In this paper we study the benefit of using the adaptive LASSO for predictive quantile regression. It is common that predictors in predictive quantile regression have various degrees of persistence and exhibit different signal strengths in explaining the dependent variable. We show that the adaptive LASSO has the consistent variable selection and the oracle properties under the simultaneous presence of stationary, unit root and cointegrated predictors. Some encouraging simulation and out-of-sample prediction results are reported.

翻译：在本文中,我们研究了利用适应性LASSO预测四分位回归的好处,预测性四分位回归中的预测者具有不同程度的持久性,在解释依附变量时表现出不同的信号强度。我们表明,适应性LASSO在固定、单位根和共集预测器同时存在的情况下,具有一致的变量选择和甲骨文特性。报告了一些令人鼓舞的模拟和模拟外预测结果。