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

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 for the period covering 1986:06 to 2021:04, we document evidence for several model configurations that both El Nino and La Nina phases contain information useful for forecasting subsequent 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.