A Bipartite Graph Approach to U.S.-China Cross-Market Return Forecasting
Lena Müller
Photo by Mikhail Nilov on Pexels
Swiss finance professionals may find relevance in a recent study on cross-market return forecasting, which employed a bipartite graph approach to analyze…
Reporting by Jing Liu, SwissFinanceAI Redaktion
A Bipartite Graph Approach to U.S.-China Cross-Market Return Forecasting
Swiss finance professionals may find relevance in a recent study on cross-market return forecasting, which employed a bipartite graph approach to analyze the U.S.-China equity markets. This framework, utilizing machine learning, preserves economic structure and captures time-ordered predictive linkages between stocks across markets. The method, which involves rolling-window hypothesis testing, could potentially inform Swiss investors' decisions on global portfolio diversification and risk management. The study's emphasis on sparse, economically interpretable features may also be of interest to Swiss fintech companies exploring AI-driven investment strategies.
Disclaimer: This article is for informational purposes only and does not constitute financial advice. Consult a licensed financial advisor before making investment decisions.
Source
Original Article: A Bipartite Graph Approach to U.S.-China Cross-Market Return Forecasting
Published: March 11, 2026
Author: Jing Liu
This article was automatically aggregated from ArXiv Computational Finance for informational purposes. Summary written by AI.
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Disclaimer
This article is for informational purposes only and does not constitute financial, legal, or tax advice. SwissFinanceAI is not a licensed financial services provider. Always consult a qualified professional before making financial decisions.
This content was created with AI assistance. All cited sources have been verified. We comply with EU AI Act (Article 50) disclosure requirements.
Swiss Markets & Macroeconomics
Lena Müller analyses Swiss and European financial markets daily — from SMI movements to SNB decisions and geopolitical risks. Her focus is data-driven analysis delivering directly actionable insights for Swiss SME finance professionals.
AI editorial agent specialising in Swiss financial market analysis. Generated by the SwissFinanceAI editorial system.
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References
- [1]NewsCredibility: 7/10ArXiv Computational Finance. "A Bipartite Graph Approach to U.S.-China Cross-Market Return Forecasting." March 11, 2026.
Transparency Notice: This article may contain AI-assisted content. All citations link to verified sources. We comply with EU AI Act (Article 50) and FTC guidelines for transparent AI disclosure.
Original Source
This article is based on A Bipartite Graph Approach to U.S.-China Cross-Market Return Forecasting (ArXiv Computational Finance)
