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In this paper, we contribute to the old debate on the dynamic correlation between gold and stock markets by considering a spectral approach within the framework of portfolio hedging. Specifically, we consider eight MENA stock markets (Tunisia, Egypt, Morocco, Jordan, UAE, Saudi Arabia, Qatar, and Oman) and examine the optimal composition between gold and the stock market index, with a minimum portfolio risk and a high expected return. Based on the spectral approach, we propose seven portfolio structures and evaluate them through a comparison with the conventional DCC-GARCH method and the most best 10 portfolios constructed by using wavelet approach. The main results show that the spectral-based approach outperforms the DCC-GARCH and the wavelet methods. In fact, the optimal gold-stock composition depends on the spectral density of each stock market index, where a stock market index with a stable spectral density requires more investments in gold than a stock market index with an unstable spectral density. [ABSTRACT FROM AUTHOR]

Interactions between stock and cryptocurrency markets have experienced shifts and changes in their dynamics. In this paper, we study the connection between S&P500 and Bitcoin in higher-order moments, specifically up to the fourth conditional moment, utilizing the time-scale perspective of the wavelet coherence analysis. Using data from 19 August 2011 to 14 January 2022, the results show that the co-movement between Bitcoin and S&P500 is moment-dependent and varies across time and frequency. There is very weak or even non-existent connection between the two markets before 2018. Starting 2018, but mostly 2019 onwards, the interconnections emerge. The co-movements between the volatility of Bitcoin and S&P500 intensified around the COVID-19 outbreak, especially at mid-term scales. For skewness and kurtosis, the co-movement is stronger and more significant at mid- and long-term scales. A partial-wavelet coherence analysis underlines the intermediating role of economic policy uncertainty (EPU) in provoking the Bitcoin-S&P500 nexus. These results reflect the co-movement between US stock and Bitcoin markets beyond the second moment of return distribution and across time scales, suggesting the relevance and importance of considering fat tails and return asymmetry when jointly considering US equity-Bitcoin trading or investments and the policy formulation for the sake of US market stability. [ABSTRACT FROM AUTHOR]

We study the tail dependence between crude oil and BRIC stock markets using a time-varying optimal copula (TVOC) approach. We show evidence of multiple tail dependence regimes, suggesting that simple static or dynamic copula specifications do not fully characterize the extreme dependence between oil and BRIC stock markets. The identified combinations of asymmetric and extreme positive lower tail dependence justify the application of the TVOC. Interestingly, the positive lower tail dependence between oil and stock markets and risk spillover from oil is higher for Brazil and Russia (oil exporters) than India and China (oil importers). Finally, we assess the effectiveness of hedging and measure the conditional diversification benefits of investing in oil for BRIC stock indices. Notably, the Chinese and Indian equity markets offer higher conditional diversification benefits when combined with oil in an equally weighted portfolio. [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]

Economic policy uncertainty generally tends to induce a pessimistic view of future market behaviour. Furthermore, instabilities in global oil prices have serious implications for the economies of oil exporters and importers, due to their over-dependence on crude oil for revenue and production activities, respectively, and thereby on stock market indices. Against limited empirical evidence, this study examines the spillover effects from global economic policy uncertainty (GEPU) and oil price volatility to the volatility of the stock market indices of oil exporters and importers in both developed and emerging economies. The results show that the spillover effect from GEPU to oil exporters is relatively smaller than to oil importers, for both developed and emerging countries. Conversely, the volatility spillovers from oil prices to oil exporters are relatively larger than to oil importers, for both developed and emerging countries. Specifically, the volatility spillovers from oil prices to oil exporters (importers) in emerging countries are relatively stronger compared to oil exporters (importers) in developed countries. The findings indicate that the volatility of the stock markets of emerging countries is more sensitive to global factors such as GEPU and oil price volatility, and that oil exporters and importers in emerging economies are more sensitive to oil price volatility than oil exporters and importers in developed economies, which is in line with previous studies. [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]

This study examines the dynamics of return and volatility connectedness between the rare earth stock index and the indexes of clean energy, consumer electronics, telecommunications, healthcare equipment, and aerospace & defence. Using daily data from 25 March 2010 to 25 August 2020, a quantile-based connectedness approach is applied to uncover both average and tail-based connectedness while considering the full sample period and the COVID-19 pandemic days. The results suggest that the interdependence among these indexes changes dramatically at the lower and upper quantiles, suggesting a strong influence of extreme market scenarios on both returns and volatility connectedness dynamics. Higher integration of sectoral indexes is observed during 2010–2012 and the COVID-19 pandemic period. Health care and telecommunication indexes have been consistent transmitters of return and volatility spillovers to other indexes during the full sample period. Consumer electronics and clean technology indexes switch their roles from a net receiver to a net transmitter during pandemic days. The rare earth remains on the recipient's side consistently. The findings indicate that the ongoing U.S.–China trade embargo has not impacted the return and volatility dynamics of the five sectoral indexes superseding the demand-driven dynamics for rare earth. [ABSTRACT FROM AUTHOR]

Uncovering the tail risk spillover among global financial markets helps provide a more comprehensive understanding of the information transmission in extreme market conditions such as the COVID-19 outbreak. In this paper, we examine systemic distress risk spillover between the global stock market and individual stock markets in the countries most affected by the COVID-19 pandemic. Using two important measures of tail dependence risk: conditional value at risk (CoVaR) and delta conditional VaR (Δ CoVaR), we apply the bivariate dynamic conditional correlation (DCC) conditional autoregressive heteroscedastic (GARCH) model. The empirical results reveal that bivariate systemic risk contagion between the global stock market and each individual stock market evolved during the sample period and intensified as COVID-19 spread worldwide. During the COVID-19 period, the developed markets in Europe and North America transmitted and received more marginal extreme risk to and from the entire global market than Asian stock markets. Further analysis involving the connectedness among the value at risk (VaR) series of the sampled stock market indices and the global stock index, shows a high degree of integration in the extreme downside risk of the stock market system, especially during the COVID-19 period. These findings offer practical implications for regulators, policymakers, and portfolio risk managers during the unprecedented uncertainty period provoked by the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

This study examines the safe-haven and hedging roles of gold against thirteen Asian stock markets during the COVID-19 outbreak. During the COVID-19 sub-period, gold is shown to be a strong hedge (diversifier) for the majority (minority) of Asian stock markets; it exhibits the property of a strong safe-haven in China, Indonesia, Singapore, and Vietnam, and a weak safe-haven in Pakistan and Thailand. The optimal weights of all stock-gold portfolios are lower during the COVID-19 sub-period than the pre COVID-19 sub-period, suggesting that portfolio investors should increase their investment in gold during the COVID-19 sub-period. The hedging effectiveness for most Asian stock markets is higher during the COVID-19 sub-period. Further analyses show that the hedge portfolio returns in many cases are mostly driven by gold implied volatility and inflation expectations in both sub-periods. Our findings have useful implications for market participants holding investments in Asian stocks during stressful periods. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine the extreme return spillovers among the US stock market sectors in the light of the COVID-19 outbreak. To this end, we extend the now-traditional Diebold-Yilmaz spillover index to the quantiles domain by building networks of generalized forecast error variance decomposition of a quantile vector autoregressive model specifically for extreme returns. Notably, we control for common movements by using the overall stock market index as a common factor for all sectors and uncover the effect of the COVID-19 outbreak on the dynamics of the network. The results show that the network structure and spillovers differ considerably with respect to the market state. During stable times, the network shows a nice sectoral clustering structure which, however, changes dramatically for both adverse and beneficial market conditions constituting a highly connected network structure. The pandemic period itself shows an interesting restructuring of the network as the dominant clusters become more tightly connected while the rest of the network remains well separated. The sectoral topology thus has not collapsed into a unified market during the pandemic. [ABSTRACT FROM AUTHOR]

Stock return predictability has always been one of the central themes of finance literature, given its crucial implications for investment decisions, risk management, and financial and monetary policymaking. This paper evaluates the in-sample and out-of-sample stock return predictive power of the global and Saudi geopolitical risk indices and crude oil returns in the context of six Gulf Cooperation Council (GCC) countries. Monthly data from February 2007 to December 2019 and the feasible generalized least square (FGLS) estimator for predictive modelling by Westerlund and Narayan (2012, 2015) are used. Global and Saudi GPR indices show weak evidence of in-sample predictability of excess stock returns. However, the out-of-sample forecasts show that only the global geopolitical risk index provides superior prediction in the context of Kuwaiti and Omani stock markets, compared to the historical average benchmark model. Crude oil prices are shown to be a better predictor in most cases, in both in-sample and out-of-sample forecast models The results imply that crude oil returns can be used for active prediction of GCC stock market returns, once econometric issues are accounted for. The findings remain mostly unaffected when excess risk adjusted returns are used. [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]

We examine spillover and its determinants among Eurozone sector level credit markets using time and frequency domain spillover approaches. Based on network theory and connectedness analysis, we identify the sectors that are major transmitters and receivers of spillover during normal and crisis periods. The rolling window analysis shows that short-run spillover among credit market sectors intensifies during global and Eurozone crisis periods. Further, using Bayesian model averaging, we find that overall financial conditions and stock market volatility are the main drivers of total and sector-level spillover. Our findings have important implications for policymakers and investors interested in Euro-area credit risk at the sector level. [ABSTRACT FROM AUTHOR]

This article uses dependence-switching copulas and time-varying single copulas to characterize the world oil-stock market dependence in a broad range of emerging economies, and it then conducts a regression analysis to explore the determinants of the market dependence patterns. Our results support a positive crude oil-emerging stock market link overall. The regression results show that oil return volatility, country-specific variables (i.e., stock market volatility, petroleum production growth), and US economic policy uncertainty have positive effects on the oil-stock dependence. However, a strong US economy tends to decrease the oil-stock dependence. The robustness of these findings is confirmed. [ABSTRACT FROM AUTHOR]

This study applies a non-parametric causality-in-quantiles test to examine the causal effect of geopolitical risks on return and volatility dynamics of Islamic equity and bond markets. Geopolitical risks are generally found to impact Islamic equity market volatility measures, rather than returns. However, geopolitical risks tend to predict both returns and volatility measures of Islamic bonds. Interestingly, causality, when it exists for returns and/or volatility of Islamic equities and bonds, is found to hold over entire conditional distributions of returns and volatilities, barring the extreme ends of the same. [ABSTRACT FROM AUTHOR]

This paper aims to examine short- and long-run asymmetries in the impacts of disaggregated oil price shocks on economic policy uncertainty, stock market uncertainty, treasury rates, and investor (bullish and bearish) sentiment in the US. To this end, we use a nonlinear auto-regressive distributed lag cointegration approach, which allows us to capture both positive and negative disaggregated oil shocks. We find that oil demand shocks are the main drivers of both measures of uncertainty, while oil supply shocks affect treasury rates. However, both oil demand shocks and oil supply shocks affect investor sentiment, with certain differences in the effects of positive and negative shocks. The overall effects of both oil demand and supply shocks—whether positive or negative—are stronger in the long-run than in the short-run. Additionally, we apply rolling causality and reveal evidence of a rather homogenous causal flow from disaggregated oil shocks to the variables studied, particularly around global stress periods. Our findings have implications for asset pricing and portfolio risk management and suggest policy formulations that differentiate between disaggregated positive and negative oil price shocks. [ABSTRACT FROM AUTHOR]

We examine the predictive power of implied volatility in the commodity and major developed stock markets for the implied volatility in individual BRICS stock markets. We use daily data from March 2011 to October 2016 and employ the newly developed Bayesian Graphical Structural Vector Autoregressive (BGSVAR) model of Ahelegbey et al. (2016). Evidence suggests that the predictability of individual implied volatilities in BRICS is generally a function of both global and within the group stock market implied volatilities, and that the role of commodity market volatility is marginal, except for South Africa. Important implications for policy-makers and portfolio-managers are discussed. [ABSTRACT FROM AUTHOR]

This paper examines the return and volatility linkages between oil prices and the Lebanese stock market by applying the newly developed VAR-GARCH (Vector Autoregressive-Generalized Autoregressive Conditional Heteroskedasticity) model to weekly data from 30 January 1998 to 30 May 2014. To better understand the impact of the global financial crisis, we divide the data into three sub-periods: the pre-crisis period (02 February 1998–28 December 2007), the crisis period (02 January 2008–30 June 2009), and the post-crisis period (01 July 2009–30 May 2014). Contrary to previous studies showing the two-way transmission of return and volatility from oil prices to the stock markets of oil-exporting countries, our empirical results for the whole period reveal weak unidirectional return and volatility transmissions from oil prices to the Lebanese stock market. While the interrelationship between oil prices and Lebanese stocks increased during the crisis, it eased significantly in the post-crisis period. Our empirical results are important for policymakers involved in shock prevention and for portfolio managers seeking optimal portfolio allocation. [ABSTRACT FROM AUTHOR]

The article discusses the importance of fine wine as an alternative investment during the equity market downturns. Topics discussed includes factors affecting wine prices, the risk-return relationship and hedge characteristics of fine wine and correlation between fine wines and the U.S. consumer price index.

Purpose – This paper aims to examine the dynamic relationship across stock market returns in Morocco, Tunisia, Egypt, Lebanon, Jordan, Kuwait, Bahrain, Qatar, United Arabic Emirates (UAE), Saudi Arabia, and Oman from June 2005 to January 2012. Design/methodology/approach – The paper uses a multivariate model with leptokurtic distribution which allows for both return asymmetry and fat tails. The paper also derives from the model the conditional correlation between stock markets and examines the impact of the global financial crisis of 2008 on the conditional variance and correlation. Findings – The empirical results show that the Middle East and North African (MENA) markets are interconnected by their volatilities and not by their returns. Volatility persists in each market and significant volatility spillovers from small to relatively larger markets. During the crisis, the paper finds that conditional volatilities across markets increase but then during the post-crisis period return to their pre-crisis levels. More importantly, the conditional correlation behaves differently, with a significant evidence of downwards trend in some correlations across the MENA stock markets. Research limitations/implications – One limitation of the study relates to the relatively short-sample period which drives the empirical results. Practical implications – The key results imply that there is still a possibility of benefits from portfolio diversification across specific MENA countries during periods of high volatility. Originality/value – No previous study investigates the transmission of both the first and second moments of the return series across the MENA stock markets allowing for time-varying volatility and correlation and accounts for the 2008 global financial crisis to examine whether the conditional volatilities and correlations have strengthened or weakened during the crisis and afterwards. [ABSTRACT FROM AUTHOR]

Green investing has recently received considerable attention in India in light of the local government plans to significantly reduce the level of CO 2 emissions through conducting and funding various types of eco-friendly infrastructures and green projects on a national scale. Given that investment in environmentally friendly projects is still relatively new in India, the stock prices of Indian green companies could be highly volatile and very prone to risk transmission from other assets, which requires a precise estimation of the time-varying volatility of these green stocks to understand their underlying risk. In this paper, we examine if the stock volatility of Indian green companies can be predicted based on the information contents of commodity market implied volatility indexes (VIX) by employing a GARCH-based quantile regression model on daily data. The results show that risk significantly transmits from crude oil, gold, and silver markets to various Indian green stock indexes. The impact of the transmission from commodity market VIXs is stronger during the bearish stock market periods compared to bullish stock market periods, suggesting that green stock indexes are more likely to receive volatility from energy and precious metal markets during the periods of high uncertainty. Our findings are useful to socially responsible investors who focus not only on the environmental performance of a firm but also consider its financial performance. [ABSTRACT FROM AUTHOR]

The aim of this study is to understand the effect of the recent novel coronavirus pandemic on investor herding behavior in global stock markets. Utilizing a daily newspaper-based index of financial uncertainty associated with infectious diseases, we examine the association between pandemic-induced market uncertainty and herding behavior in a set of 49 global stock markets. More specifically, we study the pattern of cross-sectional market behavior and examine whether the pandemic-induced uncertainty drives directional similarity across the global stock markets that cannot be explained by the standard asset pricing models. Utilizing a time-varying variation of the static herding model, we first identify periods during which herding is detected. We then employ probit models to examine the possible association between pandemic-induced uncertainty and the formation of herding. Our findings show a strong association between herd formation in stock markets and COVID-19 induced market uncertainty. The herding effect of COVID-19 induced market uncertainty is particularly strong for emerging stock markets as well as European PIIGS stock markets that include some of the hardest hit economies in Europe by the pandemic. The findings establish a direct link between the recent pandemic and herd formation among market participants in global financial markets. Considering the evidence that herding behavior can drive security prices away from equilibrium values supported by fundamentals and further contribute to price fluctuations in financial markets, our findings have significant implications for policy makers and investors in their efforts to monitor investor sentiment and mitigate mis-valuations that might occur as a result. Furthermore, the evidence on the behavioral pattern of stock investors in relation to infectious diseases uncertainty can be useful in studying price discovery in stock markets and might help market participants in forming hedging strategies to mitigate downside risk in their investment portfolios. [ABSTRACT FROM AUTHOR]

Previous studies indicate that the US equity market implied volatility index (VIX) impacts the crude oil market volatility. However, the VIX typically reflects macroeconomic fluctuations, little affected by social media or investor perception changes. In this paper, we use recently introduced news-based equity market volatility (EMV) trackers to examine their impacts on crude oil volatility in its various states and their ability to predict oil volatility relative to that of the VIX. Applying quantile regressions, the results indicate a significant impact of EMV trackers on the oil market volatility during periods of high oil volatility, whereas the impact is mostly insignificant when the oil market is less volatile, which points to an asymmetry. Further analysis shows that various EMV trackers (EMV-overall, EMV-commodity, EMV-crises) have better forecasting power than VIX, economic policy uncertainty (EPU) and geopolitical risk (GPR) indexes. Our findings are relevant to asset pricing, oil portfolio formation, and risk management. • We explore the impact of news-based volatility trackers (EMV) on oil volatility. • The quantile regression model is employed. • The results are compared with VIX, EPU and GPR indexes. • EMV trackers have better forecasting power than other uncertainty indexes. [ABSTRACT FROM AUTHOR]

We examined the determinants of the U.S. consumer sentiment by applying linear and nonlinear models. The data are monthly from 2009 to 2019, covering a large set of financial and nonfinancial variables related to the stock market, personal income, confidence, education, environment, sustainability, and innovation freedom. We show that more than 8.3% of the total of eigenvalues deviate from the Random Matrix Theory (RMT) and might contain pertinent information. Results from linear models show that variables related to the stock market, confidence, personal income, and unemployment explain the U.S. consumer sentiment. To capture nonlinearity, we applied the switching regime model and showed a switch towards a more positive sentiment regarding energy efficiency, unemployment rate, student loan, sustainability, and business confidence. We additionally applied the Gradient Descent Algorithm to compare the errors obtained in linear and nonlinear models, and the results imply a better model with a high predictive power. [ABSTRACT FROM AUTHOR]

We examine the multifractal scaling behaviour and weak form market efficiency of clean energy stock indices using an asymmetric MF-DFA. We find asymmetric multifractality in the US, European, and global clean energy stock indices. Asymmetric multifractality in the clean energy stock index of the US is due to fat-tails and long-range correlation. However, for European and global clean stocks, multifractality is due only to fat-tailed distribution. We find higher efficiency in the upward trend of the European and global clean stock markets whereas, for the US, the market is less efficient when the market is upward trending. The time-varying market deficiency measure shows that US clean energy stocks are becoming relatively more efficient over time. • Asymmetric multifractal behaviour of clean stocks. • Markets are weak form efficient. • Multifractality of US due fat-tail distribution and long-range correlation. • Higher efficiency in the upward trend for European and global stocks. • US clean stocks are becoming relatively efficient over time. [ABSTRACT FROM AUTHOR]