Carpe diem: Can daily oil prices improve model-based forecasts of the real price of crude oil?

Amor Aniss Benmoussa, Reinhard Ellwanger and Stephen Snudden

International Journal of Forecasting, 2026, vol. 42, issue 1, 281-295

Abstract: This paper proposes methods to include information from the underlying nominal daily series in model-based forecasts of average real series. We apply these methods to forecasts of the real price of crude oil. Models utilizing information from daily prices yield large forecast improvements and, in some cases, almost halve the forecast error compared to current specifications. We demonstrate for the first time that model-based forecasts of the real price of crude oil can outperform the traditional random walk forecast, that is, the end-of-month no-change forecast, at short forecast horizons.

Keywords: Forecasting Methods; Time Series Analysis; Temporal Aggregation; Oil Price Forecasts; Real-Time Data; Macroeconomic Forecasting (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:42:y:2026:i:1:p:281-295

DOI: 10.1016/j.ijforecast.2025.02.009

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