Oil Price Shocks and Volatility in Australian Stock Returns

This paper examines the effect of oil shocks on return and volatility in the sectors of Australian stock market and finds significant effects for most sectors. For the overall market index, an increase in oil price return significantly reduces return, and an increase in oil price return volatility significantly reduces volatility. An advantage of looking at sector returns rather than a general index of stock returns is that sectors may well differ markedly in how they respond to oil price shocks. The energy and material sectors (as expected) and the financial sector (surprisingly) are out of step (in different ways) with results for the other sectors and for the overall index. A rise in oil price increases returns in the energy and material sectors and an increase in oil price return volatility increases stock return volatility in the financial sector. Explanation for the negative (positive) association between oil return (oil return volatility) and returns (volatility of returns) in the financial sector must be based on the association via lending to and/or holdings of corporate bonds issued by firms with significant exposure to oil price fluctuations and their speculative positions in oil‐related instruments.     

Oil prices and economic downturns: the case of Spain

We address the macroeconomic effects of an oil price shock in Spain. We apply a vector autoregression model (VAR) analysis to quarterly data for the Spanish economy since 1986, to elucidate the effects of variations in the oil price on the economy, considering the three main causes of disruptions in the oil markets: oil supply shocks, oil demand shocks and oil-specific (precautionary) demand shocks. We conclude that the effects in Spain strongly depend on the type of shock: the consumer price index (CPI) has mainly been influenced by oil demand shocks; output has only reacted to oil supply shocks; and monetary policy has mainly reacted after precautionary shocks. Second-round effects caused by the behaviour of nominal wages have not been found. Additionally, we discuss two facts: the ability of firms to increase markups in a context of rising demand and the procyclical role of monetary policy when faced with oil demand shocks.     

期权加油卡的产品设计、定价和套期保值研究

在消费者被迫接受成品油价格风险、石油零售商零售业竞争日益激烈和我国成品油定价机制矛盾日益突出的背景下,本文提出石油零售商可发行期权加油卡来实现下面三个目标:(1)为消费者提供成品油价格风险管理的工具;(2)为石油零售商提供一种新的锁定客户的营销手段;(3)推进成品油的市场化改革。本文首先设计期权加油卡,然后采用蒙特卡罗模拟方法对加油卡定价,接着分析石油零售商发行加油卡的风险的套期保值损益,最后讨论期权加油卡的相关实际操作问题。     

On the influence of US monetary policy on crude oil price volatility

Forecasting oil prices is not straightforward, such that it is convenient to build a confidence interval around the forecasted prices. To this end, the principal ingredient for obtaining a reliable crude oil confidence interval is its volatility. Moreover, accurate crude oil volatility estimation has fundamental implications in terms of risk management, asset pricing and portfolio handling. Generally, current studies consider volatility models based on lagged crude oil price realizations and, at most, one additional macroeconomic variable as crude oil determinant. This paper aims to fill this gap, jointly considering not only traditional crude oil driving forces, such as the aggregate demand and oil supply, but also the monetary policy rate. Thus, this work aims to contribute to the debate concerning the potential impact of (lagged) US monetary policy as well as the other crude oil future price (COFP) determinants on daily COFP volatility. By means of the recently proposed generalized autoregressive conditional heteroskedasticity mixed data sampling model, different proxies of the US monetary policy alongside US industrial production (proxy of the US aggregate demand) and oil supply are included in the COFP volatility equation. Strong evidence that an expansionary (restrictive) variation in monetary policy anticipates a positive (negative) variation in COFP volatility is found. We also find that a negative (positive) variation of industrial production increases (decreases) COFP volatility. This means that volatility behaves counter-cyclically, according to the literature. Furthermore, the out-of-sample forecasting procedure shows that including these additional macroeconomic variables generally improves the forecasting performance.     

Revisiting the oil price and stock market nexus: A nonlinear Panel ARDL approach

In this paper, we re-examine the relationship between oil price and stock prices in oil exporting and oil importing countries in the following distinct ways. First, we account for possible nonlinearities in the relationship in order to quantify the asymmetric response of stock prices of these two categories to positive and negative oil price changes. Secondly, in order to capture within group differences, we allow for heterogeneity effect in the cross-sections by formulating a nonlinear Panel ARDL model which is the panel data representation of the Shin et al. (2014) model and also analogous to the non-stationary heterogenous panel data model. Thirdly, we evaluate the relative predictability of the linear (symmetric) and nonlinear (asymmetric) Panel ARDL models using the Campbell and Thompson (2008) test. Our results depict that stock prices of both oil exporting and oil importing groups respond asymmetrically to changes in oil price although the response is stronger in the latter than the former. This finding is further corroborated by the out-of-sample forecast results suggesting that the inclusion of positive and negative oil price changes in the predictive model for stock prices will produce better forecast results only for the oil importing countries. Our results are robust to different oil price proxies, lag structure and in-sample periods. Overall, the dichotomy between oil exporting and oil importing countries has implications on oil price-stock nexus.     

The effects of oil price shocks on expenditure category CPI

In this study, we apply a two-block structural vector autoregressive (VAR) model proposed by Kilian and Park (2009) in order to investigate the dynamic effects of changes in oil price on the expenditure category consumer price index (CPI) in the United States and Japan. Our results confirm that each expenditure category price index responded very differently to the same structural shock, and that whether changes in oil price function as a positive stimulus or a negative shock for the individual expenditure category prices also depends on the kind of underlying shock that drives the changes in oil price. Finally, our results also reveal that the manner in which changes in oil price affect each expenditure category price differs between the United States and Japan and these detailed-level differences may lead to aggregate-level differences in the price response of both countries to changes in oil price.     

Assessing dynamics of crude oil import demand in Korea

Although Korea was the world's seventh largest oil consumer and fourth largest oil importer, relatively little attention has been paid to empirical analyses of the Korean crude oil market. In this paper, we have attempted to expand the scope of previous literature by examining Korea's import demand for crude oil in a dynamic framework of cointegration. The empirical focus is on assessing the short- and long-run relationships among volume of crude oil import, economic growth and price of imported crude oil in Korea. For this purpose, an autoregressive distributed lag (ARDL) approach is applied to quarterly data for 1986–2010. Results show that income level is a more powerful determinant of the long-run behavior of Korea's crude oil imports than crude oil price. In the short-run, on the other hand, oil price is found to play a more important role in determining crude oil imports than income level.     

Does international oil volatility have directional predictability for stock returns? Evidence from BRICS countries based on cross-quantilogram analysis

While numerous studies have investigated the relationship between oil volatility and stock returns, it is surprising that little research has examined the quantile dependence and directional predictability from oil volatility to stock returns in BRICS (Brazil, Russia, India, China, and South Africa) countries. We address this issue by using the cross-quantilogram model proposed by Han et al. (2016). The empirical results show that, overall, oil volatility has a directional predictability for the stock returns in BRICS countries. When the oil volatility is in a low quantile (lower than its 0.1 quantiles), it is less likely to show either a large loss or a large gain in the stock market. In contrast, there is an increased likelihood of either large loss or a large gain in the stock market when the oil volatility is in a high quantile (higher than its 0.9 quantiles). The directional predictability from the oil volatility to stock returns depends on the net position of oil imports and exports of these BRICS countries in the oil market. The net oil exporters (Russia and Brazil) are less likely to have large gains and large losses in the stock market than are the net oil importers (India, China, and South Africa) when the oil volatility is in a low quantile. The net oil exporters are more likely to have large gains and large losses than are the net oil importers when the oil volatility is in a high quantile. The results are robust to change in the variable of oil volatility and the sample interval.     

U.S. industry-level returns and oil prices

This paper empirically investigates and provides further support for the oil price effect documented in Driesprong et al. (2008) in the U.S. industry-level returns. We find that oil price predictability is concentrated in a relatively small number of industry-level returns, the relevant measure for a study of the oil effect is percentage change in oil spot prices, and changes in oil futures prices have virtually no prediction power for industry-level returns. With percentage changes in oil spot prices as the predictor, approximately one fifth of industry returns are oil-predictable. We detect a two trading weeks delay in reaction to oil price changes which is consistent with the Hong and Stein (1996) underreaction hypothesis. These results are robust to various alternative specifications, and are shown to be unrelated to time-varying risk premia. Moreover, we demonstrate that trading strategies based on the oil effect generate superior gains in comparison with buy-and-hold strategy in the presence of reasonable trading costs.     

Forecasting realized volatility of crude oil futures with equity market uncertainty

This paper examines whether the equity market uncertainty (EMU) index contains incremental information for forecasting the realized volatility of crude oil futures. We use 5-min high-frequency transaction data for WTI crude oil futures and develop six heterogeneous autoregressive (HAR) models based on classical HAR-type models. The empirical results suggest that EMU contains more incremental information than the economic policy uncertainty (EPU) for forecasting the realized volatility of crude oil futures. More importantly, we argue that EMU is a non negligible additional predictive variable that can significantly improve the 1-day ahead predictive accuracy of all six HAR-type models, and improve the 1-week ahead forecasting performance of the HAR-RV, HAR-RV-J, HAR-RSV, HAR-RV-SJ models. These findings highlight a strong short-term and a weak mid-term predictive ability of EMU in the crude oil futures market.     

The effects of oil shocks on government expenditures and government revenues nexus (with an application to Iran's sanctions)

The main purpose of this study is to investigate the dynamic relationship between government revenues and government expenditures in Iran as a developing oil export based economy. Moreover, I want to know how oil price (revenue) shocks can affect this relationship. The results of the impulse response functions and variance decomposition analysis indicate that the contribution of oil revenue shocks in explaining the government expenditures is stronger than the contribution of oil price shocks. Moreover the results of the vector autoregression (VAR) and vector error correction (VEC) models show that the strong causality is running from government revenues to government expenditures (both current and capital) in Iranian economy while the evidence for the reverse causality is very weak. Overall the results support the revenue–spending hypothesis for Iran. My results imply that those sanctions aiming to restrict the Iranian government's oil export revenues, potentially can affect the government total expenditures as an important engine for developing the Iranian economy.     

Risk assessment of oil price from static and dynamic modelling approaches

The price gap between West Texas Intermediate (WTI) and Brent crude oil markets has been completely changed in the past several years. The price of WTI was always a little larger than that of Brent for a long time. However, the price of WTI has been surpassed by that of Brent since 2011. The new market circumstances and volatility of oil price require a comprehensive re-estimation of risk. Therefore, this study aims to explore an integrated approach to assess the price risk in the two crude oil markets through the value at risk (VaR) model. The VaR is estimated by the extreme value theory (EVT) and GARCH model on the basis of generalized error distribution (GED). The results show that EVT is a powerful approach to capture the risk in the oil markets. On the contrary, the traditional variance–covariance (VC) and Monte Carlo (MC) approaches tend to overestimate risk when the confidence level is 95%, but underestimate risk at the confidence level of 99%. The VaR of WTI returns is larger than that of Brent returns at identical confidence levels. Moreover, the GED-GARCH model can estimate the downside dynamic VaR accurately for WTI and Brent oil returns.     

Optimization agricultural production under financial risk of water constraint in the Jordan Valley

Using high-frequency data the co-movements among crude oil prices are analysed in order to address the question of regionalization of the world crude oil market. Time-series econometrics in the form of error-correction modelling is applied for daily crude oil price data covering the time period 1988 to 2004 and in this framework topics like weak and strong exogeneity among three major oil prices – represented by Brent, OPEC and Texas (WTI) – are addressed. The empirical results are that causality is most likely bi-directional among these crude oil prices – and hence rejecting a regionalization hypothesis of the global oil market – and also an influence from the OPEC oil price towards Bent and WTI, which are usually claimed to have a benchmark role.     

An investigation into the dynamic relationship between international and China’s crude oil prices

This article studies the dynamic relationship between international (WTI, Brent and Dubai) and domestic (Da Qing) crude oil prices in China using threshold cointegration method. We find evidence of a long-run equilibrium relationship between each pair of international and Da Qing oil prices, favouring the market integration hypothesis. We also estimate asymmetric adjustments under the momentum threshold autoregressive (M-TAR) specification in a TVECM, and the results show that adjustments to eliminate disequilibrium happen faster when oil price spread increases than when it decreases. The long-run and short-run Granger causality tests support the notion that China has influence on the international oil markets. The results imply that China should open up its domestic and imported oil markets, and also establish a well-functioning crude oil futures market, as they are essential for arbitrage and hedging strategies.     

Oil supply and economic development strategy: A dynamic planning approach

Most oligopolistic models of the oil market begin with the assumption of rising supply curves for oil. Lack of convincing evidence that high oil prices are being maintained by oligopolistic action has raised the possibility of competitive behavior in the oil market and therefore of a backward bending supply curve. This paper presents numerical solutions of a linear dynamic planning model of an oil exporting country with a development strategy which consists of utilizing oil revenues for building an export sector to replace oil. To make a stronger case a high absorber, Algeria, is used as an example. The numerical results are consistent with the hypothesis that there may well be good economic reasons to restrict supply of oil in response to increased prices. Three important characteristics of the model which produce this result are (a) diminishing marginal utility of consumption, (b) absorptive capacity, and (c) imperfect capital markets. A ‘perverse’ supply behavior is found consistent with optimal allocation of oil resources when a price increase is expected to last for a long time. The effects of temporary price changes which can, for example, result from temporary supply shocks or demand changes during the business cycle are also studied. It is shown that in response to such short term price changes competitive behavior is ‘normal’, i.e., supply varies in the same direction as the price. This implies that reductions in OPEC production which have taken place during the recent market downturns cannot be taken as evidence of cartel coordination, as they usually are, since they are also consistent with price-taking behavior.     

The case of Japan: Price bargaining and controls on oil products

This paper shows how the Japanese variant of indicative planning has dealt with the oil crisis. Goals for leading export industries and for income distribution have been promoted through “administered competition” (a key policy in the strong economic growth of the 1960s) and pricing policies (including selective controls). The “price-bargaining” mechanism (aided by sociopolitical forces) has proved effective in oil products, even under floating exchange rates. One noteworthy policy alteration is the encouragement of sales in Japan by large foreign oil companies but under constraints that tie their interests more closely to those of Japan.     

India’s petroleum demand: estimations and projections

Energy security is crucial for sustaining high economic growth in India. This article empirically estimates India’s long- and short-term demand relations for crude oil, diesel and petrol (gasoline) using the ARDL and ECM cointegration procedures and then uses them to project demand for these products up to 2025 under various scenarios of GDP growth and oil prices. Our projections show that over 2012 to 2025, demand is likely to increase by about 74% for crude oil, 117% for diesel and 136% for petrol – the annual growth rates being about 4.3% for crude oil, 6.1% for diesel and 6.8% for petrol (gasoline). This article suggests that India needs to (1) take measures to improve efficiency in the use of petroleum products; (2) try to enhance supplies such as through production sharing agreements by Indian oil companies with other countries and (3) increase the use of nuclear, hydro, solar and other alternative energy sources, as Western European countries have done.     

Return and volatility transmission between oil prices and oil-exporting and oil-importing countries

This paper provides further evidence of the comovements and dynamic volatility spillovers between stock markets and oil prices for a sample of five oil-importing countries (USA, Italy, Germany, Netherland and France) and four oil-exporting countries (United Arab Emirates, Kuwait, Saudi Arabia and Venezuela). We make use of a multivariate GJR-DCC-GARCH approach developed by Glosten et al. (1993). The results show that: i) dynamic correlations do not differ for oil-importing and oil-exporting economies; ii) cross-market comovements as measured by conditional correlation coefficients increase positively in response to significant aggregate demand (precautionary demand) and oil price shocks due to global business cycle fluctuations or world turmoil; iii) oil prices exhibit positive correlation with stock markets; and iv) oil assets are not a good ‘safe haven’ for protection against stock market losses during periods of turmoil.     

Projections of oil demand in road transportation sector on the basis of vehicle ownership projections,worldwide: 1972–2020

Oil demand in the road transportation section accounts for more than 50% of total world oil consumption amongst the whole sectors, including road, aviation, railway, waterways and international marine transportation. The high demand rate of oil makes this sector the main and major oil consumer in the world. The vehicle ownership or intensity of vehicles is one of the main factors which determines the development of oil demand in this major sector.Vehicle ownership (in 1000 population) is estimated using the nonlinear Gompertz model on the basis of pooled time series (1972–2020) and cross-sections data for 154 countries. Different saturation levels for the selected countries and over time horizon is calculated by adding specific demographic and geographic variables. Then, under two different scenarios – business as usual and policy scenario – we make projections of oil demand in the road transportation sector across 154 countries by using available data up to 2020.According to the results of the model, it is predicted that the number of world total vehicles will be approximately 1.5 times higher in 2020 than in 2008. Moreover, oil demand projections for road transportation over 2009–2020 show that under business as usual scenario, world oil demand will increase to 14,748 million barrel of oil equivalent until 2020 while under the policy scenario, which is based on the fuel efficiency improvement by 20% during a period of 10 years until 2020, world oil demand in the aforementioned sector will increase only to 11601 mboe until 2020.