Game-Theoretic Modeling of Heterogeneous Investor Interactions for Stock Price Forecasting
Accurate stock price forecasting has consistently remained a pivotal yet challenging FinTech task that underpins quantitative trading and investment decision making. Recent efforts have been dedicated to modeling various complex relationships among stocks in the stock market toward more reliable stock price forecasting.These methods depend heavily on strong static prior assumptions by modeling either temporal dependencies within individual stocks or spatial dependencies across different stocks based on predefined structures, while the complex market dynamics that drive stock price movements remain unexplored. To alleviate this issue, we propose a novel game-theoretic modeling method that ...
| Authors | Yong Zhang, Xinxiao Wu, Yunde Jia et al. |
|---|---|
| Primary category | q-fin.TR |
| Published | 11 May 2026 |
| Last updated at source | 11 May 2026 |
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