Oil shocks and stock market volatility of the BRICS: A GARCH-MIDAS approach

In this study, we employ the GARCH–MIDAS (Generalised Autoregressive Conditional Heteroskedasticity variant of Mixed Data Sampling) model to investigate the response of stock market volatility of the BRICS group of countries (Brazil, Russia, India, China, and South Africa) to oil shocks. We utilise the recent datasets of Baumeister & Hamilton (2019), where oil shocks are decomposed into four variants: oil supply shocks, economic activity shocks, oil consumption shocks, and oil inventory shocks. We further decompose each of these shocks into positive and negative shocks, and our findings show heterogeneous response of stock market volatility of the BRICS countries to the alternative oil shocks, including positive and negative shocks. The differing responses across the BRICS countries could be attributed to differences in the economic size, oil production, and consumption profile of the countries, market share distribution across firms, and financial system and regulation efficiency.     

Oil price shocks and exchange rate movements

This study investigates the effects of oil price shocks on exchange rate movements in five major oil-exporting countries: Russia, Brazil, Mexico, Canada, and Norway. The R² of the fundamental model doubles in Russia and Brazil, but increases slightly in Canada and Norway when oil prices are added to it. The volatility of exchange rates associated with oil price shocks is significant in Russia, Brazil, and Mexico, but weak in Norway and Canada. It takes much longer for the exchange rate to reach the initial equilibrium level in Russia, Brazil, and Mexico than in Norway and Canada. The asymmetric behavior of exchange rate volatility among countries seems to be related to the efficiency of financial markets rather than to the importance of oil revenues in the economy.     

Flexibility of Adjustment to Shocks: Economic Growth and Volatility of Middle-Income Countries Before and After the Global Financial Crisis of 2008

Our analysis shows that the associations of growth level, growth volatility, shocks, institutions, and macroeconomic fundamentals have changed in important ways after the 2008 global financial crisis. Economic growth across countries has become more dependent on external factors, including global growth, global oil prices, and global financial volatility. After accounting for the effects global shocks, we find that several factors facilitate adjustment to shocks in middle-income countries. Educational attainment, share of manufacturing output in gross domestic product, and exchange rate stability increase the level of economic growth; although, exchange rate flexibility, education attainment, and lack of political polarization reduce the volatility of economic growth.     

Do heterogeneous oil price shocks really have different effects on earnings management?

Under the modern corporate governance structure, there is a knowledge gap in how companies' financial reporting practices respond to oil price shocks in China. To fill this gap, we employ China's A-share listed companies and follow Kilian (2009) study to investigate how the three types of classical oil shocks affect corporate earnings management heterogeneously. We also consider the role of oil implied volatility in this relationship and further examine the possible heterogeneity between energy-related and non-energy-related subsamples. The empirical results show that there are variant effects among the heterogeneous oil price shocks on earnings management. Specifically, oil supply shocks stimulate firms to manipulate more accrual and real earnings, and firms are more likely to carry out accrual earnings management downward. Oil aggregate demand shocks weaken the degree of accrual earnings manipulation and mainly reduce the negative accrual earnings manipulation. Oil-specific demand shocks constrain the earnings management behavior of companies and improve their accounting quality. Besides, the increased uncertainty of oil price weakens the promotion effect of oil supply shocks on earnings manipulation, and the moderating effect occurs mainly in downward earnings management. Furthermore, the subsample estimated results reveal that oil price shocks do not affect the degree of accrual earnings management of energy-related companies. Instead, they impact the non-energy-related companies. Overall, our findings provide a series of targeted policy recommendations to mitigate the principal-agent problems and cope with energy price volatility risks.     

Volatility transmission between oil prices and equity sector returns

This paper employs bivariate GARCH models to simultaneously estimate the mean and conditional variance between five different US sector indexes and oil prices. Since many different financial assets are traded based on these market sector returns, it is important for financial market participants to understand the volatility transmission mechanism over time and across these series in order to make optimal portfolio allocation decisions. We examine weekly returns from January 1, 1992 to April 30, 2008 and find evidence of significant transmission of shocks and volatility between oil prices and some of the examined market sectors. The findings support the idea of cross-market hedging and sharing of common information by investors.     

Time-varying impacts of demand and supply oil shocks on correlations between crude oil prices and stock markets indices

This paper investigates the time-varying impacts of demand and supply oil shocks on correlations between changes in crude oil prices and stock markets returns. The findings, obtained by means of a DCC-GARCH from June 2006 to June 2016, indicate that demand shocks positively affected the correlations between crude oil prices and stock market returns from late 2007 to mid-2008, during the apex of the financial markets volatility; from early 2009 to mid-2013, during global economy recovery from the financial crisis; and after 2015, when uncertainties about the Chinese growth and the US economy upturning arose. The dynamic conditional correlation, obtained after the removal of demand shocks effects, presented an average value of 0.13 when all economy sectors were considered and of 0.03 when the energy sector returns were excluded from the stock index. These correlations, still positive on average, suggest that exogenous supply oil shocks had little impact on US mainly enterprises cash flows over the last 10 years. Exceptions are the periods from 2006 to financial crisis and from 2014 until April 2016, when significant and unpredicted changes in oil market happened, considerably affecting the value of the main US companies.     

Financial Frictions,Financial Shocks,and Aggregate Volatility

The Great Moderation was accompanied by an increase in financial volatility. We explore the sources of these divergent patterns in volatilities by estimating a model with time‐varying financial rigidities subject to structural breaks in the size of shocks, the monetary policy rule coefficients, and the average size of the financial rigidity. Institutional changes are key in accounting for the Great Moderation and in shaping the transmission mechanism of financial shocks. The increase in financial volatilities is accounted for by larger financial shocks, but the vulnerability of the economy to these shocks is significantly alleviated by the estimated changes in institutions.     

Multilayer information spillover networks between oil shocks and banking sectors: Evidence from oil-rich countries

There is no doubt that oil price shocks significantly affect oil-producing countries' macroeconomic fundamentals and financial stability, mainly in crisis times. The recent oil price shocks, coupled with the COVID-19 pandemic, motivated us to investigate the connectedness and risk transmission among oil shocks and banking sectors in the Gulf Cooperation Council (GCC) economies from June 30, 2006, to September 9, 2021. Thus, we construct multilayer information spillover networks between oil price shocks and GCC banking sectors. The empirical results show that the Bahrain banking sector depicts the highest connectedness and risk transmission with oil price shocks on the extreme risk spillover layer. In addition, Kuwait and the United Arab Emirates are highly connected to oil demand shocks. Furthermore, we find a substantial increase in extreme risk spillover and volatility spillover layers during the COVID-19 period. The results of this paper have some important implications for regional portfolio risk management, alleviating systemic risk, and developing hedging and investment strategies.     

Oil price shocks and American depositary receipt stock returns

In this paper we examine the impact of oil price shocks on twelve countries American Depositary Receipt (ADR) returns using monthly data from 1999.01 to 2014.12. The results show that oil price shocks have a positive and statistically significant impact on ADR return in all twelve countries. These results are robust to the inclusion of other explanatory variables such as oil price volatility and the spillover of the United States stock market. Further analysis shows that this effect is stronger in the post financial crisis time period compared to the pre-financial crisis time period.     

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.     

Volatility spillover in the foreign exchange market: the Indian experience

We find evidence of significant volatility co-movements and/or spillover from different financial markets to the forex market in India. Among a large number of variables examined, volatility spillovers from domestic stock, government securities, overnight index swap, Ted spread and international crude oil markets to the foreign exchange market are found to be significant. There is evidence of asymmetric reactions in the forex market volatility. Comparisons between pre-crisis and post-crisis volatility indicate that the reform measures and changes in financial markets microstructure during the crisis period had significant impact on volatility spillover. During the post-crisis period, the lagged volatility component that represents persistent or fundamental changes had significant spillover effect on forex volatility, rather than the temporary shocks component. There is evidence of a decline in the asymmetric response in the forex volatility during the post-crisis period in India.     

Dynamic effects of idiosyncratic volatility and liquidity on corporate bond spreads

We study the dynamic impact of idiosyncratic volatility and bond liquidity on corporate bond spreads over time and empirically disentangle both effects. Using an extensive data set, we find that both idiosyncratic volatility and liquidity are critical mainly for the distress portfolios, i.e., low-rated and short-term bonds; for others only volatility matters. The effects of volatility and liquidity shocks on bond spreads were both exacerbated during the recent financial crisis. Liquidity shocks are quickly absorbed into bonds prices; however, volatility shocks are more persistent and have a long-term effect. Our results overall suggest significant differences between how volatility and liquidity dynamically impact bond spreads.     

Oil price shocks,investor sentiment,and asset pricing anomalies in the oil and gas industry

This paper documents that stocks are not efficiently priced in the oil and gas industry. We find significant cross-sectional effects on stock returns from various firm characteristics in the oil and gas industry. Specifically, 13 out of 15 prominent capital market anomalies are robust in the oil and gas industry. Investor sentiment has significantly positive impact on 4 anomalies: composite equity issues, investment to assets, net stock issues, and value effect. Among the three oil shocks, we find that aggregate demand shocks have significantly impact on 6 anomalies: composite equity issues, financial distress, net stock issues, O-SCORE, return on assets, and idiosyncratic volatility. Our results are consistent with the view that high arbitrage costs and risks have significant deterring effects on arbitrage in the oil and gas industry. Our findings also have practical investment and policy implications for investors, firm managers, and policy makers alike.     

Harnessing jump component for crude oil volatility forecasting in the presence of extreme shocks

Oil markets are subject to extreme shocks (e.g. Iraq’s invasion of Kuwait), causing the oil market price exhibits extreme movements, called jumps (or spikes). These jumps pose challenges on oil market volatility forecasting using conventional volatility dynamic models (e.g. GARCH model) This paper characterizes dynamics of jumps in oil market price using high frequency data from three perspectives: the probability (or intensity) of jump occurrence, the sign (e.g. positive or negative) of jumps, and the concurrence with stock market jumps. And then, the paper exploits predictive ability of these jump-related information for oil market volatility forecasting under the mixed data sampling (MIDAS) modeling framework. Our empirical results show that augmenting standard MIDAS model using the three jump-related information significantly improves the accuracy of oil market volatility forecasting. The jump intensity and negative jump size are particularly useful for predicting future oil volatility. These results are widely consistent across a variety of robustness tests. This work provides new insights on how to forecast oil market volatility in the presence of extreme shocks.     

Forecasting crude oil volatility with geopolitical risk: Do time-varying switching probabilities play a role?

This study examines whether geopolitical risk (GPR) exhibits an ability to forecast crude oil volatility from a time-varying transitional dynamics perspective. Unlike previous studies that assume an oversimplification of the fixed transition probabilities for crude oil volatility, we develop an asymmetric time-varying transition probability Markov regime switching (AS-TVTP-MS) GARCH model. In-sample estimated results show that GPR yields strong evidence of regime switching behavior on crude oil volatility and that the negative shocks of GPR result in greater effects on switching probabilities than positive shocks. Out-of-sample results indicate that the AS-TVTP-MS GARCH model containing the GPR index outperforms other models, suggesting that the consideration of GPR information and time-varying regime switching together results in superior predictive performance. Moreover, the predictability of oil volatility is further verified to be economically significant in the framework of portfolio allocation. In addition, our results are robust to various settings.     

Linkages between Indian and US financial markets: impact of global financial crisis and Eurozone debt crisis

This paper examines inter-linkages between Indian and US equity, foreign exchange and money markets using the vector autoregressive-multivariate GARCH-BEKK framework. We investigate the impact of global financial crisis (GFC) and Eurozone debt crisis (EZDC) on the conditional volatility and conditional correlation estimates derived from the multivariate GARCH model for Indian and US financial markets. Our results indicate that there is significant bidirectional causality-in-mean between the Indian stock market returns and the Rs./USD market returns, and significant unidirectional causality-in-mean from the US stock market returns to the Indian stock market returns. As regards volatility spillovers, we find that volatility in the Indian stock market rises in response to domestic as well as US financial market shocks but Indian financial market shocks do not impact the US markets. Further, impact of the recent crisis episodes on the covariance matrix is found to be significant. We find that volatility in the Indian and US financial markets significantly amplified during GFC. The conditional correlations across asset markets were significantly accentuated in the wake of the two crisis episodes. The impact of GFC on cross-market conditional correlations is higher for majority of the asset market pairs in comparison to the EZDC.     

Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013

We determine the events that cause large shocks in volatility of the DJIA index over the period 1928–2013, using a new semi-parametric test based on conditional heteroscedasticity models. We find that these large shocks can be associated with particular events (financial crashes, elections, wars, monetary policies, etc.). We show that some shocks are not identified as extraordinary movements by the investors due to their occurring during high volatility episodes, especially the 1929–1934, 1937–1938 and 2007–2011 periods.     

Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest

In this study we examine the dynamic structural relationship between oil price shocks and stock market returns or volatility for a sample of both net oil–exporting and net oil–importing countries between 1995:09 and 2013:07. We accomplish that, by extending the Diebold and Yilmaz (2014) dynamic connectedness measure using structural forecast error variance decomposition. The results for both stock market returns and volatility suggest that connectedness varies across different time periods, and that this time–varying character is aligned with certain developments that take place in the global economy. In particular, aggregate demand shocks appear to act as the main transmitters of shocks to stock markets during periods characterised by economic–driven events, while supply–side and oil–specific demand shocks during periods of geopolitical unrest. Furthermore, differences regarding the directions and the strength of connectedness can be reported both between and within the net oil–importing and net oil–exporting countries. These results are of particular importance to investors and portfolio managers, given the recent financialisation of the oil market.     

Information connectedness of international crude oil futures: Evidence from SC,WTI, and Brent

The first Yuan (RMB) denominated crude oil futures contract, SC, was launched in the Shanghai International Energy Exchange (INE) on 26 March 2018, which is extremely meaningful for China and other Asian countries by offering a new option of oil price risk management. To identify the information connectedness among this emerging contract and those mature WTI and Brent oil futures, we provide return and volatility directional connectedness evidence among them in both the time and frequency domains. The empirical results show that, firstly the three oil futures of SC, WTI, and Brent present high degree of total connectedness in the return and volatility series, implying tight information transfer among them. Secondly, the net directional connectedness results suggest that the SC can provide competitive information on oil returns and is a net and powerful contributor to volatility shocks. In addition, from a frequency-specific perspective, we find that the SC appears to be not only a net transmitter of return shocks on the medium- and long-term frequencies but also a net transmitter of volatility shocks consistently across the whole frequency ranges. The overall evidence suggests that China's new oil futures is an active participant in the international oil futures market, and may become an important product in information transmission across international crude oil futures markets by providing effective hedging instrument for crude oil producers, refiners, consumers, and investors, especially those in Asia.