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Prospects for a Tighter World Oil Market

Edward W. Erickson

Year: 1985
Volume: Volume 6
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol6-No1-1
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Abstract:
Once again, the world oil market has failed to behave according to expectation. This time, the predictions of sharp price drops did not materialize-nor did previous forecasts of continuing escalation. This ongoing divergence between expectations and reality is becoming standard-as is the remarkable resiliency in the position and behavior of Saudi Arabia.



Historical Causes of Postwar Oil Shocks and Recessions

James D. Hamilton

Year: 1985
Volume: Volume 6
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol6-No1-9
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Abstract:
Turbulent petroleum markets and poor economic performance have been making headlines for the last decade. Three major oil shocks (1973-1974, 1979, and 1980-1981) have each been followed by major recessions. While the magnitude and violence of recent oil price changes are unique in postwar experience, the phenomenon of political instability producing disruptions in petroleum supply is not. Hamilton (1983a) observed that all but one of the recessions in the United States since World War II were preceded-typically by about nine months-by a dramatic increase in the price of crude petroleum (see Figure 1).



Reducing the Impacts of Energy Price Volatility Through Dynamic Portfolio Selection

H. Brett Humphreys and Katherine T. McClain

Year: 1998
Volume: Volume19
Number: Number 3
DOI: 10.5547/ISSN0195-6574-EJ-Vol19-No3-6
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Abstract:
This paper uses financial portfolio theory to demonstrate how the energy mix consumed in the United States could be chosen given a national goal to reduce the risky to the domestic macroeconomy of unanticipated energy price shocks. An efficient portfolio frontier of U.S. energy consumption is constructed using time-varying variances and covariances estimated with generalized autoregressive conditional heteroskedastic models. The set of efficient portfolios developed are intended to minimize the impact of price shocks, but are not the least cost energy consumption bundles. The results indicate that while the electric utility industry is operating close to the minimum variance position, a shift towards coal consumption would reduce price volatility for overall U.S. energy consumption. With the inclusion of potential externality costs, the shift remains away from oil but towards natural gas instead of coal.



Systematic Features of High-Frequency Volatility in Australian Electricity Markets: Intraday Patterns, Information Arrival and Calendar Effects

Helen Higgs and Andrew C. Worthington

Year: 2005
Volume: Volume 26
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol26-No4-2
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Abstract:
This paper investigates the intraday price volatility process in four Australian wholesale electricity markets; namely New South Wales, Queensland, South Australia and Victoria. The data set consists of half-hourly electricity prices and demand volumes over the period January 1, 2002 to June 1, 2003. A range of processes including GARCH, RiskMetrics, normal Asymmetric Power ARCH or APARCH, Student APARCH and skewed Student APARCH are used to model the time-varying variance in prices and the inclusion of news arrival as proxied by the contemporaneous volume of demand, time-of-day, day-of-week and month-of-year effects as exogenous explanatory variables. The skewed Student APARCH model, which takes account of right skewed and fat tailed characteristics, produces the best results in all four markets. The results indicate significant innovation (ARCH effects) and volatility (GARCH effects) spillovers in the conditional standard deviation equation, even with market and calendar effects included. Intraday prices also exhibit significant asymmetric responses of volatility to the flow of information.



Oil Price Volatility and Bilateral Trade

Shiu-Sheng Chen and Kai-Wei Hsu

Year: 2013
Volume: Volume 34
Number: Number 1
DOI: 10.5547/01956574.34.1.9
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Abstract:
This paper examines whether oil price volatility affects bilateral trade between two countries around the world. Using the gravity econometric model with 1,995 country-pairs covering 117 countries from 1984 to 2009, the empirical results suggest that oil price fluctuations significantly decrease bilateral trade volumes. The negative impact is more prominent the greater the distance between the two trading countries. As geographical distance is one of the measures of transport cost, our results also suggest that a potential channel through which oil price volatility hurts trade volumes is the uncertainty in transport cost.



OPEC’s Impact on Oil Price Volatility: The Role of Spare Capacity

Axel Pierru, James L. Smith, and Tamim Zamrik

Year: 2018
Volume: Volume 39
Number: Number 2
DOI: 10.5547/01956574.39.2.apie
View Abstract

Abstract:
OPEC claims to hold and use spare production capacity to stabilize the crude oil market. We study the impact of that buffer on the volatility of oil prices. After estimating the stochastic process that generates shocks to demand and supply, and assessing OPEC's limited ability to accurately measure and offset those shocks, we find that OPEC's use of spare capacity has reduced price volatility, perhaps by as much as half. We also apply the principle of revealed preference to infer the implicit loss function that rationalizes OPEC's investment in spare capacity and compare it to other estimates of the cost of crude oil supply shortfalls. That comparison suggests that OPEC's buffer capacity was in line with global macroeconomic needs.



Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence

Stavros Degiannakis, George Filis, and Vipin Arora

Year: 2018
Volume: Volume 39
Number: Number 5
DOI: 10.5547/01956574.39.5.sdeg
View Abstract

Abstract:
Do oil prices and stock markets move in tandem or in opposite directions? The complex and time varying relationship between oil prices and stock markets has caught the attention of the financial press, investors, policymakers, researchers, and the general public in recent years. In light of such attention, this paper reviews research on the oil price and stock market relationship. The majority of papers we survey study the impacts of oil markets on stock markets, whereas, little research in the reverse direction exists. Our review finds that the causal effects between oil and stock markets depend heavily on whether research is performed using aggregate stock market indices, sectorial indices, or firm-level data and whether stock markets operate in net oil-importing or net oil-exporting countries. Additionally, conclusions vary depending on whether studies use symmetric or asymmetric changes in the price of oil, or whether they focus on unexpected changes in oil prices. Finally, we find that most studies show oil price volatility transmits to stock market volatility, and that including measures of stock market performance improves forecasts of oil prices and oil price volatility. Several important avenues for further research are identified.Keywords: Oil prices, oil price volatility, stock markets, interconnectedness, forecasting, oil-importers, oil-exporters



Oil price volatility is effective in predicting food price volatility. Or is it?

Ioannis Chatziantoniou, Stavros Degiannakis, George Filis, and Tim Lloyd

Year: 2021
Volume: Volume 42
Number: Number 6
DOI: 10.5547/01956574.42.6.icha
View Abstract

Abstract:
Volatility spillovers between food commodities and oil prices have been identified in the literature, yet, there has been no empirical evidence to suggest that oil price volatility improves real out-of-sample forecasts of food price volatility. In this study we provide new evidence showing that oil price volatility does not improve forecasts of agricultural price volatility. This finding is based on extensive and rigorous testing of five internationally traded agricultural commodities (soybeans, corn, sugar, rough rice and wheat) and two oil benchmarks (Brent and WTI). We employ monthly and daily oil and food price volatility data and two forecasting frameworks, namely, the HAR and MIDAS-HAR, for the period 2nd January 1990 until 31st March 2017. Results indicate that oil volatility-enhanced HAR or MIDAS-HAR models cannot systematically outperform the standard HAR model. Thus, contrary to what has been suggested by the existing literature based on in-sample analysis, we are unable to find any systematic evidence that oil price volatility improves out-of-sample forecasts of food price volatility. The results remain robust to the choice of different out-of-sample forecasting periods and three different volatility measures.





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