We show empirically that survey-based measures of expected inflation are significant and strong predictors of future aggregate stock returns in several industrialized countries both in-sample and out-of-sample. By empirically discriminating between competing sources of this return predictability...

This paper introduces a new predictive analytics model for forecasting stock price trends in financial assets traded on major stock exchanges worldwide and the Colombian Stock Exchange. The model is built on a probability space definition that consists of a measurable space derived from...

The work scrutinises the predictive prowess of ensemble machine learning models, namely Random Forest, Gradient Boosting, and XGBoost, in the domain of stock prediction by training models at two different stages. In stage 1, we restrict our evaluation to 18 technical indicators alongside holding...