This paper proposes a new forecasting framework for the stock market that combines machine learning algorithms with several technical analyses. The paper considers three different algorithms: the Random Forests (RF), the Gradient-boosted Trees (GBT), and the Deep Neural Networks (DNN), and...

This study examines the effect of carbon price uncertainty on stock price crash risk. Utilizing the dynamic panel model on the data of Chinese listed firms from 2011 to 2018, we find that high carbon price uncertainty increases stock price crash risk. The impact of carbon price uncertainty is...