5 citations · 9 across the 4 of their papers we have counts for
4 papers
Trend-encoded Probabilistic Multi-order Model: A Non-Machine Learning Approach for Enhanced Stock Market Forecasts
Peiwan Wang, Chenhao Cui, Yong Li
In recent years, the dominance of machine learning in stock market forecasting has been evident. While these models have shown decreasing prediction errors, their robustness across…
Are Crises Predictable? A Review of the Early Warning Systems in Currency and Stock Markets
Peiwan Wang, Lu Zong
The study efforts to explore and extend the crisis predictability by synthetically reviewing and comparing a full mixture of early warning models into two constitutions: crisis ide…
A Novel Distributed Representation of News (DRNews) for Stock Market Predictions
Ye Ma, Lu Zong, Peiwan Wang
In this study, a novel Distributed Representation of News (DRNews) model is developed and applied in deep learning-based stock market predictions. With the merit of integrating con…
An Integrated Early Warning System for Stock Market Turbulence
Peiwan Wang, Lu Zong, Ye Ma
This study constructs an integrated early warning system (EWS) that identifies and predicts stock market turbulence. Based on switching ARCH (SWARCH) filtering probabilities of the…