Time-varying linkages between energy and stock markets: Dynamic spillovers and driving factors

Integration between international energy prices and stock market returns is critical for global economics and politics. In this study, we employ a TVP-VAR (time-varying parameter vector autoregression) connectedness decomposition approach to investigate the time-varying linkages between a diversified energy portfolio comprising oil, coal, natural gas, and stock returns in G7 countries and China. This approach allows us to show the dynamic spillovers and explore the driving factors underlying the dynamic patterns. We find that geopolitical risks, global economic policy uncertainties, and equity market volatility can influence cross-market spillovers. This study expounds the effect of energy financialization.     

Dynamic volatility spillovers and investment strategies between the Chinese stock market and commodity markets

Building on the increased interest in the volatility spillover effects between Chinese stock market and commodity markets, this paper investigates the dynamic volatility spillovers of Chinese stock market and Chinese commodity markets based on the volatility spillover index under the framework of TVP-VAR. The result shows that there is a highly dependent relationship between the stock market and commodity markets. On average, the Chinese stock market is the net recipient of spillover, non-ferrous metals and chemical industry have a very obvious spillover impact on the stock market. The degree of total volatility spillover is different in different periods. After major crisis events, the volatility correlation between markets increases. Since the outbreak of COVID-19, the spillover effect of the stock market on the commodity market has been significantly enhanced. Then optimal portfolio weights and hedge ratios are calculated for portfolio diversification and risk management. The result shows that the ability of most commodities to hedge against risks is significantly reduced when the crisis occurs; NMFI (precious metals) and CRFI (grain) still have good hedging ability after the crisis, but the effectiveness of hedging risk is relatively low. Besides, the combination of CRFI and SHCI (the Shanghai composite index) is the most effective for risk reduction.     

Dynamic spillovers between commodity and currency markets

In this study, we examine the dynamic link between returns and volatility of commodities and currency markets. Based on weekly data over the period from January 6, 1987 to July 22, 2014, we find the following empirical regularities. First, our results suggest that the information contents of gold, silver, platinum, and the CHF/USD and GBP/USD exchange rates can help improve forecast accuracy of returns and volatilities of palladium, crude oil and the EUR/CHF and GBP/USD exchange rates. Second, gold (CHF/USD) is the dominant commodity (currency) transmitter of return and volatility spillovers to the remaining assets in our model. Third, the analysis of dynamic spillovers shows time- and event-specific patterns. For instance, the dynamic spillover effects originating in gold and silver (platinum) returns and volatility intensified (degraded) in the period marked by the global financial crisis. After the global financial crisis, the net transmitting role of gold and silver (platinum) returns shocks weakened (strengthened), while the net transmitting role of gold, silver and platinum volatility shocks remained relatively high. Overall, our findings reveal that, while the static analysis clearly classifies the aforementioned variables into net transmitters and net receivers, the dynamic analysis denotes episodes wherein the role of transmitters and receivers of return (volatility) spillovers can be interrupted or even reversed. Hence, even if certain commonalities prevail in each identified category of commodities, such commonalities are time- and event-dependent.     

On detection of volatility spillovers in overlapping stock markets

This paper applies a recently proposed structural vector autoregressive model identification method to an established, previously unidentified theoretical model of stock market volatility spillovers. The structural model is identified and can be estimated with the method of maximum likelihood. Volatility spillovers can then be tested with the standard likelihood ratio test. This way our test, unlike the majority of the existing volatility spillover tests, has its foundations firmly in the economic theory. Our test is developed for fully overlapping stock markets. The empirical application of the paper considers stock markets of the eurozone in the years 2010–2011. Evidence of volatility spillovers is found.     

Analysis of risk correlations among stock markets during the COVID-19 pandemic

The outbreak of the COVID-19 pandemic significantly negatively impacted the global economy and stock markets. This paper investigates the stock-market tail risks caused by the COVID-19 pandemic and how the pandemic affects the risk correlations among the stock markets worldwide. The conditional autoregressive value at risk (CAViaR) model is used to measure the tail risks of 28 selected stock markets. Furthermore, risk correlation networks are constructed to describe the risk correlations among stock markets during different periods. Through dynamic analysis of the risk correlations, the influence of the COVID-19 pandemic on stock markets worldwide is examined quantitatively. The results show the following: (i) The COVID-19 pandemic has caused significant tail risks in stock markets in most countries, while the stock markets of a few countries have been unaffected by the pandemic. (ii) The topology of risk correlation networks has become denser during the COVID-19 pandemic. The impact of the COVID-19 pandemic makes it easier for risk to transfer among stock markets. (iii) The increase in the closeness of the risk relationship between countries with lower economic correlation has become much higher than that between counties with higher economic correlation during the COVID-19 pandemic. For researchers and policy-makers, these findings reveal practical implications of the risk correlations among stock markets.     

Dynamic spillovers across oil,gold and stock markets in the presence of major public health emergencies

Extreme events have a systemic impact on global financial markets, leading to significant cross-market spillovers in the oil, gold, and stock markets and raising widespread concerns about market linkages and risk contagion. In this paper, with a focus on both return and volatility, a frontier spillover network analysis is used to examine the strength and scale characteristics of spillovers in the oil, gold and stock markets under major public health emergency shocks. In addition, the paper adopts a marginal spillover and network analysis to evaluate linkage relationships, risk sources and transmission paths in the oil, gold, and stock markets during such events. The results show that the return and volatility spillover effects generated across the oil, gold, and stock markets are significant, with return spillovers being more stable and volatility spillovers being highly sensitive to emergencies. Meanwhile, the COVID-19 pandemic has displayed the strongest return and volatility spillovers. The high intensity of the shocks during the COVID-19 period has changed the usual characteristics of the market, with the gold market becoming the risk receiver and the oil market becoming risk sources.     

Dynamic linkages between the center and periphery in international stock markets

This paper examines the dynamic linkages between the equity market of US representing the center and emerging markets using the Granger-causality test. The findings show that causality runs from the S&P500 to the stock prices of the 15 emerging markets but not vice versa.     

Investigating volatility spillover of energy commodities in the context of the Chinese and European stock markets

This paper investigates spillover from energy commodities to Shanghai stock exchange and European Stock market, and identifies possible risks transmission and portfolio diversification opportunities. The study is conducted on daily spot prices of carbon (CO2) emission, natural gas and crude oil from 16 December 2010 to 29 December 2022, employing Granger causality test, dynamic conditional correlation (DCC), Diebold-Yilmaz (2012) and Barunik-Krehlic (2017) models. Results identify higher volatility and imply greater connectedness in the longer run. Additionally, natural gas is witnessed as the highest contributor of the shocks and crude oil as the highest receiver of the shocks from the network connection. Further results suggest for investment in energy commodities in shorter run rather than long run for efficient portfolio diversification. Results from this study are expected to have practical implications for portfolio managers, investors, and market regulators, given the suggestion of this study to incorporate energy stocks for efficient diversification of risk.     

Asymmetric volatility spillovers between economic policy uncertainty and stock markets: Evidence from China

This study explores the spillovers between economic policy uncertainty (EPU) and stock market realized volatility (RV). The monthly index of Chinese and US EPU and RV are used to analyze the pairwise directional spillovers. We find that RV is a net receiver that is more vulnerable to shocks from U.S. EPU than to shocks from Chinese EPU. We further decompose the RV into good and bad volatility to test the asymmetric spillover effect between the stock market and EPU. The results suggest that EPU has a bigger effect on bad volatility in the stock market throughout most of the sample period. However, we find that good volatility spillovers become larger during periods of stimulated reform, whereas bad volatility spillovers become larger during periods of international disputes. We show that Chinese stock market volatility is sensitive to both U.S. and Chinese EPU and that the spillover is asymmetric in different periods.     

Immunizing markets against the pandemic: COVID-19 vaccinations and stock volatility around the world

The COVID-19 pandemic has exerted a noteworthy impact on stock market volatility around the world. Can vaccination programs revert these adverse effects? To answer this question, we scrutinize daily data from 66 countries from January 1, 2020 to April 30, 2021. We provide convincing evidence that COVID-19 vaccination assists in stabilizing the global equity markets. The drop in volatility is robust to many considerations and does not result solely from either the pandemic itself or the government policy responses—the negative correlation remains significant after controlling for these factors. The impact of vaccinations is relatively stronger within developed markets than in emerging ones.     

Financial crises and the dynamics of the spillovers between the U.S. and BRICS stock markets

We examine the spillover dynamics between the U.S. and BRICS stock markets using the multivariate DECO-GJR-GARCH model and spillover index method. We identify time variations in volatility equicorrelation and significant dynamic spillovers between these stock markets, as well as an increased impact of uncertainty on spillovers. Spillovers between markets intensify after the inception of the global financial crisis and subsequent European sovereign debt crisis. We also find, following the commencement of the crisis periods, that the U.S., Brazilian, and Chinese markets are net volatility transmitters, whereas the Russian, Indian, and South African markets are net recipients. These results shed new light on the information transmission channels between the U.S. and BRICS stock markets.     

Dynamic information spillovers in intraregionally-focused spot and forward currency markets

This paper proposes an intraregionally-focused tri-currency modeling framework to investigate dynamic information spillovers across spot and forward exchange rate markets in frontier and emerging country currencies, for both price levels and volatilities. Empirical estimates of structural parameters were obtained using an MGARCH–MSKST model that incorporated the term structure of non-deliverable forward (NDF) and deliverable forward (DF) markets, the dominance of regional currencies, and the influence of differing forward contract maturities (1-, 3-, 6- and 12-months). The currencies for nine countries were grouped into three regions: Northeast Asia (China, Korea and Taiwan); South/Southeast Asia (India, Indonesia and Philippines); and Latin America (Brazil, Chile and Columbia). The currency for each selected country was evaluated within the regionally determined tri-currency system. We found that NDF markets play a dominant role over DF markets with regard to price discovery during periods of tranquility. During periods of crisis, both NDF and DF markets exhibit a more balanced impact on currency market price discovery mechanisms. In addition, distinct differences were observed across regions: currencies in Northeast Asia were shown to be affected by the Chinese renminbi during periods of crisis and the Indian rupee could be regarded as the dominant currency in South/Southeast Asia. No robust results were obtained with regard to the dominance of currencies in Latin America. Finally, our results also suggest important distinctions between the effect of various instrument maturities on NDF and DF market returns – with DF returns being more responsive to longer maturities (6-months and 12-months). During tranquil periods NDF returns are more responsive to shorter maturities, but during crisis periods this effect is diminished.     

Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models

This paper examines the dynamic relationship between the oil market and stock markets from two perspectives: dependence between the crude oil market (WTI) and stock markets of the US and China, and volatility spillovers between them during 1991–2016. We further analyze structural breaks of market dependences and consider the extent of their influence on such relationships. Our vine-copula results show that the dependences between the three paired markets, WTI-US, WTI-China and US-China, vary dynamically across the six identified structural break periods. In particular, the dependence between WTI-US is stronger and more volatile than that between WTI-China during most of the periods. The dependence between US-China remains at a lower level in the earlier periods, but increases in the final period. Our VAR-BEKK-GARCH results demonstrate distinctive volatility spillovers across these periods, with varying directionality, in response to the structural changes. Overall, our results indicate that the oil market stimulates rapid and continual fluctuations in market dependences, which become manifest most acutely in the aftermath of the Financial Crisis of 2007–08, demonstrating the increasing interdependence between the oil and stock markets. Further, the growing influence of China on the dynamics of these relationships, in the period following the Great Recession, presents evidence that it begins to assume an increasingly important role in global economic recovery.     

Volatility spillovers between the Chinese and world equity markets

We propose measures of the directional volatility spillovers between the Chinese and world equity markets based on Diebold and Yilmaz's (2011b) forecast-error variance decompositions in a generalized vector autoregressive framework. It was found that the US market had dominant volatility impacts on other markets during the subprime mortgage crisis. The other markets were also very volatile, and driven by bad news, their massive volatilities were transmitted back to the US market. The volatility of the Chinese market has had a significantly positive impact on other markets since 2005. The volatility interactions among the markets of China, Hong Kong, and Taiwan were more prominent than those among the Chinese, Western, and other Asian markets were. The major correction of the Chinese stock market between February and July 2007 significantly contributed to the volatility surges of other markets. Owing to the restrictions on foreign investment, the Chinese stock market was not considerably affected in terms of market volatility during the subprime mortgage crisis.     

COVID-19 and time-frequency connectedness between green and conventional financial markets

Against the backdrop of the exponentially growing trend in green finance investments and the calls for green recovery in the post-COVID world, this study presents the time-frequency connectedness between green and conventional financial markets by using the spillover models of Diebold and Yilmaz (2012) and Baruník and Křehlík (2018). Covering a sample period from January 01, 2008, to July 31, 2020, we aim to explore the dynamics of connectedness between conventional and green investments in fixed income, equity, and energy markets. Additionally, we determine the role of market-wide uncertainty in altering the connectedness structure by performing a subsample analysis for the ongoing COVID-19 pandemic crisis period. Our results show that competing energy investments are not connected, and there is only one-way spillovers from the conventional bonds in the fixed-income investments. Additionally, we observe a low (high) intergroup connectedness for conventional (green) investments. Moreover, the frequency-based analysis shows that connectedness between these competing markets is more pronounced during the short-run. The subsample analysis for the pandemic crisis period shows similar results except for the disconnection between bond markets in the short-run frequency. Our time-varying analysis shows peaks and troughs in the connectedness between climate-friendly and conventional investments that suggest different global events such as the Eurozone Debt Crisis and Shale Oil Revolution drives the association between alternate investments. Similarly, we observe an enhanced connectedness during the recent COVID-19 period, suggesting that financial stability would be a significant factor in determining the smooth transition to green investments.     

Risk spillovers from China's and the US stock markets during high-volatility periods: Evidence from East Asianstock markets

This paper studies cross-country risk spillovers through C-vine copula quantile regression. We find Both China's and the US markets can result in large risk spillovers to East Asian markets. Furthermore, their significant conditional spillovers indicate they can emit risk through an intermediary market. However, their distinctive dependency structures with East Asian markets reflect their differences in spillovers to the markets in magnitude. The risk spillovers from US are stronger than China in magnitude. Moreover, the risk spillover from China's stock market during its high-volatility period is weaker than the whole period, which is contrary to the US market. It may imply Chinese financial influences gradually increase with Chinese financial liberalization and regional integration. Our results have implications for macroprudential regulators adopt the effective supervision and regulation to deal with the cross-border risk spillovers, and for international investors in risk hedging, derivative valuation and investment.     

Illiquidity,return and risk in G7 stock markets: Interdependencies and spillovers

Trading activity in G7 stock markets reflects not only the macroeconomic and financial impact of these G7 economies in international economic growth, but also their financial interdependence. While this nexus of major stock markets has been explored in terms of volatility and return spillovers, there has been no combined analysis of return, volatility and illiquidity spillovers. We study illiquidity spillovers because they are transmissions of trading activity and, thereof, transmissions of information and market sentiment. We find that the dynamics of international stock markets are characterized by persistent illiquidity and also that illiquidity shocks are significantly correlated across markets. Furthermore, we discover Granger causal associations between risk, return and illiquidity across G7 stock market and also within each stock market. Our findings bear significance for the regulation of international financial markets and also for international portfolio diversification.     

Have the predictability of oil changed during the COVID-19 pandemic: Evidence from international stock markets

The COVID-19 has undoubtfully brought fierce shocks to the real economic activities, financial market and public lives. Under this special condition, this study explores whether the predictability of crude oil futures information has changed before and during the COVID-19 pandemic for 19 international stock markets. From an in-sample perspective, we find that the crude oil futures RV can significantly affect future stock volatility for each equity index except SSEC. Moreover, the out-of-sample results from statistic and economic perspective reveal that crude oil futures RV is a more efficient predictor during the COVID-19 pandemic compared with the pre-crisis period. Furthermore, we find that the predictability of crude oil futures information is stronger from March to May 2020, when the epidemic is seriously prevailing. The empirical results from alternative evaluation method, recursive window method, alternative realized measures, controlling VIX and the seasonal effect, asymmetric forecasting window and different testing windows are robust and consistent. Our findings could offer novel and significant policy and practical implications.     

Dynamic efficiency of stock markets and exchange rates

We use generalized Hurst exponents to investigate long-range dependence across countries that have implemented an inflation targeting monetary policy regime and have a floating currency regime. We show that the degree of long-range dependence has changed after the 2008 crisis for equity markets but not as much for exchange rate markets. We compare results for developed and emerging economies and find that there still are some important differences but not as they were before the crisis. We also include an additional set of relevant countries and find that our results are more pronounced for inflation targeters. We discuss several implications of these results.     

Constructing a positive sentiment index for COVID-19: Evidence from G20 stock markets

The present study investigates the degree of market responses through the scope of investors' sentiment during the COVID-19 pandemic across G20 markets by constructing a novel positive search volume index for COVID-19 (COVID19⁺). Our key findings, obtained using a Panel-GARCH model, indicate that an increased COVID19⁺ index suggests that investors decrease their COVID-19 related crisis sentiment by escalating their Google searches for positively associated COVID-19 related keywords. Specifically, we explore the predictive power of the newly constructed index on stock returns and volatility. According to our findings, investor sentiment positively (negatively) predicts the stock return (volatility) during the COVID-19. This is the first study assessing global sentiment by proposing a novel proxy and its impacts on the G20 equity market.