mlsanityData to 14 Oct 2026

Modeling News Interactions and Influence for Financial Market Prediction

arXiv 2410.10614 ↗First posted 14 Oct 2024cs.CE cs.AI cs.CLcited by 6

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Abstract (arXiv)

The diffusion of financial news into market prices is a complex process, making it challenging to evaluate the connections between news events and market movements. This paper introduces FININ (Financial Interconnected News Influence Network), a novel market prediction model that captures not only the links between news and prices but also the interactions among news items themselves. FININ effectively integrates multi-modal information from both market data and news articles. We conduct extensive experiments on two datasets, encompassing the S&P 500 and NASDAQ 100 indices over a 15-year period and over 2.7 million news articles. The results demonstrate FININ's effectiveness, outperforming advanced market prediction models with an improvement of 0.429 and 0.341 in the daily Sharpe ratio for the two markets respectively. Moreover, our results reveal insights into the financial news, including the delayed market pricing of news, the long memory effect of news, and the limitations of financial sentiment analysis in fully extracting predictive power from news data.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 11 of its 53 references that are in the map. First posted on arXiv 14 Oct 2024.

Builds on

11 of 53 references.

References · 11

  1. 2017Attention Is All You Needcited by 60,361
  2. 2023GPT-4 Technical Reportcited by 18,396
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  4. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  5. 2019FinBERT: Financial Sentiment Analysis with Pre-trained Language Modelscited by 385
  6. 2020Reinforcement-Learning based Portfolio Management with Augmented Asset Movement Prediction Statescited by 55
  7. 2020Applications of deep learning in stock market prediction: recent progresscited by 51
  8. 2021REST: Relational Event-driven Stock Trend Forecastingcited by 30
  9. 2020A Novel Ensemble Deep Learning Model for Stock Prediction Based on Stock Prices and Newscited by 16
  10. 2024MANA-Net: Mitigating Aggregated Sentiment Homogenization with News Weighting for Enhanced Market Predictioncited by 6
  11. 2019Transformation of Dense and Sparse Text Representationscited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 3.

6 papers.

  1. 2025From Deep Learning to LLMs: A survey of AI in Quantitative Investmentcited by 9
  2. 2025FinGEAR: Financial Mapping-Guided Enhanced Answer Retrievalcited by 5
  3. 2026FinSafetyBench: Evaluating LLM Safety in Real-World Financial Scenarioscited by 3
  4. 2025Exploring the Synergy of Quantitative Factors and Newsflow Representations from Large Language Models for Stock Return Predictioncited by 2
  5. 2026Summoning the Oracle to Slay It: Mitigating Look-Ahead Bias in Financial Backtesting with Large Language Modelscited by 2
  6. 2026Self Knowledge Re-expression: A Fully Local Method for Adapting LLMs to Tasks Using Intrinsic Knowledgecited by 1