We combine convolutional neural network (CNN) and gated recurrent unit (GRU) to form a new structure and embed it as a base layer in the autoencoder (AE) framework to efficiently extract features from financial time series data. To better utilize the hierarchical features, skip connection is...

Evidences from structural VAR show that new business formation positively co-moves with output under news shocks. The Jaimovich-Rebelo model augmented with firm dynamics can explain the empirical findings. The key assumption is endogenous survival rates for new entrants

For change-point analysis of high dimensional time series, we consider a semiparametric model with dynamic structural break factors. The observations are described by a few low dimensional factors with time-invariate loading functions of covariates. The unknown structural break in time models...