Oil price shocks,global financial markets and their connectedness

This paper extends the literature on the relationship between oil price shocks and financial markets by examining the effect of oil shocks on the sovereign bond markets of a large number of advanced and emerging economies and exploring the impact of oil shocks on the degree of connectedness among international financial markets. We show that the effect of oil price shocks is not only limited to stock market returns, but also extends to bond markets, even after controlling for discount rate shocks as well as aggregate capital market effects. Unlike the case for stock markets, the effect on sovereign bonds is found to be rather heterogeneous (in terms of size and sign) and primarily driven by demand related shocks. We also show that oil price shocks serve as a driver of connectedness patterns across global financial markets, although the effect on connectedness depends on the nature of the oil market shock and the economic characteristics of the countries. Overall, the findings highlight the role of crude oil as a driver of not only of return dynamics in global stock and bond markets, but also of global financial connectedness patterns.     

Linkages between oil price shocks and stock returns revisited

In this paper, we revisit the debate on the relationship between oil price shocks and stock market returns by replicating the quantile-on-quantile (QQ) regression model for the US stock market in Sim and Zhou (2015, Journal of Banking and Finance), and extending it to 15 countries. The classification of these countries as oil importers or oil exporters depends on their net position in crude oil trade. Our results indicate that the main finding by Sim and Zhou (2015) that large negative oil price shocks can bolster stock returns when markets are performing well is only partially supported by the three largest oil importers in our sample – China, Japan and India – during the period 1988:1–2007:12. However, when extending the study to more recent data (period 1988:1–2016:12), we find that China and India experience higher returns when markets perform well and there is a large positive oil price shock. Also, large positive oil price shocks often lead to higher stock market returns when markets perform well for both oil exporting countries – Canada, Russia, Norway – and moderately oil dependent countries – such as Malaysia, Philippines and Thailand. In most cases large negative oil price shocks depress further already poorly performing markets, as in Sim and Zhou (2015). These findings highlight that the relationship between the distributions of oil price shocks and stock market returns is not stable over time in most countries studied. Furthermore, the asymmetric effect between positive and negative oil price shocks observed in the US market by Sim and Zhou (2015) is less evident in most countries for both the baseline and extended periods.     

Which oil shocks really matter in equity markets?

This paper examines the relationship between structural oil shocks and US equity markets. The recent oil shock decomposition of Ready (2018) is reconsidered and refined, providing a clearer delineation between shocks to equity market discount rates and aggregate demand, leading to an oil shock specification which attributes substantially more explanatory power to the latter in explaining equity market variation. Providing links with the literature dating back to Kilian and Park (2009), an explicit role is given to precautionary demand shocks using an independent measure constructed from oil futures data, reducing the role of the supply shocks obtained as the final residual in the recursive identification scheme. In an extended sample that allows an analysis of the oil/equity market relationship since the global financial crisis, the modified aggregate demand shocks have approximately twice as much explanatory power for stock return variation than the demand shocks of Ready (2018). The importance of these shocks in driving oil price changes and equity market volatility has only increased since the financial crisis, with the role of supply shocks diminishing. Once these demand effects are accounted for, there is little relationship between precautionary demand shocks and equity returns, in contrast to the existing literature.     

Time-varying co-movements between energy market and global financial markets: Implication for portfolio diversification and hedging strategies

This study explores the time patterns of volatility spillovers between energy market and stock prices of seven major global financial markets including clean energy, energy, information technology corporations, equity markets and United States economic policy index over the period vary from December 28, 2000 to December 31, 2018. We employ a time domain connectedness measures of Diebold and Yilmaz (DY, 2009, 2012 and 2014) to examine spillover mechanism of volatility shocks across future markets. Optimal weights and hedge ratios are calculated for portfolio diversification and risk management. The main findings of the study conclude that oil shocks are exogenous and contribution of oil market volatility to global financial markets is insignificant. The returns of World Stock Index and World Energy Index are major transmitters of volatility to clean energy market. Moreover, the impact of energy market become strong in global financial market when data is divided into pre, during and post financial crisis periods. Finally, the hedge ratios are volatile over time and their maximum value is observed during the financial crisis period of 2008–09. The optimal portfolio between energy and stock prices are heavily weighted to the stock markets.     

Oil shocks and financial systemic stress: International evidence

By conducting a structural VAR analysis on the financial systemic stress in 20 countries, this paper provides international evidence that oil structural shocks impact not only stress in individual financial markets but also their connectedness. The oil structural shocks explain a large fraction of the variation in the connectedness among various financial markets. The effect of oil structural shocks on financial systemic stress is largely dependent on the origins of oil price changes and a country's net oil export position. In most oil importing economies, financial systemic stress is negatively impacted by supply and aggregate demand shocks and positively impacted by oil-market specific demand shocks. Opposite patterns are detected in oil exporting economies. The effects of the spillovers are asymmetrically related with market conditions: During normal periods, more risks are spilled over from the oil market to financial systems, but during financial crises, the opposite occurs. In periods of financial crises and oil price collapses, there is noticeable contagion between the oil market and financial systems.     

Asymmetric volatility spillovers between oil and stock markets: Evidence from China and the United States

The relationship between oil and stock markets is a hot topic, but little research has focused on the time-varying asymmetric volatility spillover in a quantitative manner. In this study, we use a new spillover directional measure and asymmetric spillover measures to investigate the dynamic asymmetric volatility spillover between oil and stock markets during the period of 2007 to 2016. Using the intra-day data of WTI future prices, the S&P 500 index, and the Shanghai stock market composite index, we find that there exists an asymmetric spillover effect between the oil market and stock markets and that bad volatility spillovers dominate good volatility spillovers for most of the sampling period. In addition, participants are more pessimistic about the oil market than they are about the stock market. We further investigate the presence of asymmetric response to volatility shocks using the asymmetric generalized dynamic conditional correlation (AG-DCC) model; the results also show strong evidence of asymmetries in volatility shocks between the oil and stock markets due to bad volatility.     

Crude oil shocks and stock markets: A panel threshold cointegration approach

This paper proposes a panel threshold cointegration approach to investigate the relationship between crude oil shocks and stock markets for the OECD and non-OECD panel from January 1995 to December 2009. Nonlinear cointegration is confirmed for the oil–stock nexus in the panel. Because threshold cointegration is found, the threshold vector error correction models can be run to investigate the presence of asymmetric dynamic adjustment. The Granger causality tests demonstrate the existence of bidirectional long-run Granger causality between crude oil shocks and stock markets for these OECD and non-OECD countries. However, the short-run Granger causality between them is bidirectional under positive changes in the deviation and unidirectional under negative ones. Moreover, the speed of adjustment toward equilibrium is faster under negative changes in the deviation than that under positive ones in these OECD and non-OECD countries.     

Crude oil,equity and gold futures open interest co-movements

The study is unique in its investigation of the co-movements between trading activity on the equity, crude oil, and gold futures market, proxied by open interest. It provides empirical evidence that stock and crude oil futures demand for hedging is positively related, but reacts negatively to sudden shocks in open interest on the other market. Furthermore, gold futures open interest reacts positively to shocks in the crude oil futures trading activity. The level of instantaneous linkage is related to external market conditions. During periods of unstable financial markets, the correlation between equity and energy futures open interest decreases, and the correlation of the open interest on the equity and gold futures market turns weak negative. This indicates hedging funds allocation toward gold market in periods of stock market uncertainty.     

Oil volatility shocks and the stock markets of oil-importing MENA economies: A tale from the financial crisis

The role of oil price volatility in predicting the stock-market volatility of small oil-importing countries that have a substantial number of investors from neighboring oil-exporting countries remains unexplored. To refine our basic understanding of this role, this paper proposes a methodological extension of the recently developed causality-in-variance procedure and considers the case of Lebanon and Jordan. These two heavy importers of oil are interesting in the sense that they are located in a region with a large number of rich oil-exporting countries, so their stock markets are tied to oil-exporters by way of foreign investors. The conditional mean and variance of returns are modeled within an ARMAX–GARCH framework that accommodates three salient features of the data, namely: autocorrelation, day-of-the-week effects, and movements in international markets. For comparison purposes, the stock markets of Morocco and Tunisia are also included in the study. Empirical analyses highlight the dynamic effects of the global financial crisis on the volatility spillovers between oil and the stock markets of oil-importing countries and provide more insights into the seemingly contradictory effects of being oil-importers while having investors from oil-exporting countries. The main results indicate that the volatility spillover is much more apparent from the world oil market to the stock market of Jordan than the other way around, whereas oil volatility is not a good predictor of Lebanese stock market volatility. Finally, policy/practical implications and conclusions for future research are drawn.     

Relationships between oil price shocks and stock market: An empirical analysis from China

This paper investigates the interactive relationships between oil price shocks and Chinese stock market using multivariate vector auto-regression. Oil price shocks do not show statistically significant impact on the real stock returns of most Chinese stock market indices, except for manufacturing index and some oil companies. Some “important” oil price shocks depress oil company stock prices. Increase in oil volatility may increase the speculations in mining index and petrochemicals index, which raise their stock returns. Both the world oil price shocks and China oil price shocks can explain much more than interest rates for manufacturing index.     

Market inefficiencies associated with pricing oil stocks during shocks

The assumption that market efficiency informs the pricing of oil stocks is critical to understanding the co-movement between stock markets and oil markets. To test this assumption in relation to various types of real oil price changes, this article proposes a two-stage analysis method that starts with a quantile regression to identify oil shocks and develop interval-valued factor pricing models. These interval-based methods, relative to traditional point-based methods, can produce more efficient parameter estimations by providing more information. The results show that oil stocks tend to be overpriced following negative oil price shocks, which partially violates the efficient market hypothesis. Yet oil stocks are efficiently priced in response to moderate changes or positive oil price shocks, such that in most cases, the market remains efficient in pricing oil stocks.     

The effects of crude oil shocks on stock market shifts behaviour: A regime switching approach

In this paper we develop a two regime Markov-switching EGARCH model introduced by Henry [Henry, O., 2009. Regime switching in the relationship between equity returns and short-term interest rates. Journal of Banking and Finance 33, 405–414.] to examine the relationship between crude oil shocks and stock markets. An application to stock markets of UK, France and Japan over the sample period January 1989 to December 2007 illustrates plausible results. We detect two episodes of series behaviour one relative to low mean/high variance regime and the other to high mean/low variance regime. Furthermore, there is evidence that common recessions coincide with the low mean/high variance regime. In addition, we allow both real stock returns and probability of transitions from one regime to another to depend on the net oil price increase variable. The findings show that rises in oil price has a significant role in determining both the volatility of stock returns and the probability of transition across regimes.     

Tight oil,real WTI prices and U.S. stock returns

Following the adoption of new techniques of shale and fracking by U.S. oil companies, a structural vector autoregression model (SVAR) complements studies on why Brent and WTI started to diverge around early-2011. Using monthly data from 2000 to 2018, we decompose oil supply into: world oil (excluding U.S.), U.S. conventional (non-tight) oil and U.S. tight oil. We examine the variance decomposition of stock returns for the aggregate market (S&P 500), the S&P Energy sector and Chevron and Exxon Mobil oil companies, and we further identify differences between two subsamples from 2000 to 2010 and 2011 to 2018, respectively. We find that supply considerations (especially due to tight oil) become more important in the subsample after 2011, not only for individual oil companies but also for the aggregate market and energy sector: Supply shocks due to tight oil explain in our benchmark model between 29% (S&P 500) and 31% (S&P Energy) of the variance in stock returns after 24 months and between 28% and 29% for oil companies. None of these are statistically significant in the pre-2011 subsample. Among impulse responses, tight oil production responds positively to disruptions in world oil, and U.S. stock returns respond positively to oil price shocks and respond negatively to tight oil shocks which is a further finding while being consistent with the literature. Copula modeling uncovers stronger tail dependences in the second subsample for the interactions during downturns and upturns among global demand, crude oil prices and stock markets.     

Does the S&P500 index lead the crude oil dynamics? A complexity-based approach

Taking the complex property of nonlinear feedback connectivity into consideration, the goal of this paper is to apprehend the interdependences between the financial and energy sectors. Our contribution is both theoretical and methodological. We conduct a multivariate analysis employing nonlinear tools, namely the Partial Transfer Entropy and the Asymmetric Mackey-Glass causality test. In particular, we build a system comprising the petroleum complex (crude oil, gasoline and heating oil), the S&P500 index and the 1-month futures-spot spread for crude oil. By adopting a rolling-window approach, we observe a persistent lead-lag relationship between the S&P500 index and the market participants' expectations for crude oil, from 2004 to 2009. Depending on the bubble period in the stock market, it appears that the resulting coupling becomes subject to the deterioration of global economic activity, induced by large common shocks.     

Oil price volatility and stock returns in the G7 economies

This study examines the relationship between oil price volatility and stock returns in the G7 economies (Canada, France, Germany, Italy, Japan, the UK and the US) using monthly data for the period 1970 to 2014. In order to measure oil volatility we consider alternative specifications for oil prices (world, nominal and real prices). We estimate a vector autoregressive model with the following variables: interest rates, economic activity, stock returns and oil price volatility taking into account the structural break in the year 1986. We find a negative response of G7 stock markets to an increase in oil price volatility. Results also indicate that world oil price volatility is generally more significant for stock markets than the national oil price volatility.     

The effects of terrorism and war on the oil price–stock index relationship

The effects war and terrorism have on the covariance between oil prices and the indices of four major stock markets – the American S&P500, the European DAX, CAC40 and FTSE100 – using non-linear BEKK–GARCH type models are investigated. The findings indicate that the covariance between stock and oil returns is affected by war. A tentative explanation is that the two wars examined here predispose investors and market agents for more profound and longer lasting effects on global markets. On the other hand, terrorist incidents that are one-off unanticipated security shocks, only the co-movement between CAC40, DAX and oil returns is affected and no significant impact is observed in the relationship between the S&P500, FTSE100 and oil returns. This difference in the reaction may tentatively be interpreted as indicating that the latter are more efficient in absorbing the impact of terrorist attacks.     

The impacts of structural oil shocks on macroeconomic uncertainty: Evidence from a large panel of 45 countries

Using local projection methods, this paper employs monthly panel data from 1989 to 2017 to examine both linear and nonlinear impulse responses of macroeconomic uncertainty to structural shocks to global oil production, aggregate demand, oil-market-specific demand and speculative demand in a large group of 45 economies. We find that both oil supply and demand shocks are important drivers of uncertainty. There is strong evidence that the impacts of oil price shocks on macroeconomic uncertainty are regime-dependent and contingent on the states of investor sentiments and perceived volatility in financial markets. The responses of economic uncertainty to oil shocks, especially demand-side shocks, appear to experience a dramatic change in the post-Global Financial Crisis period.     

Volatility spillovers between crude oil and Chinese sectoral equity markets: Evidence from a frequency dynamics perspective

We examine the frequency dynamics of volatility spillovers between crude oil and China's stock markets in a spectral representation framework of generalized forecast error variance decomposition using sectoral stock indices data. We find evidence of total volatility spillover driven mainly by short-term spillovers. The net spillovers of the oil market are almost all positive and dominated by short-ter.m components, although the spillover during China's 2015 financial crisis is negative and attributable to long-term components. In addition, there exists heterogeneity in net pairwise (frequency) spillovers between the oil and sectoral stock markets. Moreover, structural breaks in volatilities appear to be a significant feature of volatility spillovers. Finally, frequency spillovers in our system can predict future stock market volatility. These results have economic implications for investors and policymakers.     

Oil shock transmission to stock market returns: Wavelet-multivariate Markov switching GARCH approach

Since oil prices are typically governed by nonlinear and chaotic behavior, it’s become rather difficult to capture the dominant properties of their fluctuations. In recent years, unprecedented interest emerged on the decomposition methods in order to capture drifts or spikes relatively to this data. Together, our understanding of the nature of crude oil price shocks and their effects on the stock market returns has evolved noticeably. We accommodate these findings to investigate two issues that have been at the center of recent debates on the effect of crude oil shocks on the stock market returns of five developed countries (USA, UK, Japan, Germany and Canada). First, we analyze whether shocks and or volatility emanating from two major crude oil markets are transmitted to the equity markets. We do this by applying, the Haar A Trous Wavelet decomposition to monthly real crude oil series in a first step, and the trivariate BEKK Markov Switching GARCH model to analyze the effect of the smooth part on the degree of the stock market instability in a second step. The motivation behind the use of the former method is that noises and erratic behavior often appeared at the edge of the signal, can affect the quality of the shock and thus increase erroneous results of the shock transmission to the stock market. The proposed model is able to circumvent the path dependency problem that can influence the prediction’s robustness and can provide useful information for investors and government agencies that have largely based their views on the notion that crude oil markets affect negatively stock market returns. Second, under the hypothesis of common increased volatility, we investigate whether these states happen around the identified international crises. Indeed, the results show that the A Haar Trous Wavelet decomposition method appears to be an important step toward improving accuracy of the smooth signal in detecting key real crude oil volatility features. Additionally, apart from UK and Japanese cases, the responses of the stock market to an oil shock depend on the geographic area for the main source of supply whether from the North Sea or from the North America (as we take two oil benchmarks WTI and Brent respectively).     

Does the U.S. economic policy uncertainty connect financial markets? Evidence from oil and commodity currencies

We provide novel insight to the emerging literature on the role of U.S. monetary policy as a driver of a global financial cycle by examining the possible causal effect of U.S. economic policy uncertainty on the connectedness of crude oil and currency markets, using a sample of commodity currencies from advanced and emerging nations. A battery of linear and nonlinear Granger-based causality tests indicate the presence of a causal relationship between economic policy uncertainty and the connectedness of oil and currency markets, particularly at low frequencies and more significantly after the outburst of the global financial crisis. While crude oil generally serves as a net transmitter of shocks to currencies across all frequency bands, the spillover effects from oil are largely concentrated towards the G10 currencies of Australian and New Zealand dollar that are often used as investment currencies in global carry trade strategies. Overall, our findings suggest the presence of a significant pass-through effect of economic policy uncertainty via oil prices, spilling over to the currency market, in line with the emerging evidence that the monetary policy by the U.S. Fed serves as a major driver of a global financial cycle that describes patterns in global capital flows, credit activity and asset prices across financial markets.