Using the long-term wavelet component of monthly S&P 500 excess returns as supervision information, we employ a machine learning method to extract the common predictive information of 14 prevalent macroeconomic variables, and construct a new macroeconomic index aligned for predicting stock...

This paper combines quantile regression withtime-varying vector autoregressive model to study extreme spillover effects among high carbon emission stocks, green bond and WTI crude oil from April 21, 2010 to March 25, 2022.The results display a static total spillover index of approximately 49% at...

Using the long-term wavelet component of monthly S&P500 excess returns as supervision information, we employ a partial least squares method to extract the common predictive information of 14 prevalent macroeconomic variables, and construct a new macroeconomic index aligned for predicting stock...