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This paper undertakes an investigation into the efficiency of the crude oil futures market and the forecasting accuracy of futures prices. Efficiency of the market is analysed in terms of the expected excess returns to speculation in the futures market. Accuracy of futures prices is compared with that of forecasts using alternative techniques, including time series and econometric models, as well as judgemental forecasts. The paper also explores the predictive power of futures prices by comparing the forecasting accuracy of end-of-month prices with weekly and monthly averages, using a variety of different weighting schemes. Finally, the paper investigates whether the forecasts from using futures prices can be improved by incorporating information from other forecasting techniques.
This paper undertakes an investigation into the efficiency of the crude oil futures market and the forecasting accuracy of futures prices. Efficiency of the market is analysed in terms of the expected excess returns to speculation in the futures market. Accuracy of futures prices is compared with that of forecasts using alternative techniques, including time series and econometric models, as well as judgemental forecasts. The paper also explores the predictive power of futures prices by comparing the forecasting accuracy of end-of-month prices with weekly and monthly averages, using a variety of different weighting schemes. Finally, the paper investigates whether the forecasts from using futures prices can be improved by incorporating information from other forecasting techniques.
The paper makes an original contribution to the electricity market literature by using an international sample to explore the efficiency of electricity futures across different markets. We focus on the efficiency of five futures markets (Australia, Germany, New Zealand, Nord Pool and the PJM Interconnection) between 2002 and 2016. Our analysis has three components; first we explore the validity of the unbiasedness hypothesis in this context; second, we test the forecast power of futures prices; and; third we explore market characteristics as determinants of efficiency. Our analysis of the unbiasedness hypothesis finds that the German and New Zealand markets are the only efficient markets for the entire sample, even though they are at the two extremes in terms of liquidity and market maturity. When testing the forecast power, all futures markets outperform naïve forecasts and the predictability seems to be improving as markets mature, except for the U.S. futures which show a decline. The generating mix does not seem to affect forecastability. We find that market efficiency is time varying, mostly improving with market maturity and is related to risk and liquidity factors.
"This paper examines the relationship between spot and futures prices for energy commodities (crude oil, gasoline, heating oil markets and natural gas). In particular, we examine whether futures prices are (1) an unbiased and/or (2) accurate predictor of subsequent spot prices. We find that while futures prices are unbiased predictors of future spot prices, with the exception those in the natural gas markets at the 3-month horizon. Futures do not appear to well predict subsequent movements in energy commodity prices, although they slightly outperform time series models"--National Bureau of Economic Research web site.
Fluctuations of commodity prices, most notably of oil, capture considerable attention and have been tied to important economic effects. This book advances our understanding of the consequences of these fluctuations, providing both general analysis and a particular focus on the countries of the Pacific Rim.
This book concerns the use of concepts from statistical physics in the description of financial systems. The authors illustrate the scaling concepts used in probability theory, critical phenomena, and fully developed turbulent fluids. These concepts are then applied to financial time series. The authors also present a stochastic model that displays several of the statistical properties observed in empirical data. Statistical physics concepts such as stochastic dynamics, short- and long-range correlations, self-similarity and scaling permit an understanding of the global behaviour of economic systems without first having to work out a detailed microscopic description of the system. Physicists will find the application of statistical physics concepts to economic systems interesting. Economists and workers in the financial world will find useful the presentation of empirical analysis methods and well-formulated theoretical tools that might help describe systems composed of a huge number of interacting subsystems.