“…In this regard, it is important to note that measuring variance in terms of RV, defined as the sum of squared daily returns of prices observed over a given month (see [25]), provides an observable and unconditional metric of variance, which is otherwise a latent process. Accordingly, we differ from the existing literature (see for example, [26][27][28][29][30][31][32]) on modeling and forecasting heating oil volatility based on various types of univariate GARCH models, under which the conditional variance is a deterministic function of model parameters and historical data, and, hence, is not model-free as in the case of RV. Moreover, as discussed in [33,34], the benchmark HAR-RV model captures the generally observed long-memory and multi-scaling properties of volatility, despite having a simplistic structure.…”