This paper constructs a global anomaly index based on the 153 long-short portfolio returns of 33 stock markets. We find that global anomaly index is a strong negative predictor of future aggregate stock returns in international markets both in- and out-of-sample. It captures the common change in...

In this paper, we apply the BERT model, a cut-edging deep learning model, to construct a novel textual sentiment index in the Chinese stock market. By introducing the market returns as sentiment labels, our BERT model successfully extracts useful sentiment-related information contained in asset...

We propose a global expected business cycle condition factor (GEBC) relying on OECD leading economic indicators of 18 stock markets through Principal Component Analysis (PCA) approach, and show that this index is a powerful predictor for stock returns around the globe both in- and out-of-sample....