Does high-frequency crude oil futures data contain useful information for predicting volatility in the US stock market? New evidence

This study examines whether high-frequency crude oil futures data contain useful information to forecast the realized volatility (RV) of the US stock market from both in- and out-of-sample perspectives. There are several significant findings. First, from the in-sample analysis, crude oil futures RV exhibits a significant positive impact on the future S&P 500 volatility. Second, the out-of-sample results reveal that the prediction models, including crude oil futures RV, outperform the related competing models, implying that crude oil RV is an important predictive factor for the US stock market. Third, we further find that the primary forecasting ability of crude oil RV is reflected in high-frequency information, negative crude oil RV, and high volatility level. Finally, the out-of-sample empirical results based on different forecasting windows, alternative forecast evaluation approaches, subsample analysis, different prediction models, alternative MIDAS lags, and controlling the leverage effect are robust to our conclusions.     

Which determinant is the most informative in forecasting crude oil market volatility: Fundamental,speculation, or uncertainty?

This paper aims to identify the most informative determinant in forecasting crude oil market volatility. We use a new GARCH-class model based on mixed data sampling regression and the dynamic model averaging combination method to examine the predicting power of the determinants. We integrate both the global economic policy uncertainty (GEPU) indices and several national economic policy uncertainty (EPU) indices with traditional determinants, such as global oil demand, supply, and speculation. Our analysis suggests that the EPU indices comprehensively integrate the information contained in other determinants. Specifically, GEPU indices and the U.S.’s EPU index have superior predictive powers for West Texas Intermediate spot oil volatility. This finding highlights the importance of EPU indices, implying that they are key factors to consider when determining crude oil market volatility.     

Do emerging markets matter in the world oil pricing system? Evidence of imported crude by China and India

This paper provides empirical evidence on the changing structure of world oil price system by identifying an additional driver-emerging market factor. We choose China and India as a representative of emerging markets to examine if the quantity of crude oil imported by China and India is significant in the existing oil pricing system (Kaufmann et al., 2004). Our data starts from January 2002 and ends in March 2010, which includes the oil shock of 2007–2008. We utilize cointegration and error correction model framework developed by Engle–Granger (1987) and Gregory–Hansen (1996) in the analysis. Our results indicate that demand from emerging markets has become a significant factor in the world oil pricing system since 2003. This result is significant as it lends empirical support to the widely held conjecture that the oil shock of 2007–2008 is a demand-led shock (Hamilton, 2009). Our result also has significant policy implications that go beyond the oil shock. The emerging market factor is there to stay and reflects the changing power between emerging and developed economies in the world economic system as a result of decades of fast economic development in the former. It will certainly influence policy issues related to oil and beyond.     

Spillovers between oil and stock returns in the US energy sector: Does idiosyncratic information matter?

This paper investigates the inter-connectedness between WTI oil price returns and the returns of listed firms in the US energy sector. Specifically, we focus on the issue of whether firm-level idiosyncratic information matters. A generalised dynamic factor model is used to separate common components from idiosyncratic components in these energy stocks. Systemic connectedness is then estimated following Diebold and Yilmaz (2014). Our empirical results demonstrate the important role of industrial-level common information in understanding the oil–stock relationship. A number of interesting points include: the US energy sector is the net contributor to WTI price changes, but the effect is mainly driven by industrial-level common information; the oil and gas industry dominates other industries in the energy sector; the dynamic analysis shows that although idiosyncratic information is mostly independent of oil shocks, individual energy stock returns do respond to WTI price movements.     

Does crude oil price play an important role in explaining stock return behavior?

Employing the MS-ARJI-GJR-GARCH-X model, in which the parameters for the jump process, the asymmetric GARCH effect and the impacts of oil price shocks are regime-dependent, this paper analyzes the impact of crude oil price shock on stock return dynamics. Empirical results reveal three interesting findings. First, incorporating the asymmetric GARCH effect and the oil price shock can substantially improve fitting ability. Second, the GARCH and jump components show very different behaviors during turbulent and stable periods. Third, the effects of current and past oil price shocks differ. The conditional mean, mean of jump size and variance of jump size immediately respond to a current oil price shock. A one-period lagged oil price shock, no matter whether positive or negative, can affect the transition probability that the stock market will remain conditional in the next period. Moreover, the effects of lagged positive and negative shocks on transition probabilities are very different.     

Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models

Extensive studies have used stock market information to forecast crude oil prices, and stock market can more easily derive high-frequency data than crude oil market due to no revisions, which raises a question that whether high-frequency stock market data can improve the forecast performance of crude oil prices. Therefore, this paper employs the MIDAS model and the high-frequency data of four stock market indices to forecast WTI and Brent crude oil prices at lower frequency. The results indicate that the high-frequency stock market indices have certain advantage over the lower-frequency data in forecasting monthly crude oil prices, and the MIDAS model using high-frequency data proves superior to the ordinary model.     

Oil prices and stock markets: Does the effect of uncertainty change over time?

This paper investigates empirical marginal effects of uncertainty measured by conditional variance of the stock and crude oil prices on their returns using stock index prices for U.S., Japan, Korea, and Hong Kong over the period 1996–2015. A time-varying parameter model with a dynamic conditional correlation (DCC) bivariate GARCH-in-Mean specification is considered to investigate time-varying marginal effects of uncertainty on the stock and crude oil returns. The empirical findings show that there exist significant negative time-varying effects of uncertainty on the returns over some sub-periods.     

Can investor attention predict oil prices?

This paper sets out to investigate the predictive power of investor attention onto oil prices. We firstly construct investor attention index by using the Google search volume index (SVI) based on a broad set of words related to oil-related variables and terms that are directly linked to real economy to measure investor attention. Then the empirical work is performed via a novel hybrid approach and WN model (Westerlund and Narayan, 2012, 2014) that account for characteristics of persistency, endogeneity, and heteroskedasticity. The empirical results show that investor attention does exhibit statistically and economically significant in-sample and out-of-sample forecasting power to directly forecast oil prices for both daily data and weekly data. In addition, the results exhibit the term structure character, which are helpful for understanding the financial phenomena that irrational attentions have more effect in short-term decision-making.     

Regulatory interventions in the US oil and gas sector: How do the stock markets perceive the CFTC's announcements during the 2008 financial crisis?

This paper analyzes the effects of the Commodity Futures Trading Commission's (CFTC) announcements on the stock returns of oil and gas companies around the financial crisis of 2008. Using event study methodology and regression analyses, we examine a set of 122 oil and gas related stocks listed in the New York Stock Exchange (NYSE) for 35 announcements. Our results indicate that CFTC announcements, depending on their content, can affect the stock returns of oil and gas companies. In particular, this is found to hold true during the period of high-volatility in oil prices, i.e., the period following Lehman Brothers failure. During this period, oil and gas related stock returns respond positively to most regulatory announcements, showing that the CFTC's regulatory interventions are perceived positively by the stock market.     

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.     

How to effectively estimate the time-varying risk spillover between crude oil and stock markets? Evidence from the expectile perspective

With the integration and financialization of world economy, massive hot money has frequently flowed between crude oil and stock markets, and has brought significant extreme risks and their spillover. For this reason, this paper develops the ARCH-Expectile model with embedded Conditional AutoRegressive structure (namely CAR-ARCHE model) and expectile-based VaR (EVaR) approach, and investigates the time-varying risk spillover between WTI futures market and US, UK, Japanese and global stock markets, respectively. The results indicate that, for one thing, the EVaR approach based on CAR-ARCHE model is more adequate than the conventional quantile-based VaR (QVaR) approach based on GED-GARCH for WTI and stock markets, which is due to the evident advantages of expectile compared to quantile. For another, the unidirectional downside risk spillover effects from WTI to the four stock markets and vice-versa are only remarkable during major events and present variations with jumps, but the bidirectional downside risk spillover effects between them are significant for each time point during the in-sample period, which indicate that the simultaneous risk spillover between WTI and stock markets are fairly pronounced.     

Do exchange rates respond asymmetrically to shocks in the crude oil market?

The paper argues that exchange rates respond asymmetrically to different shocks to the crude oil market. We apply Kilian's (2009) methodology to disentangle shocks to the crude oil market into distinct demand and supply shocks, and examine the response of the U.S. real and nominal trade-weighted U.S. dollar exchange rate indexes, as well as six other bilateral exchange rates to these shocks. Our analysis indicates that oil supply shocks have no significant effects on exchange rates, while global aggregate demand and oil-specific demand shocks lead to depreciations. We further show that exchange rates respond asymmetrically to shocks in the crude market depending on whether the shocks are large versus small, or positive versus negative.     

Can market power in the electricity spot market translate into market power in the hedge market?

Electricity is a non-storable commodity frequently traded in complex markets characterized by oligopolistic structures and uniform-price auctions. Electricity prices have idiosyncratic patterns not addressed by the usual commodity pricing literature. This paper develops an electricity market model that allows for oligopoly, vertical integration, and a uniform-price auction mechanism. It derives a linear equilibrium relationship between spot prices and state variables affecting firms' costs and demand. It then applies a two-factor forward pricing model over the equilibrium spot price process, and shows that forward prices can be positively affected by spot market power. An empirical estimation of the model follows, using NZEM data.     

Gold and oil futures markets: Are markets efficient?

In this paper we examine the long-run relationship between gold and oil spot and futures markets. We draw on the conceptual framework that when oil price rises, it creates inflationary pressures, which instigate investments in gold as a hedge against inflation. We test for the long-run relationship between gold and oil futures prices at different maturity and unravel evidence of cointegration. This implies that: (a) investors use the gold market as a hedge against inflation and (b) the oil market can be used to predict the gold market prices and vice versa, thus these two markets are jointly inefficient, at least for the sample period considered in this study.     

Effects of oil price shocks on the stock market performance: Do nature of shocks and economies matter?

The main focus of this study is to examine how oil price fluctuations influence the performance of stock markets. This study used the causality approach developed by Toda and Yamamoto (1995) to explore the causality between oil prices and stock prices in the long-run and their short-term impact. The generalized impulse response functions were applied to the monthly data in the period from January 1997 to July 2013. In this study, to capture the different characteristics of oil refining, exporting and importing, three Asian economies were examined. The results indicate that the manner in which a market reacts to hikes in oil prices varies between different markets and periods. This depends on differences in the oil characteristics of the economy and the nature of the shock in oil prices.     

“De-financialization” of commodities? Evidence from stock,crude oil and natural gas markets

In order to investigate whether the crude oil and natural gas market volatility is influenced by the volatility in the stock market or whether these different variables move all together, we introduce the Volatility Threshold Dynamic Conditional Correlations (VT-DCC) approach to investigate the spillover effect of stock market volatility index (VIX, VSTOXX) on crude oil and natural gas markets during 1999–2015, and make the correlation dynamics dependent on conditional variance values through a threshold grid search algorithm. By detecting one endogenous break point in the raw series, we identify two clusters: one in 2008 and another in 2014, due to the financial crisis and the structural low oil prices linked to changing fundamentals, respectively. Also, the U.S. Henry Hub gas seems to be associated with the stock market volatility indexes, contrary to the European NBP gas, which is linked to the Brent. Besides, regarding the volatility behaviors of our series, the four energy variables violate their thresholds at similar moments, and the stock market VIX and VSTOXX exhibit logically similarities. Co-movements are detectable as well between the VIX and crude oil series, when investigating the volatility extracted from the GARCH model. In addition, the Block-DCC estimates provide ample evidence of similarities in the correlation dynamics between the crude oil and stock volatility series. It should be noted that the modeling framework proposed in this paper represents a useful tool for the study of cross-market contagion.     

Does the source of oil price shocks matter for South African stock returns? A structural VAR approach

In this paper, we investigate the dynamic relationship between different oil price shocks and the South African stock market using a sign restriction structural VAR approach for the period 1973:01 to 2011:07. The results show that for an oil-importing country like South Africa, stock returns only increase with oil prices when global economic activity improves. In response to oil supply shocks and speculative demand shocks, stock returns and the real price of oil move in opposite directions. The analysis of the variance decomposition shows that the oil supply shock contributes more to the variability in real stock prices. The main conclusion is that different oil price shocks affect stock returns differently and policy makers and investors should always consider the source of the shock before implementing a policy and making investment decisions.     

How does the U.S. natural gas market react to demand and supply shocks in the crude oil market?

In this paper we use monthly data (over the period from January 1976 to December 2012) and a structural VAR model to disentangle demand and supply shocks in the global crude oil market and investigate their effects on the real price of natural gas in the United States. We identify the model by assuming that innovations to the real price of crude oil are predetermined with respect to the natural gas market and show that close to 45% of the variation in the real price of natural gas can be attributed to structural supply and demand shocks in the global crude oil market.     

What happens to the relationship between EU allowances prices and stock market indices in Europe?

The stock market may reflect the economic conditions of an economy and a positive economic situation is expected to improve the companies' profits, which makes company shares more attractive since the expected dividends to shareholders will be larger. Theoretically, higher economic activity leads to higher energy demand and, consequently, higher carbon emissions, which give rise to higher EU allowances (EUA) prices. Therefore, the stock market and EUA prices seem to be connected, with causality going from the stock markets to EUA prices. This paper formally tests for it, showing that the causality effectively runs from the stock market to the European Climate Exchange market. Furthermore, the paper studies the effects of the evolution of European stock markets on the EUA spot prices.     

How is volatility in commodity markets linked to oil price shocks?

This study investigates the effects of oil price shocks on volatility of agricultural and metal commodities. We decompose an oil price shock to its underlying components, including macroeconomics and oil specific shocks. The applied method is the structural vector autoregressive (SVAR) model and the time span is from April 1983 to May 2014. The investigation is divided into two subsamples, before and after May 2006 for agriculture taking into account the 2006–2008 food crisis and change in U.S. ethanol production policy, and before and after January 2008 for metals considering the recent global financial crisis. We find that, based on impulse response functions, the response of volatility of each commodity to an oil price shock differs significantly depending on the underlying cause of the shock for the both periods. Moreover, according to variance decomposition the explanatory power of oil shocks becomes stronger after the crisis. The different responses of commodities are described in detail by investigating market characteristics in each period.