6 papers
Janus-Q: End-to-End Event-Driven Trading via Hierarchical-Gated Reward Modeling
Xiang Li, Zikai Wei, Yiyan Qi +6
Financial market movements are often driven by discrete financial events conveyed through news, whose impacts are heterogeneous, abrupt, and difficult to capture under purely numer…
Unleashing Expert Opinion from Social Media for Stock Prediction
Wanyun Zhou, Saizhuo Wang, Xiang Li +3
While stock prediction task traditionally relies on volume-price and fundamental data to predict the return ratio or price movement trend, sentiment factors derived from social med…
Automated machine learning for physics-informed convolutional neural networks
Wanyun Zhou, Haoze Song, Xiaowen Chu
Recent advances in deep learning for solving partial differential equations (PDEs) have introduced physics-informed neural networks (PINNs), which integrate machine learning with p…
DeltaLag: Learning Dynamic Lead-Lag Patterns in Financial Markets
Wanyun Zhou, Saizhuo Wang, Mihai Cucuringu +5
The lead-lag effect, where the price movement of one asset systematically precedes that of another, has been widely observed in financial markets and conveys valuable predictive si…
FinKario: Event-Enhanced Automated Construction of Financial Knowledge Graph
Xiang Li, Penglei Sun, Wanyun Zhou +3
Individual investors are significantly outnumbered and disadvantaged in financial markets, overwhelmed by abundant information and lacking professional analysis. Equity research re…
QuantBench: Benchmarking AI Methods for Quantitative Investment
Saizhuo Wang, Hao Kong, Jiadong Guo +7
The field of artificial intelligence (AI) in quantitative investment has seen significant advancements, yet it lacks a standardized benchmark aligned with industry practices. This…