Oil Prices and Personal Consumption Expenditures: Does the Source of the Shock Matter?

This paper studies the effect of structural oil shocks on personal consumption expenditures (PCE). First, we estimate a nonlinear simultaneous equation model, compute impulse responses by Monte Carlo integration, and conduct a test of the symmetry of the impulse response functions. We find that aggregate PCE responds asymmetrically to positive and negative oil‐specific demand shocks. Second, we find that aggregate PCE responds negatively to positive oil demand shocks, while adverse oil supply shocks are of limited effect. Third, we find important heterogeneity in the magnitude, sign and timing of the disaggregate PCE responses to structural shocks in the crude oil market. Our results clearly indicate that the response of PCE to an unexpected oil price increase depends on the source of the oil price shock. Our findings are robust to different nonlinear transformations for the real price of oil.     

Economic uncertainty,oil prices,hedging and U.S. stock returns of the airline industry

This paper examines the impacts of economic policy uncertainty and oil price shocks on stock returns of U.S. airlines using both industry and firm-level data. Our empirical approach considers a structural vector-autoregressive model with variables recognized to be important for airline returns including jet fuel price volatility. Empirical results confirm that oil price increase, economic uncertainty and jet fuel price volatility have significantly adverse effect on real stock returns of airlines both at industry and at firm level. In addition, we also find that hedging future fuel purchase has statistically positive impact on the smaller airlines. Our results suggest policy implications for practitioners, managers of airline industry and commodity investors.     

Direct and indirect oil shocks and their impacts upon energy related stocks

We attempt to consolidate (at least in part) the vast literature on oil shocks and stock returns by decomposing the influence of oil shocks into two channels of effect: ‘direct’ and ‘indirect’. Using a simple empirical asset pricing model, it is shown that oil shocks can affect stocks not only directly, but also indirectly through general market risk (which is shown to be due in part to oil shocks), or put another way that additional oil price risk exposure is embedded in the traditional market beta. As far as is known this is the first paper explicitly quantifying both effects together. By doing so we offer a more complete picture of when and how oil shocks impact stock returns, thus allowing investors to make more informed responses to oil shocks. The results are illustrated using daily data from all (active) listed energy related stock portfolios in the Asia Pacific Region, and are robust to structural instability and the specification of oil shock used.     

Dynamic spillovers and linkages between gold,crude oil,S&P 500, and other economic and financial variables. Evidence from the USA

This paper focuses on the price determinants of gold, and on the challenges associated with gold’s safe haven property. Specifically, it analyses the interlinkages and the return spillover effect among gold, crude oil, S&P 500, dollar exchange rate, Consumer Price Index (CPI), economic policy uncertainty and Treasury bills, by employing a Vector Autoregression (VAR) and the spillover index of Diebold and Yilmaz (2012), Diebold and Yılmaz (2014). Monthly realized return series, covering the period from 2nd of January 1986 to 31st of December 2019 are used to examine the short-run linkages, and the return spillovers rolling-window estimates in analyzing the transmission mechanism in a time-varying fashion, respectively. Our findings identify gold as a strong dollar hedge, while crude oil and Treasury bills appear to drive inflation; they also indicate strong spillover effects between exchange rate and gold returns. In general, co-movement dynamics display state-dependent characteristics. Both total and directional spillovers increase significantly during market turbulence caused by severe financial crises such as the Global Financial Crisis (GFC) of 2007–2009 and the European Sovereign Debt Crisis of 2010–2012. Net spillovers switch between positive and negative values for all these markets, implying that the recipient/transmitter position changes drastically with market events. Economic policy uncertainty, stock market returns, and crude oil price returns are the main transmitters, while Treasury bills and CPI are the main return shock recipients. Gold and exchange rate act both as receivers and transmitters over the sample period.     

Conditional correlations and volatility spillovers between crude oil and stock index returns

This paper investigates the conditional correlations and volatility spillovers between the crude oil and financial markets, based on crude oil returns and stock index returns. Daily returns from 2 January 1998 to 4 November 2009 of the crude oil spot, forward and futures prices from the WTI and Brent markets, and the FTSE100, NYSE, Dow Jones and S&P500 stock index returns, are analysed using the CCC model of Bollerslev (1990), VARMA-GARCH model of Ling and McAleer (2003), VARMA-AGARCH model of McAleer, Hoti, and Chan (2008), and DCC model of Engle (2002). Based on the CCC model, the estimates of conditional correlations for returns across markets are very low, and some are not statistically significant, which means the conditional shocks are correlated only in the same market and not across markets. However, the DCC estimates of the conditional correlations are always significant. This result makes it clear that the assumption of constant conditional correlations is not supported empirically. Surprisingly, the empirical results from the VARMA-GARCH and VARMA-AGARCH models provide little evidence of volatility spillovers between the crude oil and financial markets. The evidence of asymmetric effects of negative and positive shocks of equal magnitude on the conditional variances suggests that VARMA-AGARCH is superior to VARMA-GARCH and CCC.     

Time-frequency causality and dependence structure between crude oil,EPU and Chinese industry stock: Evidence from multiscale quantile perspectives

This article investigates the time-frequency causality and dependence structure of Chinese industry stock returns on crude oil shocks and China's economic policy uncertainty (EPU) across quantiles over the period from January 2001 to June 2021. We use wavelet-based decomposition series to establish a multiscale causality-in-quantiles test and a quantile-on-quantile regression approach to reveal the complicated relationships involving crude oil, EPU and stock returns. Our empirical results are as follows: First, the predictability of crude oil and EPU on industry stock returns is significantly strong under extreme market conditions. Second, the explanatory ability of EPU on industry stock returns in the long term is stronger than EPU’s ability to explain short term returns. Third, the impacts of crude oil and EPU on industry stock returns remain remarkably asymmetric across quantile levels. Finally, nonenergy-intensive industries are also affected by crude oil shocks, but less than energy-intensive industries. Overall, these empirical findings can provide implications for policymakers to stabilize stock markets and investors to hedge the potential risks from crude oil and EPU.     

Heterogeneity dependence between oil prices and exchange rate: Evidence from a parametric test of Granger causality in quantiles

This paper re-examines the nexus between crude oil price and exchange rate by investigating their heterogeneity dependence structure within the framework of Granger causality in quantiles for a sample of developed and emerging economies (namely UK, Canada, Brazil, Russia, Mexico, Norway, India, Japan, South Africa, South Korea and European Union (EU)). The results indicate no distinct causality between the crude oil price changes and the real exchange rate returns for all countries besides Russia at the median of the conditional distribution. Besides, the crude oil price changes influence the exchange rate returns in all countries, except Norway and EU, particularly around the tails of the conditional distributions of exchange rate returns. This suggests that the oil price changes influence the real exchange rate returns when the real exchange rate returns are either in extreme appreciation or depreciation. Moreover, the crude oil price movement can be explained by the exchange rate returns for most oil importers only when the crude oil market is bearish or bullish. By contrast, the real exchange rate can permanently affect the crude oil price for most oil-importing countries irrespective of the crude oil market's state. Finally, our findings provide an essential reference for managing the extreme risk dependence between the exchange rate market and the crude oil market.     

Time-frequency effect of crude oil and exchange rates on stock markets in BRICS countries: Evidence from wavelet quantile regression analysis

This study examines the effects of oil prices and exchange rates on stock market returns in BRICS countries (Brazil, Russia, China, India and South Africa) from a time–frequency perspective over the period 2009–2020. We use wavelet decomposition series to develop a threshold rolling window quantile regression to detect time–frequency effects at various scales. The empirical results are as follows. First, our findings confirm that the effects of both crude oil prices and exchange rates on BRICS stock returns are asymmetric. Positive shocks of crude oil have a greater impact on a bull market, whereas negative shocks have a greater impact on a bear market. Second, there is a short-term enhancement effect of crude oil and exchange rate on BRICS stock markets. In addition, volatility in the macro financial environment also exacerbates the impacts of oil prices and exchange rates on the stock market, and these fluctuations are heterogeneous. Overall, these findings provide useful insights for international investors and policy makers.     

Does oil price variability affect the long memory and weak form efficiency of stock markets in top oil producers and oil Consumers? Evidence from an asymmetric MF-DFA approach

This study examines the asymmetric multifractality and the market efficiency of the stock markets in the countries that are the top crude oil producers (USA, KSA, Canada and Russia) and consumers (Brazil, China, India, and Japan) using an asymmetric multifractal detrended fluctuation analysis (A-MF-DFA) method. The results show evidence of an asymmetric multifractal nature for all markets. Moreover, the multifractality is stronger in the upward movement of the market returns, except in China. The degree of efficiency of the stock markets is shown to be time-varying and experienced a decrease during the 2008 global financial crisis (GFC), but an upside trend occurred during the recent oil price crash followed a significant decline during COVID-19. The stock markets have an anti-persistent feature during GFC and COVID-19, whereas they exhibit a long-term persistent feature during oil price crash. More interestingly, the efficiency of the stock markets of crude oil producers is lower in general than that of oil consumers. Furthermore, the efficiency of the stock market is lower in the downward movement of the market returns than in the upward movement. Asymmetry and oil price uncertainty index are the key driver of the stock markets and can serve as predictor of the stock market dynamics of top oil producers and top oil consumers particularly during COVID-19 and oil price crash.     

DISENTANGLING DEMAND AND SUPPLY SHOCKS IN THE CRUDE OIL MARKET: HOW TO CHECK SIGN RESTRICTIONS IN STRUCTURAL VARS

Sign restrictions have become increasingly popular for identifying shocks in structural vector autoregressive (SVAR) models. So far there are no techniques for validating the shocks identified via such restrictions. Although in an ideal setting the sign restrictions specify shocks of interest, sign restrictions may be invalidated by measurement errors, data adjustments or omitted variables. We model changes in the volatility of the shocks via a Markov switching (MS) mechanism and use this device to give the data a chance to object to sign restrictions. The approach is illustrated by considering a small model for the market of crude oil. Earlier findings that oil supply shocks explain only a very small fraction of movements in the price of oil are confirmed and it is found that the importance of aggregate demand shocks for oil price movements has declined since the mid 1980s. Copyright © 2013 John Wiley & Sons, Ltd.     

我国原油、煤炭和天然气的价格波动关系的研究——基于DCC-MVGARCH模型的实证分析

本文以原油、煤、天然气的价格收益率作为研究对象,运用DCC-MVGARCH模型,得出能源价格波动的动态相关系数,通过实证分析发现能源价格波动性的关系。结果表明,原油市场和煤炭市场波动性的动态相关系数随时间发展不断增长,原油市场和天然气市场波动性的相关系数比较稳定,煤炭市场和天然气市场波动性也比较稳定。     

Searching hedging instruments against diverse global risks and uncertainties

We evaluate the influence of five major risk and uncertainty factors on four asset classes. Our time-varying findings suggest that each asset hedges only a particular uncertainty factor, whereas gold does more than one factor, especially during COVID-19. Our frequency-based quantile regression (QR) results show that in the raw frequency, gold and Islamic stock can better hedge various uncertainty factors than Bitcoin and crude oil, depending on the market conditions. Additionally, using the frequency bands (e.g., short, medium, and long term) data, we further notice that, depending on the market circumstances and investment horizons, gold and Islamic stock returns are still better hedges for the various risks and uncertainties than Bitcoin and crude oil returns. Our findings have crucial risk and portfolio management implications for investors, portfolio managers, and policymakers.     

The economic and financial properties of crude oil: A review

In this article, we provide a structured review of crude oil price dynamics. Specifically, we summarize evidence on important factors determining oil prices, cover the impact of oil market shocks on the macro economy and the stock market, discuss how the financialization of crude oil markets affects oil market functionality and efficiency, and we then outline approaches for forecasting crude oil prices and volatility. By comparing the results of the most influential early contributions and recent studies, we can identify important developments and research gaps in each field. Thus, our review provides academics and practitioners newly engaging in crude oil research with an overview of what scientists know about crude oil dynamics and highlights which topics areparticularly promising for future research.     

Oil prices,stock returns,and exchange rates: Empirical evidence from China and the United States

Employing the diagonal BEKK model as well as the dynamic impulse response functions, this study investigates the time-varying trilateral relationships among real oil prices, exchange rate changes, and stock market returns in China and the U.S. from February 1991 to December 2015. We highlight several key observations: (i) oil prices respond positively and significantly to aggregate demand shocks; (ii) positive oil supply shocks adversely and significantly affect the Chinese stock market; (iii) oil price shocks persistently and significantly impact the trade-weighted US dollar index negatively; (iv) the US and China stock markets correlate positively just as the dollar index and the exchange rate does; (v) a significant parallel inverse relation exists between the US stock market and the dollar and between the China stock market and the exchange rate; and (vi) the Chinese stock market is more volatile and responsive to aggregate demand and oil price shocks than the US stock market in recent years.     

The nonlinear effect of oil price shocks on financial stress: Evidence from China

This paper examines the nonlinear effects of different types of oil price shocks on China’s financial stress index (FSI). For this purpose, we use newly proposed framework by Ready (2018) to decompose oil prices into supply, demand and risk shocks. Then, we use a Markov regime-switching (MRS) model to investigate the nonlinear effects of these oil price shocks on China’s FSI. The empirical results show that the effects of three oil price shocks are nonlinear under different regimes. In particular, oil supply shocks mainly have a significantly positive effect on China’s FSI in the low-volatility state; demand shocks have negative effects on China’s FSI in different regimes, but this effect is larger in the low-volatility state; the effect of risk shocks on China’s FSI is the opposite, and it is positive in the high-volatility state but negative in the low-volatility state.     

Visiting the effects of oil price shocks on exchange rates: Quantile-on-quantile and causality-in-quantiles approaches

We employ the relatively novel quantile-on-quantile and causality-in-quantiles approaches to empirically address the effects of oil price shocks on exchange rates of developed and developing countries. We find the evidence of the effects of oil shocks on exchange rates vary across quantiles. In addition, the effects and causality of oil price shocks are asymmetric and the slope of the coefficient in quantile-on-quantile analysis shows a relatively extreme fluctuation. Furthermore, for the developed currencies, the Granger causal relationship in both the mean and the variance running from oil shocks to exchange rates is always evident at all quantiles, while for the developing countries, the causal flow in the first and second moments is insignificant at middle quantiles.     

Economic policy uncertainty,oil price volatility and stock market returns: Evidence from a nonlinear model

This paper investigates the nonlinear relationship between economic policy uncertainty, oil price volatility and stock market returns for 25 countries by applying the panel smooth transition regression model. We find that oil price volatility has a negative effect on stock returns, and this effect increases with economic policy uncertainty. Furthermore, there is pronounced heterogeneity in responses. First, oil-exporting countries whose economies depend more on oil prices respond more strongly to oil price volatility than oil-importing countries. Second, stock returns of developing countries are more susceptible to oil price volatility than that of developed countries. Third, crisis plays a crucial role in the relation between oil price volatility and stock returns.     

Crude oil price dynamics with crash risk under fundamental shocks

Our paper presents a crude oil price model in which the price is confined in a wide moving band. A price crash occurs when the price breaches the lower boundary where a smooth-pasting condition is imposed. Using an asymmetric mean-reverting fundamental (supply/demand) shock, the solution derived from the oil price equation for the model shows the oil price follows a mean-reverting square-root process, which is quasi-bounded at the boundary. The oil price dynamics generates left-skewed price distributions consistent with empirical observations. A weakened mean-reverting force for the price increases the probability leakage for the price across the boundary and the risk of a price crash. The empirical results show the oil price dynamics can be calibrated according to the model, where the mean reversion of the price dynamics is positively co-integrated with the oil production reaction to negative demand shocks, and with the risk reversals of the commodity currencies, the Canadian dollar and the Australian dollar in currency option markets. The results are consistent with an increased price crash risk with negative demand shocks and negative risk reversals. The forecasting performance of the oil price model is better than the futures-spread models and random walk models during the crash periods. While the price of oil was above the lower boundary for most of the time, the conditions for breaching the boundary were met in 2008 and 2014 when the price fell sharply.     

Oil structural shocks,bank-level characteristics,and systemic risk: Evidence from dual banking systems

By performing a structural VAR analysis on oil price shocks, we provide an evidence on how the origins of oil price shocks impact the risk level of banks in oil-exporting countries and whether bank-level characteristics can influence the sensitivity of risk to oil shocks. When conducting panel regression analysis, we document the following findings. First, not all shocks have the same effect on bank risk. Due to oil supply shocks, the increase in oil price raises bank risk, whereas the similar increase in price due to economic expansion or oil-market specific demand reduces that risk. Second, the business model (whether the bank is Islamic or conventional), size, income diversification, profitability, and financial leverage influence the bank risk exposure to oil shocks differently. Third, the two major recent crises (global financial crises and COVID-19 pandemic) magnified bank risk exposure to oil supply shocks and speculative oil demand shocks. Overall, the structural oil shocks explain a large fraction of the variation in financial stability in GCC countries.     

THE ROLE OF INVENTORIES AND SPECULATIVE TRADING IN THE GLOBAL MARKET FOR CRUDE OIL

We develop a structural model of the global market for crude oil that for the first time explicitly allows for shocks to the speculative demand for oil as well as shocks to flow demand and flow supply. The speculative component of the real price of oil is identified with the help of data on oil inventories. Our estimates rule out explanations of the 2003–2008 oil price surge based on unexpectedly diminishing oil supplies and based on speculative trading. Instead, this surge was caused by unexpected increases in world oil consumption driven by the global business cycle. There is evidence, however, that speculative demand shifts played an important role during earlier oil price shock episodes including 1979, 1986 and 1990. Our analysis implies that additional regulation of oil markets would not have prevented the 2003–2008 oil price surge. We also show that, even after accounting for the role of inventories in smoothing oil consumption, our estimate of the short‐run price elasticity of oil demand is much higher than traditional estimates from dynamic models that do not account for for the endogeneity of the price of oil. Copyright © 2013 John Wiley & Sons, Ltd.