Forecasting Accuracy of Crude Oil Futures Prices
IMF Working Papers, October 1, 1991
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- Forecasting Accuracy of Crude Oil Futures Prices
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Bibliographic details
- Authors: Manmohan S. Kumar
- Published: October 1, 1991
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9781451951110.001
Research scope and objectives
- Investigates the efficiency of the crude oil futures market and the forecasting accuracy of futures prices.
- Analyses market efficiency in terms of the expected excess returns to speculation in the futures market.
- Compares accuracy of futures prices with forecasts from alternative techniques:
- time series models
- econometric models
- judgemental forecasts
- Explores predictive power of futures prices by comparing forecasting accuracy of end-of-month prices with weekly and monthly averages using a variety of different weighting schemes.
- Investigates whether forecasts based on futures prices can be improved by incorporating information from other forecasting techniques.
Key themes and analytical approaches
- Market efficiency measured via expected excess returns to speculation in the futures market.
- Forecasting accuracy comparisons across methods:
- Futures prices
- Time series and econometric models
- Judgemental forecasts
- Temporal aggregation and weighting schemes examined:
- End-of-month prices
- Weekly averages
- Monthly averages
- Various weighting schemes for averages
- Integration of information from multiple forecasting techniques to assess potential improvements in forecasts based on futures prices.
Subject areas and keywords
- Subject: Commodities, Econometric analysis, Econometric models, Financial institutions, Financial markets, Futures, Futures markets, Oil, Oil prices, Prices
- Keywords: crude oil, crude oil price, Econometric models, end-of-the-month price, forecasting accuracy, Futures, Futures markets, futures price forecast, futures prices accuracy, gasoline futures, moving average, Oil, oil futures prices, Oil prices, price of futures contracts, random walk, settlement price, time series, transactions price, WP, WTI price