Using quantile regression, we evaluate the forecasting performance of futures prices in the soybean complex. The procedure provides a more complete picture of the distribution of forecasts than mainstream methods that only focus on central tendency measures. Forecast performance differs by location in the futures price distribution. Futures forecast perform well in the centre of the distribution. However, futures prices tend to over-forecast when futures prices are high and under-forecast when futures prices are low, suggesting that futures prices tend to under-estimate price reversion towards the centre of the distribution. Forecast errors are larger when futures prices are high. The findings are related to theories in the literature used to explain pricing bias, and their implications for market participants are discussed.
- futures markets
- quantile regression
ASJC Scopus subject areas
- Agricultural and Biological Sciences (miscellaneous)
- Economics and Econometrics