Papers

• Do Better Volatility Forecasts Lead to Better Portfolios? Evidence from Graph Neural Networks (2026)
  Rylan Wade
  1.83
• Aligning Language Models with Investor and Market Behavior for Financial Recommendations (2025)
  Fernando Spadea and Oshani Seneviratne
  1.44
• Increase Alpha: Performance and Risk of an AI-Driven Trading Framework (2025)
  Sid Ghatak et al.
  1.39
• From Headlines to Holdings: Deep Learning for Smarter Portfolio Decisions (2025)
  Yun Lin et al.
  1.39
• A Distillation-based Future-aware Graph Neural Network for Stock Trend Prediction (2025)
  Zhipeng Liu et al.
  1.00
• Forecasting Financial Market Structure from Network Features using Machine Learning (2021)
  Douglas Castilho et al.
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• Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction (2023)
  Sheng Xiang et al.
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• Company2Vec -- German Company Embeddings based on Corporate Websites (2023)
  Christopher Gerling
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• Learning to Learn Financial Networks for Optimising Momentum Strategies (2023)
  Xingyue Pu et al.
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• DiffSTOCK: Probabilistic relational Stock Market Predictions using Diffusion Models (2024)
  Divyanshu Daiya et al.
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• Statistical arbitrage in multi-pair trading strategy based on graph clustering algorithms in US equities market (2024)
  Adam Korniejczuk et al.
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• Large-scale Time-Varying Portfolio Optimisation using Graph Attention Networks (2024)
  Kamesh Korangi et al.
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• Dynamic Portfolio Rebalancing: A Hybrid new Model Using GNNs and Pathfinding for Cost Efficiency (2024)
  Diego Vallarino
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