GARCHX-NoVaS: A Model-free Approach to Incorporate Exogenous Variables
GARCHX-NoVaS:纳入外生变量的无模型预测方法
In this work, we explore the forecasting ability of a recently proposed normalizing and variance-stabilizing (NoVaS) transformation with the possible inclusion of exogenous variables. From an applied point-of-view, extra knowledge such as fundamentals- and sentiments-based information could be beneficial to improve the prediction accuracy of market volatility if they are incorporated into the forecasting process. In the classical approach, these models including exogenous…