is some evidence that the rand can be considered a commodity currency for metal exports but there may also be other channels to explain the impact of these commodities on the currency. The results have important implications for policymakers, currency traders and hedgers in commodity markets. [ABSTRACT FROM AUTHOR]

In the financial markets, asset returns exhibit collective dynamics masking individual impacts on the rest of the market. Hence, it is still an open problem to identify how shocks originating from one particular asset create spillover effects across other assets. The problem is more acute when there is a large number of simultaneously traded assets, making the identification of which asset affects which other assets even more difficult. In this paper, we construct a network of the conditional volatility series estimated from asset returns and estimate a many-dimensional VAR model with unique identification criteria based on the network topology. Because of the interlinkages across stocks, volatility shock to a particular asset propagates through the network creating a ripple effect. Our method allows us to find the exact path the ripple effect follows on the whole network of assets. [ABSTRACT FROM AUTHOR]

Orientation: This study investigated the relationship between the equity markets and foreign exchange markets in Brazil, Russia, India, China and South Africa (BRICS). Research purpose: This study examined the financial connectedness through volatility spillovers and co-movements among equity and foreign exchange markets in the BRICS countries to better understand market interdependencies. Motivation for the study: The literature mainly focused on volatility transmission from developed countries. Research approach: This research, used the Diebold and Yilmaz spillover index approach (DY index). The DY index is based on variance decompositions (VD) and impulse response functions that use a vector autoregressive (VAR) modelling framework. The study period was from 02 January 1997 to 31 December 2018. Main findings: Shocks from the equity markets dominate the foreign exchange markets, while foreign exchange markets dominate their equity markets at an individual level. There are interdependencies between BRICS equity markets and foreign exchange markets, except for China, whose markets are relatively isolated from other BRICS markets. Brazil is the largest contributor of volatility spillovers to other BRICS markets. The South African rand is the most integrated within BRICS. Practical implications: Foreign exchange markets provided better diversification opportunities. Significant increases in volatility spillovers associated with turmoil periods in domestic and global markets provide evidence for contagion effects in BRICS markets. Contribution: The current account (flow-oriented model) is crucial in exchange rate determination at the individual country level. In contrast, the capital account (stock-oriented model) is a significant factor in exchange rate determinations at an aggregate level.

This study examines how the COVID-19 pandemic crisis affects the interactions between the stock, oil, gold, currency, and cryptocurrency markets. The impacts of the COVID-19 pandemic crisis on the optimal asset allocation and optimal hedged strategy are also discussed. Empirical results show that the volatility spillover significantly exists in most of the ten paired markets whereas the return spillover and correlation are significant only for the few paired markets. Moreover, the impact of the COVID-19 pandemic on the return spillover is the greatest followed by the correlation whereas the volatility spillover is not affected by the COVID-19 pandemic. Furthermore, the Quantitative easing (QE) implemented after the COVID-19 pandemic crisis increases the risk-adjusted return for each asset and minimum variance portfolio (MVP) and raises the correlation between two assets. In addition, most of the pairs of assets are not suitable to hedge each other except for a few pairs of assets. Regarding these few pairs of assets, the optimal hedge asset with the fewer hedge cost is accompanied by less risk reduction and vice versa. Finally, the investors should choose the euro to construct a portfolio to achieve risk diversification and to hedge gold or WTI to get the risk reduction. The above findings can help investors and fund managers make a useful investment strategy, optimal asset allocation, and effective hedged strategy. For example, the investors can use the volatility of one market to predict the volatility of another market and they can take a long position during the post-COVID-19 period but they should withdraw capital from the market when the QE tapering is executed.JEL classificationC52; C53; G15.

Financial markets are widely believed to be complex systems where interdependencies exist among individual entities in the system enabling the risk spillover effect. The detrended cross-correlation analysis (DCCA) has found wide applications in examining the comovement of fluctuations among financial time series. However, to what extent can such cross-correlation represent the spillover effect is still unknown. This article constructs the DCCA network of commodity future markets and explores its proximity to the volatility spillover network. Results show a moderate agreement between the two networks. Centrality measures applied to the DCCA networks are able to identify key commodity futures that are transmitting or receiving risk spillovers. The evolution of the DCCA network reveals a significant change in the network structure during the COVID-19 pandemic in comparison to that of the pre- and post-pandemic periods. The pandemic made the commodity future markets more interconnected leading to a shorter diameter for the network. The intensified connections happen mostly between commodities from different categories. Accordingly, cross-category risk spillovers are more likely to happen during the pandemic. The analysis enriches the applications of the DCCA approach and provides useful insights into understanding the risk dynamics in commodity future markets.

The main purpose of the study is to find out the hedging capabilities between alternative assets (Gold, Crude oil, Currencies, MSCI Global, and Mutual Funds) and stock returns of Pakistan Stock Exchange (PSX). ARCH (1,1) and and GARCH (1,1) models are applied to determine the mean and spillover effect between alternative assets returns and PSX index returns. The results of the study reveal that volatility spillover exists in all alternative investments except MSCI Global Index because MSCI indicates insignificant results. Therofre, it is better opportunity for fund managers to invest in MSCI Global or Emerging Index as it will provide more hedging opportunities

The paper is an attempt to assess the Indian agricultural commodity futures market in terms of price discovery, hedging efficiency, and volatility. Cointegration test, Granger causality test, and vector error correction (VEC) model, ordinary least squares (OLS) regression, exponential generalised autoregressive conditional heteroskedasticity (EGARCH) model, value-at- risk (VaR) model are employed to achieve the objectives of the study. It is observed that the spot market leads the futures market. The lead-lag relationship varies from commodity to commodity. Additionally, downside risk exists in both the markets, and volatility is transmitted from the spot market to the futures market. The agricultural commodity futures market is found to lack hedging efficiency.

This paper examines the effects of the Standard and Poor’s 500 (SP500) stock index crash during the global financial crisis and the COVID-19 pandemic periods on the South African top sector indices (basic materials, consumer goods, consumer services, financials, healthcare, industrials, technology, and telecommunication). The results of a copula-based BEKK-GARCH approach technique demonstrate the existence of price and volatility spillover during times of stock crashes. We discover that during a stock crisis, strong shocks and higher volatility spillover effects from the United States (U.S.) SP500 index to the top sector indices of the South African Johannesburg Stock Exchange (JSE) markets are more significant. However, there is no integrated economy, as the results did not show any spillover effects from South Africa to U.S. markets. Furthermore, the Gumbel copulas have higher dependence parameters, implying that extreme co-movements occur in the upper tails, suggesting the possibility of a large transmission of shocks from the SP500 to the eight top sector indices of the JSE and showing an asymmetric dependence between these markets. This result is important for investors willing to invest in the South African sector of equity markets to develop hedging strategies to prevent risk spillover from developed markets.

Amidst increasing interest from investors and scholars in the emerging Metaverse market, this paper marks a pioneering attempt to investigate the volatility connections between the Metaverse stock index and traditional financial markets such as Gold, Crude Oil, the Volatility Index, Bitcoin, and the Nasdaq. Utilizing a novel Quantile Vector Autoregressive (QVAR) model, the study assesses the transmission of shocks between the Metaverse market and its counterparts during bearish, normal, and bullish market conditions. The results highlight a significant increase in connectivity during extreme conditions compared to median levels. Notably, the Nasdaq emerges as a principal volatility transmitter to the Metaverse index, while Bitcoin shows minimal influence, suggesting that technological innovations, rather than cryptocurrencies, predominantly drive the Metaverse market. This investigation provides valuable insights for investors and policymakers, considering the nascent stage of Metaverse-related empirical research. [Display omitted] • Volatility spillover transmission from Metaverse to stock markets is investigated. • Quantile connectedness approach is employed. • Global metaverse market is a higher contributor of shocks. • NASDAQ is the leading net transmitter of spillovers. [ABSTRACT FROM AUTHOR]

Financial stocks in the industry chain interact notably because of close economic and technical relationships. Some participants pay particular attention to one industry chain and are concerned with different investment horizons. The motivation for this study is to offer more targeted information to various market participants who focus on different time scales in one industry chain from a systematic perspective by combining the GARCH-BEKK, heterogeneous network, and wavelet analysis methods. The findings are as follows: (1) For parties who prefer to take more risks to gain higher returns, scale 2 (4–8 days) is a good option, while long-term investment (32–128 days) is suitable for conservative investors. (2) In most cases, some links in the industry chain are particularly sensitive to changes in stocks in other links. (3) The influence, sensitivity, and intermediary of stocks in the industry chain on different time scales were explored, and participants could use the resulting information to monitor the market or select stocks. (4) The structures, key players, and industry chain attributes of the main transmission paths differ on multi-time scales. Risk transmission can be controlled by intercepting important spillover relations within the paths. [ABSTRACT FROM AUTHOR]

Economic cooperation of countries across the world has led to the integration of stock and commodities markets. The group of seven countries (G7) represents the world's most industrialised and developed economies. In an integrated market, understanding the price discovery mechanism and volatility spillover across markets is crucial for traders, investors and other stakeholders. This paper investigates the return dynamics and volatility Spillover among the stock markets of G7 countries, oil and gold. We apply VAR and GARCH to examine the relationship between the returns and the transmission of volatility between commodities and stock markets. The research is based on the major stock indices of G7 countries for the years between 2009 and 2018. Oil and gold are taken as a proxy for the commodities market. This study begins by examining the cointegration of the stock and commodities market using the Johansen cointegration test. Stochastic volatility models are used to estimate the volatility and its spillover effect. We estimate the volatility spillover index using variance decomposition. The results indicate the presence of an asymmetric volatility spillover effect between the stock and commodities market. The outcome of the study would facilitate the investors and portfolio managers to understand the return dynamics and volatility spillover effect, which is a prerequisite for an investment decision. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the mean and volatility spillover between the price of green bonds and the price of renewable energy stocks using daily price series from 02/11/2011 to 31/08/2021. The unrestricted trivariate VAR-BEKK-GARCH model is employed to examine potential causality, mean, and volatility spillover effects from the green bond market to the renewable energy stock market and vice-versa. The results from the VAR-BEKK-GARCH model indicate that there exists a uni-directional Granger causality from renewable energy stock prices to green bond prices. While the price of green bonds is positively influenced by its own lagged values and the lagged values of renewable energy stock prices, only the past price value of renewable energy stocks has a positive effect on the current price value. We identified a uni-directional volatility spillover from renewable energy stock prices to green bond prices. However, there was no shock spillover from both sides of the market. This research shows that investors in the green bond market should always consider information from the renewable energy stock market because of the causal link between renewable energy stocks and green bonds. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the impact of Brexit on the dependence between European financial markets. We use the Diebold and Yilmaz (2009, 2012) approach to better map the relationship between the three main European markets and we propose an Optimal portfolio weighting to gain insights into the portfolio design dynamics in the period between 2013 and 2019, in particular any changes due to uncertainty surrounding Brexit. First, the findings show that between September 2015 and September 2016, the high level of volatility and spillover confirms the strong degree of market integration, with uncertainty surrounding the referendum outcome having a clear impact on the three main European markets. Second, the direction of spillover in the pre-Brexit period was from the UK market to the French and German markets in anticipation of uncertainty regarding the outcome of the referendum and the period immediately following it. Third, only the conditional correlation between the pair (CAC40–FTSE100) is characterized by an asymmetric effect. [ABSTRACT FROM AUTHOR]

Credit default swaps (CDS) are an important indicator of country risks. The study was carried out with daily data for 12.04.2013-03.12.2020. The aim of the study is to test the interaction between the changes in Turkey's CDS premiums and the BIST 100 index, exchange rates, and bond rates. The findings obtained aim to make recommendations to policymakers and investors in terms of risk monitoring, risk management, and investment portfolio. The interaction between CDS and BIST 100 index, exchange rates, and bond interest rates was analyzed via cDCC-EGARCH and causality in variance. As a result of the analysis, it has been seen that the effect of shocks created by increases for CDS, USD/TL, EU/TL, and bond interest series is more and more significant than shocks created by decreases. According to the results of causality analysis in variance, a unidirectional causality relationship was found from exchange rates and interest rates to CDS premiums. A causality relationship was determined from CDS premiums to the BIST 100 index. It is possible to predict the volatility in CDS premiums from the first lag by monitoring exchange rates and bond yields volatility. The results show that if the stability in the exchange rate level in Turkey is ensured, the CDS premiums can be kept in the appropriate range, and the borrowing costs can be reduced. [ABSTRACT FROM AUTHOR]

Investment in Green energy is becoming a popular alternative asset class for investors, primarily due to its environment-friendly attributes. However, there is a dire need for subjective evaluation of this emerging asset class based on the risk-return dynamics to which investors are exposed. To respond to this call, in this study, we conduct this evaluation utilizing a unique and rich data set consisting of daily prices of exchange-traded funds (ETFs) established on different asset classes. We use Vector autoregression and Baba-Engle-Kraft-Kroner parameterization of multivariate GARCH models and assess the relative strength of return and volatility spillovers from the Green and Grey energy markets. Our results reveal the return shocks originated in the Green energy market and transmitted to other markets are more pronounced. It is also observed that the potential to earn high returns and the weak correlation of Green energy ETFs with the traditional asset classes are the crucial factors helpful in inviting attention and investment of investors after 2015. Although our results further suggest that the role of Grey energy is diminishing, as shown by the Impulse response functions and the coefficients of multivariate ARCH and GARCH. Nonetheless, for some asset classes, e.g., Bonds, the volatility spillovers that originated in the Grey energy market are still prominent and robust. [ABSTRACT FROM AUTHOR]

We examine the relationship between oil prices, foreign exchange (FX) swaps and local interbank offered rates in the six Gulf Cooperation Council (GCC) countries. We also investigate the potential hedging and diversification benefits from adding oil positions to portfolios containing GCC FX swaps or interest rate positions. Our findings confirm that oil predicts, and in some cases causes, movements in the various GCC FX swaps and interbank offered rates. We also find that the Saudi FX swap market has the highest volatility spillover from the oil market compared to other markets in the region. Furthermore, our analysis shows a significant change in liquidity conditions in the GCC FX swap markets following a sudden shift in oil prices. Lastly, we document the presence of significant risk reduction benefits from adding oil exposure to portfolios of GCC FX swaps or interest rates with risk going down by at least half in the case of the GCC FX swaps. [ABSTRACT FROM AUTHOR]

The objective of this study is to use the South African financial markets (Johannesburg Stock Exchange or JSE and USD/ZAR) as a case study to understand the volatility spillover dynamics of Bitcoin as a digital asset. Methodologically, the study applies the exponential generalized autoregressive conditional heteroskedastic (EGARCH) model, followed by a robustness check by applying the time-varying conditional correlation multivariate GARCH (VCC-MGARCH) model. The study utilizes the data set for the period 2011 to 2019, a period before the COVID-19 pandemic. The research outcome revealed three interesting observations. First, Bitcoin and the South African stock market are independent of each other. Second, there is a bidirectional shock transmission between Bitcoin and USD/ZAR in the mean returns only, but not variance. Lastly, results confirm the existence of a bidirectional volatility spillover in both the mean and variance between the JSE stock market and the USD/ZAR market. The study outcome should enlighten investors who may want to consider Bitcoin as a diversifier in their investment and portfolio strategies. [ABSTRACT FROM AUTHOR]

The aim of this research is to test the volatility spillover between the stock values of the major liner shipping companies in the world and the freight indices measuring the freight revenues in the container market. The dataset in the study consists of 9 stock values of the top 10 biggest liner companies in 2018 and 3 container freight indices on weekly basis covering the period between 05.11.2010 and 06.07.2018. Volatility spillovers have been determined to some companies' stock values from some container freight indices, and the most influential freight index has been determined as New ConTex. Moreover, some volatility spillovers from some companies' stock values to freight indices have been also determined. These results suggest that some stock investors position their portfolios in the market according to the flow of information from freight indices while some investors position by following macro variables.

This study investigates the impact of macroeconomic instabilities on returns volatility spillover that is transmitted from the global to the Islamic equity market. The economic factors examined are the exchange rate, inflation rate, interest rate, and production growth. To achieve the purpose of the study, we utilize three analysis tools: a GARCH(p,q) model to derive values of volatility for all variables; an asymmetry dynamic conditional correlation (ADCC) model to produce a measure of volatility spillover as the dependent variable; and a panel data regression technique to assess the causality significance of macroeconomic factors to volatility spillover. This study is the first which expands such approaches. We observe monthly data of world and Islamic market indices, exchange rates, consumer price indices, interest rates, and industrial production indices. The data, which range from May 2002 to February 2019, are taken from the world market, and twenty-three economies, which consist of fourteen developed and nine emerging markets that have Islamic stock indices. In several sections, we provide important additional analysis for five stock markets in Central European economies, which are compared to the others. The finding suggests that the presence of volatility spillover on the Islamic markets that originates from the global market is affected by the internal instabilities of macroeconomic factors, except for industrial production instability for developed markets, including Central European markets. An implication of the study is that regulators should anticipate and prevent adverse consequences of volatility spillover by arranging their internal economic policy to control inflation rates, interest rates, and industrial production growth, as well as exchange rate flexibility. Moreover, market practitioners should include both global market volatility and macroeconomic instabilities in their prediction to create minimum risk.

Purpose – This article examines volatility spillovers, cross-market correlation, and comovements between selected developed and former communist emerging stock markets in the European Union. Modelling the behavioural dynamics of European stock markets represents a vital topic in a fascinating context, but also a current challenge of great interest. Research Methodology – We propose to estimate and model volatility using GARCH family models for selected European markets. We aim to explore volatility movement, presence of leverage effect/ asymmetry in selected financial markets. Findings – The econometric approach includes GARCH (1, 1) models for the sample period from 1, January 2000 to 12, July 2018. The empirical results revealed that exists a significant presence of volatility clustering in all selected financial markets except Poland and Croatia. The empirical analysis also indicates that both recent and past news generate a considerable impact on present volatility. Research limitations – Our empirical study has certain limitations regarding the relatively small number of only eight stock markets. Practical implications – It can provide a useful perspective for researchers, academics, investors, investment managers, decision-makers, and scientists. Originality/Value – The empirical analysis is focused on 8 European stock markets, which are classified as developed (Spain, UK, Germany, and France) and emerging (Poland, Hungary, Croatia, and Romania).

In agricultural economics, fluctuations in food prices and the factors affecting these fluctuations have always been an important research topic. From production to delivery to consumers, the supply chain of agricultural products has a dynamic structure with continuous changes. In this dynamic process, analyzing the intensive use of energy at each stage has gained more importance with its deepening effects in comparison to the past. This study will empirically explore the volatility spillovers between energy price index and fruit-vegetables price index in the period of 2007-2020 in Turkey using the Kanas and Diebold-Yilmaz approaches. According to the results obtained from the Kanas approach in the study, it has been observed that there is a statistically significant volatility spillover from the energy price index to the vegetable price index, whereas there is no statistically significant volatility spillover to the fruit price index. This finding was supported by the results obtained from the Diebold-Yilmaz approach showing that there is a volatility spillover of 13.52% to the vegetable price index and 0.86% to the fruit price index from the energy price index.

The outbreak of the COVID-19 epidemic intensified the volatility of commodity markets (the energy and precious metals markets), which created a significant negative impact on the volatility spillovers among these markets. It may also have triggered a new volatility risk contagion. In this paper, we introduce the DCC-GARCH-CONNECTEDNESS approach to explore the volatility spillover level and multi-level spillover structure characteristics among the commodity markets before and during the COVID-19 epidemic in order to clarify the new volatility risk contagion patterns across the markets. The results implied several conclusions. (i) The COVID-19 epidemic has significantly improved the total volatility spillover level of the energy and precious metals markets and has enhanced the risk connectivity among the markets. (ii) The COVID-19 epidemic has amplified the volatility of the crude oil market, making it the main volatility spillover market, namely the source of volatility risk contagion. (iii) The COVID-19 epidemic outbreak enhanced the external risk absorption capacity of the natural gas and silver markets, and the absorption level of the external volatility spillover improved significantly. Furthermore, the risk absorption capacity of the gold market weakened, while the gold market has remained the endpoint of external volatility risk during the epidemic and has acted as a risk stabilizer. (iv) The volatility spillover among markets has clear time-varying characteristics and a positive connectedness with the severity of the COVID-19 epidemic. As the severity of the COVID-19 epidemic increases, the volatility risk connectivity among the markets rapidly increases.

This study utilizes a bivariate BEKK-EGARCH model with the setting of a structural break to investigate whether the interactions between stock indices in emerging and developed markets are different in terms of region, emerging stock indices, and subperiod. Then, this study investigated how the results of interactions vary with geographical location, emerging stock indices, and subperiod. Empirical results show that the interactions between emerging and developed markets indeed vary with geographical location and emerging stock indices, but are almost the same in the two subperiods. For example, for the paired stock indices in 'Asia-America' and 'Asia-Europe', or related to 'XU100', 'SSE' and 'BSE', the developed market mainly spills into the emerging market in terms of return and volatility. The findings from these empirical results can help investors and fund managers undertake different investment strategies in different regions and subperiods, and make effective investments. [ABSTRACT FROM AUTHOR]

After China's stock market crash in 2015, the Chinese government imposed a series of trading restrictions on the stock index futures market. This paper examines how the relative informational role of China's IH stock index futures and the SGX FTSE China A50 index futures varies when market trading mechanisms are subject to these major changes. We find that imposing the trading restrictions on IH futures substantially undermines their role in price discovery and volatility spillover, and renders them more susceptible to the fluctuations of A50 futures. Importantly, even after the trading restrictions are greatly eased at a later date, the importance of IH futures in price discovery and volatility spillover relative to that of A50 futures remains at a level much lower than before. Changes in liquidity and trading volumes imply that imposing the trading restrictions on IH futures drives investors to flee the IH futures market, but relaxing these restrictions is not able to attract investors back, making it difficult for IH futures to resume its important role in information transmission. [ABSTRACT FROM AUTHOR]

Volatility spillovers have increased due to globalization, the development of communication tools and the increasing relations between financial markets. In this study, it is aimed to investigate the volatility spillovers among the main markets. The study was conducted with the Diebold and Yılmaz (2012) volatility spillover index. MSCI world index, US 2-year government bond interest rates, dollar index, ounce of gold, brent oil and bitcoin are used to represent the main markets. The sample was formed as the period of January 2, 2015-June 29, 2021 and was examined that the volatility obtained from the daily data of this period. It has been determined that the volatility spillover index among the main markets was 30,9%, the interest rate and MSCI world index are the volatility emitters, whereas the dollar index, gold, oil and bitcoin are the volatility receiver in this study. Furthermore, it has been seen that the interest rate is the important volatility emitter in the main markets, and the volatility relationship of bitcoin with the main markets is weak. In addition to these results, it was determined that the volatility spillovers between the main markets increased during the COVID- 19 process. The results obtained are usable in terms of portfolio management, risk management, investments and economy managements. [ABSTRACT FROM AUTHOR]

It is important to understand the relationship between the spot markets and the futures markets, which were developed to serve the hedging purposes of market participants, in order to play an effective role in risk management. In this study, it is aimed to investigate the relations between spot and futures markets. Within the scope of the study, BIST-30 index futures contracts, Dollar-TL futures contracts and related spot markets are discussed. In the study, which was carried out using daily logarithmic returns for the period of August 5, 2013-April 28, 2021, the lead-lag relationships between spot and futures markets and the price discovery function as well as volatility spillovers were tried to be revealed. Thus, it is aimed to shed light on which market the new information is priced in first, and therefore which market has the higher efficiency. Findings obtained from the VAR-BEKK-GARCH and VAR-DCC-GARCH models reveal the leadership of the spot market in the index and the presence of bidirectional interaction in the foreign exchange markets. Accordingly, it is understood that index futures contracts process new information more slowly than stock markets and that the spot market can predict the futures market. Results also show that dynamic conditional correlations between markets are significant and the effect of positive information on volatility is stronger than the negative information. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, which affected global markets in the short term, and the fear and anxiety created by the pandemic in the economy and financial markets, caused volatility in asset prices and financial markets. In this study, in the mentioned period; It investigates the volatility spillover between the fragile five markets consisting of Indonesia, Turkey, Brazil, India and South Africa, and the markets of developed countries consisting of France, USA, Germany, England and Japan. In the study, the data of the countries for the period 5 January 2015 - 28 May 2021 were estimated by the spillover index method of Diebold and Yılmaz (2012). The estimation results show that the volatility spillover has increased rapidly since March 2020, when COVID-19 was declared a global pandemic by the World Health Organization, and that the spillover returned to the pre- pandemic period from April 2021, when vaccines became widespread in countries. In the study, it was understood that the volatility spillover in the developed country markets is higher than the volatility spillover in the fragile five markets. In addition, BOVESPA (Brazil) and FTSE100 (UK) markets are the highest emitters of net volatility, while JKSE (Indonesia) and NIKKEI225 (Japan) markets are the highest volatility re [ABSTRACT FROM AUTHOR]

Prices of oil and other commodities have fluctuated wildly since the outbreak of the COVID-19 pandemic. It is crucial to explore the causes of price fluctuations and understand the source and path of risk contagion to better mitigate systemic risk and maintain economic stability. The paper adopts the method of network topology to examine the path of risk contagion between China's and foreign commodities, focusing on the dynamic evolution and transmission mechanism of risk contagion during the pandemic. This research found that among China's commodities, energy, grain, and textiles are net recipients of risk contagion, while chemical products and metals are net risk exporters. Among international commodities, industries have positive risk spillover effects on metals and textiles. During the first phase of the pandemic, China's commodities were the main exporters of risk contagion. However, international industries and metals became the main risk exporters and exerted risk spillover on China's commodities in the second phase of the pandemic. Moreover, based on total volatility spillover index of commodities, the risk contagion among the commodities follows three paths: "interest rate → commodities → money supply", "China's economic expectation → commodities → foreign economic expectation", and "commodities → consumer confidence". [ABSTRACT FROM AUTHOR]

Recent evidence suggests that ignoring structural breaks in volatility in financial asset returns can result in overestimation of volatility spillover among markets. This paper examines volatility spillover among major US equity sectors (i.e. Financial, Technology, Energy, Health, Consumer and Industrial) with bivariate GARCH models utilizing daily data from April 2006 to March 2021 after adjusting for volatility breaks. I find significantly less volatility spillover between sector returns after adjusting for detected volatility breaks into a bivariate GARCH model. I also show that after adding volatility breaks into a model the estimated hedge ratios change significantly and show considerably less variability over time, which can result in substantial savings in portfolio rebalancing costs. [ABSTRACT FROM AUTHOR]

This paper utilizes two methods to uncover the causality dynamic between the three leading cryptocurrencies: Bitcoin, Litecoin, Ripple, and nine major foreign currency markets. Firstly, we implement the technique of Diebold–Yilmaz to compute the spillover index between cryptocurrencies and currency markets. We find a significant return spillover effect between Bitcoin and Litecoin in the first three quarters of 2017. Still, the return spillover is merely meaningful in the first three quarters of 2015 for Ripple. However, the total volatility spillover index in the system decreases in the fourth quarter of 2017. Secondly, we apply the Bayesian graphical structural vector, autoregressive estimations, and find that the current level of Bitcoin depends only on the previous level of the Chinese Yuan. The current level of Ripple strongly depends on the prior levels of Bitcoin, followed by Litecoin. The current level of Litecoin strongly depends on the previous level of Ripple, followed by the Chinese Yuan. These results indicate that there is a significant causal relationship among cryptocurrencies. However, except for the Chinese Yuan, major traditional currencies do not significantly affect cryptocurrencies. [ABSTRACT FROM AUTHOR]

Volatility in financial markets is a highly explored area of research for the last few decades. Possible reasons for high concentration on the markets are its unexplained and unexplored sources. The present study aims to check certain macroeconomic variables as determinants of financial markets (stock market and exchange rate) volatility. It also aims to analyse the contribution of the volatility of one financial market to the volatility of another financial market before and after the financial crises. The analysis is conducted using two types of data sets from 27 European countries. The study employed A.R. (k)-EGARCH (p, q) models to measure financial markets volatility. The study finds no significant interlink effects among volatilities of stock market returns and volatility of exchange rate returns after the financial crises. However, the increase in volatility in one market caused an increase in the other market’s volatility before the financial crises. Further, results also revealed that macroeconomic variables affect volatilities in these markets differently before and after the financial crises. The study recommends that the macroeconomic policies for stability in these markets cannot coincide as they differ in their impacts in different markets.