THE IMPACT OF OIL PRICE SHOCKS ON THE U.S. STOCK MARKET*

It is shown that the reaction of U.S. real stock returns to an oil price shock differs greatly depending on whether the change in the price of oil is driven by demand or supply shocks in the oil market. The demand and supply shocks driving the global crude oil market jointly account for 22% of the long‐run variation in U.S. real stock returns. The responses of industry‐specific U.S. stock returns to demand and supply shocks in the crude oil market are consistent with accounts of the transmission of oil price shocks that emphasize the reduction in domestic final demand.     

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.     

Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach

Crude oil price behaviour has fluctuated wildly since 1973 which has a major impact on key macroeconomic variables. Although the relationship between stock market returns and oil price changes has been scrutinized excessively in the literature, the possibility of predicting future stock market returns using oil prices has attracted less attention. This paper investigates the ability of oil prices to predict S&P 500 price index returns with the use of other macroeconomic and financial variables. Including all the potential variables in a forecasting model may result in an over-fitted model. So instead, dynamic model averaging (DMA) and dynamic model selection (DMS) are applied to utilize their ability of allowing the best forecasting model to change over time while parameters are also allowed to change. The empirical evidence shows that applying the DMA/DMS approach leads to significant improvements in forecasting performance in comparison to other forecasting methodologies and the performance of these models are better when oil prices are included within predictors.     

Hedging against bunker price fluctuations using petroleum futures contracts: constant versus time-varying hedge ratios

The effectiveness of hedging marine bunker price fluctuations in Rotterdam, Singapore and Houston is examined using different crude oil and petroleum future contracts traded at the New York Mercantile Exchange (NYMEX) and the International Petroleum Exchange (IPE) in London. Using both constant and dynamic hedge ratios, it is found that in and out-of-sample hedging effectiveness is different across regional bunker markets. The most effective futures instruments for out of sample hedging of spot bunker prices in Rotterdam and Singapore are the IPE crude oil futures, while for Houston it is the gas oil futures. Differences in hedging effectiveness across regional markets are attributed to the varying regional supply and demand factors in each market. In comparison to other markets, the cross-market hedging effectiveness investigated in the bunker market is low.     

基于ARIMA与GARCH模型的国际油价预测比较分析

在分析影响油价波动因素的基础上,利用1986年1月至2010年12月的WTI国际原油价格月度数据,分别建立ARIMA和GARCH模型对油价进行预测。并通过对2011年1月至2012年4月WTI原油价格进行外推预测,检验模型的预测效果。比较分析发现,在短期预测中,ARIMA和GARCH模型对油价的预测均比较准确,但当油价由于受到重大事件的影响而有较大波动时,模型的预测精度下降;在长期预测中,GARCH模型的预测效果优于ARIMA模型;整体来看,GARCH模型预测的精度高于ARIMA模型。因此,在国际油价预测中,用GARCH模型是比较合适的。     

我国石油安全战略体系的构建

随着中国经济的快速发展,我国国内石油生产已经远远不能满足经济社会发展的需要,进口石油量逐年增加,对国际石油市场依赖程度日益加深.由于国际油价的不断上涨以及国际局势风云突变,使我国石油进口增添了新的不确定因素.面对石油供应安全出现的新形势,本文以科学发展观为指导,就如何构建石油安全体系提出自己的看法.     

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.     

Responses to World Oil and Coal Shocks, in a Short-Run Fuel Substitution Tax Model

This article examines effects on major Australian macroeconomic and structural variables of simultaneous shocks to world oil and black coal prices. The illustrative numerical results have been produced with the short-run fuel substitution tax model, ORANI-LFT. The current version of that model reflects the Australian Governmet's pre-1988 oil regulatory framework, and the simulations reported in this study reflect the recent switch from significant dependence on crude oil levy revenue to petroleum products excise revenue. Empirical results show that combined world oil and coal price shocks lead to substantially different effects than would occur from an oil shock alone. A major implication of this, for a small open economy such as Australia, is that particular attention has to be paid to the interdependence of world energy market, both when analysing the effects of such shocks and when formulating appropriate macroeconomic and energy policy responses. It is also pointed out how the model could be modified for investigating effects under deregulated oil market regimes.     

Optimal cartel trigger price strategies

A dynamical model of industry equilibrium is described in which a cartel deters deviations from collusive output levels by threatening to produce at Cournot quantities for a period of fixed duration whenever the market price falls below some trigger price. In this model firms can observe only their own production level and a common market price. The market demand curve is assumed to have a stochastic component, so that an unexpectedly low price may signal either deviations from collusive output levels or a “downward” demand shock.     

Asset arbitrage and the price of oil

It is commonly understood that macroeconomic shocks influence commodity prices and that one channel for this is the link between interest rates, expected future asset returns and stock-holding. In this paper the link is extended to the petroleum market with the recognition that recorded stocks of oil comprise a small share of annual demand and that the parallel with storable commodities is the decision to produce the oil in the first place, as opposed to holding it in the ground as reserve. Oil reserves are then a key asset in producing countries, which is arbitraged against financial assets. Thus, when the yield on financial assets falls, retaining oil reserves becomes more attractive to producing countries, which then have less incentive to accommodate demand rises, and so the oil price rises. This perspective on oil pricing is modeled in a dynamic multi-region general equilibrium framework in which regional households manage portfolios of assets that include oil reserves. When the model is calibrated to match observed data over two decades, simulation results indicate that asset arbitrage made a large contribution to the high pre-GFC oil price.     

Crude Oil Futures as an Indicator of Market Changes: A Graphical Analysis

This study investigates the changing relationship between price and volume traded of short- and long-maturity NYMEX light sweet crude oil futures contracts and major changes in the physical crude oil market during the last decade. Monthly series for the #1-month to 84-month out maturity contracts are generated from daily price and volume data for NYMEX West Texas Intermediate (WTI) futures contracts for the period from January 2000 to the middle of 2009. 3-D graphical analysis of the futures prices, contract volumes, maturity dates, and time is used to demonstrate the changing trading volume pattern and evolution of the shape of futures price term structure across various contract maturities in different market regimes. The study observes the impacts of both May 2004, when excess production capacity reached nearly zero, and September 2006, when electronic trading was implemented on the NYMEX WTI futures markets. This analysis will be used to determine if futures contract information can provide an early indication of market regime shifts and improve short-run crude oil spot price forecast models.     

山东省原油自给能力预测与分析

基于1972—2009年山东省原油产量数据和1985—2009年山东省原油消费量数据,通过建立ARIMA(0,2,3)模型和ARIMA(2,1,2)模型,对2010—2015年山东省的原油产量和原油消费量进行了预测,旨在预测和分析2010—2015年山东省原油自给能力的变化趋势。结果表明:2010—2015年各年山东省的原油对外依存度将分别为46.85%、50.52%、54.97%、57.34%、58.75%和61.59%;山东省的原油自给能力将进一步降低。分析认为:山东省原油自给能力降低的主要原因是原油持续性生产受限和原油消费量持续性增长,因此需要通过利用国外市场协调、加大石油勘探力度、发展先进的勘探开发技术、提高石油资源加工转化效率以及加快替代能源开发利用等缓解此趋势。     

从石油的金融属性看我国石油价格与国际接轨

石油期货定价的金融属性是现代金融理论和国际石油市场共同发展的结果,然而,通过金融市场控制石油定价权符合西方垄断利益,石油美元体制操纵原油价格,国际石油期货市场监管存在漏洞,投机活动助推国际期货油价.国际油价的暴涨暴跌掩盖我国企业经营管理水平的低下,多次造成油荒.同时,油价接轨形成的巨额利润作为境外上市公司利润分红.严重损害国家利益.石油的国际定价机制面临重大改革,要逐步加强产油国、消费国的直接对接,形成与美国主导的能源金融体系抗衡的力量,夺取石油定价权.中国石油价格不应当毫无防范地与国际原油期货价格接轨,任由国际投机势力宰割.     

Non‐Linear Oil Price Dynamics: A Tale of Heterogeneous Speculators?

Abstract. While some of the recent surges in oil prices can be attributed to a robust global demand at a time of tight production capacities, commentators occasionally also blame the impact of speculators for part of the price pressure. We propose an empirical oil market model with heterogeneous speculators. Whereas trend-extrapolating chartists may tend to destabilize the market, fundamentalists exercise a stabilizing effect on the price dynamics. Using monthly data for West Texas Intermediate oil prices, our STR-GARCH estimates indicate that oil price cycles may indeed emerge due to the non-linear interplay between different trader types.     

The market power of OPEC 1973–2001

We apply a multi-equation dynamic econometric model on monthly data to test if the behaviour of OPEC as a whole or different sub-groups of the cartel is consistent with the characteristics of dominant producers on the world crude oil market in the period 1973–2001. Our results indicate that the producers outside OPEC can be described as competitive producers, taking the oil price as given and maximizing profits. The OPEC members do not fit the behaviour of price-taking producers. Our findings of low residual demand price elasticities for OPEC underpin the potential market power of the producer group, and are in line with the results in some recent energy studies. On the other hand, our findings indicate that neither OPEC nor different sub-groups of the cartel can be characterized as a dominant producer in the period 1973–1994. However, we find that the characteristics of a dominant producer to some extent fit OPEC-Core as from 1994. Thus, although OPEC clearly has affected the market price, the producer group has not behaved as a pure profit-maximizing dominant producer.     

The benefits of storage and non‐renewable resource price dynamics

Abstract Both the Theory of Storage and the Hotelling model play a prominent role in the study of non‐renewable resource prices. This paper combines these approaches by modifying the Hotelling model to allow firms to hold inventory in addition to in‐ground reserves, contributing three new results. First, inventory is more likely to be held if future demand and/or the marginal cost of extraction are uncertain. Second, the market price of the commodity is based on the Theory of Storage when inventory is held. Third, the optimal extraction of the resource is based on the Hotelling model.     

Forecasting demand for a newly introduced product using reservation price data and Bayesian updating

Forecasting demand during the early stages of a product's life cycle is a difficult but essential task for the purposes of marketing and policymaking. This paper introduces a procedure to derive accurate forecasts for newly introduced products for which limited data are available. We begin with the assumption that the consumer reservation price is related to the timing with which the consumer adopts the product. The model is estimated using reservation price data derived through a consumer survey, and the forecast is updated with sales data as they become available using Bayes's rule. The proposed model's forecasting performance is compared with that of benchmark models (i.e., Bass model, logistic growth model, and a Bayesian model based on analogy) using 23 quarters' worth of data on South Korea's broadband Internet services market. The proposed model outperforms all benchmark models in both prelaunch and postlaunch forecasting tests, supporting the thesis that consumer reservation price can be used to forecast demand for a new product before or shortly after product launch.     

Cyclical behavior of crude oil markets and economic recessions in the period 1986–2010

For at least one century, crude oil has been one of the most important commodities for the worldwide economic activity. Important technological innovations, including chemical transformation processes and transportation systems, have been based on the availability or not of crude oil. In this way, a close understanding of the crude oil market dynamics should provide insights in important aspects related to potential directions of technological change for both improving crude oil transformation efficiency and substitution by alternative energy sources. This paper studies the dynamics of the crude oil price for the period from 1986 to 2010. To this end, the entropy time-asymmetry is computed along the price trajectory. Empirical results indicated the presence of a non-regular cyclical behavior with a dominant period of about 4.5 years. Some evidences pointing toward a comovement of entropy time-asymmetry peaks with major US economic recessions are found, suggesting a tight relationship between macroeconomy and crude oil prices. The results are discussed in terms of the major economic events that occurred in the upward and downward cycle periods and potential implications for the design of energy policies.     

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.     

WELFARE COST OF AN OIL IMPORT FEE

This paper examines the impacts on the US. oil market of a $5-per-barrel tariff on imported crude oil. The analysis shows that the United States currently is a price taker in the world oil market. This means that "optimal tariff" arguments for an oil import fee have no validity. The author also argues that any economic losses that oil supply disruptions generate are better addressed with alternative policy tools. To forecast the effects of the tariff on US. production, the author uses a domestic oil supply model that she developed elsewhere. She calculates the resulting gains in producer surplus and then combines them with an estimate of consumer surplus losses and government revenues so as to yield an estimate of the tariff's welfare cost. This welfare cost amounts to approximately $17 billion (in present-value terms) over the 1988–1998 period.