Mitigating the choice of the duration in DDMS models through a parametric link
通过参数连接缓解持续期依赖 Markov 转换模型的持续期选择
One of the most important hyper-parameters in duration-dependent Markov-switching (DDMS) models is the duration of the hidden states. Because there is currently no procedure for estimating this duration or testing whether a given duration is appropriate for a given data set, an ad hoc duration choice must be heuristically justified. In this paper, we propose and examine a methodology that mitigates the choice of duration in DDMS models when forecasting is the goal. Two Monte…