Forecasting volatility from econometric datasets is a crucial task in finance. To acquire meaningful predictions, various methods were built upon GARCH-type models, but these classical techniques suffer instability of short and volatile data. Recently, novel existing normalizing variance-stabilizing (NoVaS) method for predicting squared log-returns financial data was proposed. This model-free h...