This article explores the existing normalizing and variance-stabilizing (NoVaS) method on predicting financial volatility. First, we explore the robustness of the existing NoVaS method for long-term predictions. Then we develop a more parsimonious variant of the existing method. With systematic justification and extensive data analysis, our new method shows better performance than current NoVaS and standard GARCH(1,1) methods on both short- and long-term predictions.

翻译：本条探讨了用于预测金融波动的现有正常化和差异稳定(NoVaS)方法。 首先,我们探讨了现有用于长期预测的NOVaS方法的稳健性。 然后,我们开发了一种更难理解的现有方法的变体。有了系统化的理由和广泛的数据分析,我们的新方法比目前的NVaS和标准的GARCH(1,1)方法在短期和长期预测方面表现更好。