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....

This study proposes and validates “other information” in analysts' forecasts as a legitimate proxy for future cash flows, and examines its incremental role in explaining stock return volatility. We suggest that “other information” contains information about fundamentals beyond that...

The advantage of quantum mechanics to shift up the ability to econometrically understand extreme tail losses in financial data has become more desirable, especially in cases of Value at Risk (VaR) and Expected Shortfall (ES) predictions. Behind the non-novel quantum mechanism, it does...

We enhance the precision of predicting daily stock market price volatility using the maximum overlapping discrete wavelet transform (MODWT) spectral model and two learning approaches: the heuristic gradient descent (FS.HGD) and hybrid neural fuzzy inference system (HyFIS). The FS.HGD approach...