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Understanding the transmission of volatility across markets is essential for managing risk and financial stability, especially under crisis periods during which an extreme event occurring in one market is easily transmitted to another market. To gain such an understanding and enrich the related literature, we examine in this article the system of volatility spillovers across various equity markets and asset classes using a quantile‐based approach, allowing us to capture spillovers under normal and high volatility states. The sample period is 16 March 2011–10 November 2020 and the employed dataset comprises 12 implied volatility indices representing a forward‐looking measure of uncertainty of global equities, strategic commodities and the US Treasury bond market. The results show that the identity of transmitters and receivers of volatility shocks differ between normal and high volatility states. The US stock market is at the centre of volatility spillovers in the normal volatility state. European and Chinese stock markets and strategic commodities (e.g. crude oil and gold) become major volatility transmitters in the high volatility state, after acting as volatility receivers during normal periods. Furthermore, we study the drivers of implied volatility spillovers using regression models and find that US Default spread contributes to the total volatility spillover index in both volatility states, whereas TED spread plays a significant role in the normal volatility state. As for the role of short rate and risk aversion, it is significant in the high volatility state. These findings matter to the decision‐making process of risk managers and policymakers. [ABSTRACT FROM AUTHOR]

Academic research relies heavily on exogenous drivers to improve the forecasting accuracy of Bitcoin volatility. The present study provides additional insight into the role of both macroeconomic and technical indicators in forecasting the realized volatility of Bitcoin. Using 17 famous macroeconomic variables and 18 technical indicators between December 2011 and April 2021, the results reveal that the shrinkage methods, including elastic net and LASSO, can powerfully extract predictive information from macroeconomic and technical indicators. We further investigate the forecasting power of macroeconomic factors and technical indicators in terms of variable selection, business cycle, and volatility levels, and the results show strong evidence that the macroeconomic indicators (namely, S&P 500 realized volatility, global real economic activity index, and trade‐weighted USD index return) are the most frequently selected by shrinkage method, suggesting that their ability to forecast Bitcoin volatility is stronger than that of technical indicators. However, technical indicators are more powerful in forecasting Bitcoin volatility during the low volatility state. [ABSTRACT FROM AUTHOR]

The authors of this study examine the impact of geopolitical risk on inbound tourism in the BRICS (Brazil, Russia, India, China, and South Africa) countries. To this end, they employ second‐generation panel data methods, augmented mean group estimators, and panel quantile regressions. The results of the augmented mean group estimators show that geopolitical risk negatively impacts inbound tourism. However, the results of the panel quantile regressions reveal that the impact is heterogeneous across the distribution. At low quantiles, the impact of geopolitical risk on inbound tourism is marginal, whereas the impact is strong at high quantiles. The study has some policy implications for tourism development. [ABSTRACT FROM AUTHOR]

Environmental degradation, global warming, and climate change have become eminent risk factors posing a serious threat to global security. One of the reasons behind those risk factors is greenhouse gases (GHGs) that are mainly consisted of carbon dioxide (CO2) emissions. Previous studies try to discern the economic and noneconomic determinants of CO2 emissions to impede environmental degradation. However, the impact of economic policy uncertainty (EPU) on CO2 emissions remains largely understudied. To address this gap, this study examines the impact of EPU on CO2 emissions in the US using a novel methodology of bootstrap ARDL approach that allows for discerning heterogeneity in the impacts between the short run and the long run. The results indicate that EPU intensifies CO2 emissions in short run, suggesting that high EPU is responsible for environmental degradation in the short run. Conversely, in long run, EPU plunges CO2 emissions, implying that high EPU ameliorates environmental quality in the long run. Such evidence on trade‐off between EPU and CO2 emissions implies that policymakers should adopt measures to reduce EPU in the short run to improve environmental quality. In long run, if policymakers seek to simultaneously control EPU and CO2 emissions, they should search for alternate ways (e.g., renewable energy consumption) to mitigate CO2. [ABSTRACT FROM AUTHOR]

In this paper, we analyze contagion over the daily period of January 1, 1998 to September 13, 2018 between Real Estate Investments Trusts (REITs) and the equity markets of 19 countries, which are at their different stages of development in terms of the REITs market. For our purpose, we use the local Gaussian correlation approach during the dot‐com, global financial, European sovereign debt crises and the more recent period involving the Brexit in the UK. The employed method not only avoids the bias of the conditional correlation, but also describes any nonlinear structure in dependence and the deviation from global normality. In general, we find strong evidence of nonlinear contagion between equities and REITs of not only matured and established markets, but also in economies with an emerging REITs sector, especially during the global financial and sovereign debt crises. Further, when we considered contagion across REITs of the US and the other countries, and between US REITs and equities of the remaining 18 countries, a similar pattern emerges. Our results have important implications for investors and policymakers alike. [ABSTRACT FROM AUTHOR]

This paper subjects six alternative indicators of global economic activity to empirically examine their relative predictive powers in the forecast of crude oil market volatility. GARCH‐MIDAS approach is constructed to accommodate all the relevant series at their available data frequencies, thereby circumventing information loss and any associated bias. We find evidence in support of global economic activity as a good predictor of energy market volatility. Our forecast evaluation of the various indicators places a higher weight on the newly developed indicator of global economic activity which is based on a set of 16 variables covering multiple dimensions of the global economy, whereas other indicators do not seem to capture. Furthermore, we find that accounting for any inherent asymmetry in the global economic activity proxies improves the forecast accuracy of the GARCH‐MIDAS‐X model for oil volatility. The results leading to these conclusions are robust to multiple forecast horizons and consistent across alternative energy sources. [ABSTRACT FROM AUTHOR]

We compare the weak/strong hedging abilities of three alternative assets, namely bitcoin, gold and US VIX futures, against the downside movements in BRICS stock market indices. Results from the cross‐quantilogram approach indicate that bitcoin and gold are weak hedges. Analysis from the recursive sampling shows that each of bitcoin, gold and VIX futures has a time‐varying hedging role in some BRICS countries, which has been shaped by the COVID‐19 outbreak. Results from the conditional diversification benefits show appealing roles for the three alternative assets for investors in BRICS stock markets. However, gold appears to have higher and more stable diversification benefits in China, especially during the COVID‐19 outbreak. Conversely, VIX futures offer higher diversification benefits in Brazil, Russia, India and South Africa during the abrupt of the COVID‐19 outbreak. [ABSTRACT FROM AUTHOR]

The use of ethanol as a vehicle fuel has reduced greenhouse gas emissions significantly. The introduction of ethanol has also led to a decrease in crude oil prices. Considering the economic and environmental significance of the biofuel markets, a strand of literature investigates the price and volatility dynamics of US ethanol prices. In this paper, in contrast to previous studies, we investigate whether information on structural breaks plays an important role in predicting US ethanol market volatility. Our findings reveal that generalized autoregressive conditional heteroskedasticity (GARCH) models incorporating these breaks improve the prediction of US ethanol market volatility. Furthermore, the persistence of volatility tends to decline when structural breaks are included in the GARCH models. We further note that the influence of good and bad news is properly assessed under such breaks. Our results suggest that ignoring such breaks could mislead the risk assessment procedure for the US biofuel industry. © 2020 Society of Industrial Chemistry and John Wiley & Sons Ltd [ABSTRACT FROM AUTHOR]

We contribute to the scarce literature on the oil market volatility index (OVX) by examining the presence of time‐varying jumps in OVX and by assessing the ability of OVX to predict the conditional variance of crude oil returns. Using a GARCH‐jump model, we find evidence that OVX is characterized by jump behaviour that tends to vary over time. Further analysis indicates that accounting for the jump behaviour of OVX helps improve the conditional variance forecasts of crude oil returns. Since the studied features of OVX play a crucial role in asset pricing and risk analyses, our findings have policy implications related to refining volatility prediction models and risk measures. [ABSTRACT FROM AUTHOR]

This paper explores the role of business cycle proxies, measured by the output gap at the global, regional, and local levels, as potential predictors of stock market volatility in the emerging BRICS nations. We observe that the emerging BRICS nations display a rather heterogeneous pattern when it comes to the relative role of idiosyncratic factors as a predictor of stock market volatility. While domestic output gap is found to capture significant predictive information for India and China particularly, the business cycles associated with emerging economies and the world in general are strongly important for the BRIC countries and weakly for South Africa, especially in the postglobal financial crisis era. The findings suggest that despite the increase in the financial integration of world capital markets, emerging economies can still bear significant exposures to idiosyncratic risk factors, an issue of high importance for the profitability of global diversification strategies. [ABSTRACT FROM AUTHOR]

In this paper, we first estimate the monthly realised correlation, based on daily data, between stock returns of the United States (US) and Bitcoin returns. Then, we relate the realised correlation over the period October 2011 to May 2019 with a news‐based measure of the growth of trade uncertainty of the US. Our results show that the realised correlation is negatively impacted by increases in trade uncertainty, which continues to hold under alternative robustness checks, suggesting that Bitcoin can act as a hedge relative to the conventional stock market in the wake of heightened trade policy‐related uncertainties, and provide diversification benefits for investors. [ABSTRACT FROM AUTHOR]

Jumps in the price process of assets represent a sort of tail risk and are found to affect many aspects of asset pricing, volatility modelling and asset allocation. In this paper, we detect price jumps in the realised volatility series of a wide set of commodity futures and find evidence of jumpy behaviour, especially in energy and agricultural commodities. We examine whether the realised volatilities of commodity futures jump together and find evidence that cojumping is significant and generally clustered within the commodity groups, suggesting some sort of segmentation regarding the tail risk behaviour across energy, agricultural and metals commodities. Additional analysis shows that price jumps and macroeconomic news surprises tend to occur together in specific commodities such as crude oil, which confirms earlier findings about the sensitivity of crude oil to news about the economy. [ABSTRACT FROM AUTHOR]

The production of ethanol has increased globally over the last decade. It is mainly produced from corn and sugarcane, so earlier studies mainly investigated the impact of food prices on ethanol prices. Although biofuels have been brought into the energy markets to reduce the volume of carbon emissions, the links between ethanol and carbon emission markets have not been explored sufficiently in the existing literature. This study aimed to extend the literature in this field by using a GARCH‐jump process to examine whether Brazilian ethanol prices are affected by carbon emission prices. Our key findings are threefold. First, carbon emission prices affect Brazilian ethanol prices positively. Rising emission prices would therefore cause an increase in the ethanol price. Second, time‐varying jumps occur in the ethanol price index. Third, the impact of emission prices on the ethanol market is asymmetric, implying that increases and decreases in emission prices would have heterogeneous effects on ethanol price levels. Our findings have important implications for scholars, investors, and policymakers. © 2018 Society of Chemical Industry and John Wiley & Sons, Ltd [ABSTRACT FROM AUTHOR]

Motivated by the emergence of Bitcoin as a speculative financial investment, the purpose of this paper is to examine the persistence in the level and volatility of Bitcoin price, accounting for the impact of structural breaks. Using parametric and semiparametric techniques, we find strong evidence in favour of a permanency of the shocks and lack of mean reversion in the level series. We also reveal evidence of structural changes in the dynamics of Bitcoin. After accounting for the structural breaks in the level series, evidence of mean reversion is uncovered in some cases. Further analyses show evidence of a long memory in the two measures of volatility (absolute and the squared returns), whereas some cases of short memory are revealed in the squared returns series in particular. Practical implications are discussed on the inefficiency in the Bitcoin market and its importance for Bitcoin users and investors. [ABSTRACT FROM AUTHOR]

Abstract: The growing interest in biofuel as a green energy source has intensified the linkages between corn and ethanol markets, especially in the United States that represents the largest producing and exporting country for ethanol in the world. In this study, we examine the effect of corn market uncertainty on the price changes of US ethanol applying a set of GARCH‐jump models. We find that the US ethanol price changes react positively to the corn market volatility shocks after controlling for the effect of oil price uncertainty. In addition, we document that the impact of corn price volatility on the US ethanol prices appears to be asymmetric. Specifically, only the positive corn market volatility shocks are found to influence the ethanol market returns. Our findings also suggest that time‐varying jumps do exist in the ethanol market. [ABSTRACT FROM AUTHOR]