El Nino, La Nina, and the Forecastability of the Realized Variance of Heating Oil Price Movements

Abstract

We use the heterogenous autoregressive (HAR) model to compute out-of-sample forecasts of the monthly realized variance (RV) of movements of the spot and futures price of heating oil. We extend the HAR-RV model to include the role of El Nino and La Nina episodes, as captured by the Equatorial Southern Oscillation Index (EQSOI). Using data from June 1986 to April 2021, we show evidence for several model configurations that both El Nino and La Nina phases contain information useful for forecasting subsequent to the realized variance of price movements beyond the predictive value already captured by the HAR-RV model. The predictive value of La Nina phases, however, seems to be somewhat stronger than the predictive value of El Nino phases. Our results have important implications for investors, as well as from the perspective of sustainable decisions involving the environment.