# Leverage Financial News to Predict Stock Price Movements Using Word Embeddings and Deep Neural Networks

arXiv: https://arxiv.org/abs/1506.07220 · HTML: https://mlsanity.com/paper/1506.07220/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Jun 2015.

## Built on by (most cited first, 7 of 7)

- [FinGPT: Democratizing Internet-scale Data for Financial Large Language Models](https://mlsanity.com/paper/2307.10485/) (2023)
- [FinDPO: Financial Sentiment Analysis for Algorithmic Trading through Preference Optimization of LLMs](https://mlsanity.com/paper/2507.18417/) (2025)
- [Stock Market Analysis with Text Data: A Review](https://mlsanity.com/paper/2106.12985/) (2021)
- [Multimodal Stock Price Prediction](https://mlsanity.com/paper/2502.05186/) (2025)
- [Hierarchical Organization Simulacra in the Investment Sector](https://mlsanity.com/paper/2410.00354/) (2024)
- [A three-step machine learning approach to predict market bubbles with financial news](https://mlsanity.com/paper/2510.16636/) (2025)
- [FinSMART: Financial Sentiment Analysis for Algorithmic Trading through Market-Aligned Reinforcement Learning](https://mlsanity.com/paper/2607.28127/) (2026)

## Abstract (arXiv)

Financial news contains useful information on public companies and the market. In this paper we apply the popular word embedding methods and deep neural networks to leverage financial news to predict stock price movements in the market. Experimental results have shown that our proposed methods are simple but very effective, which can significantly improve the stock prediction accuracy on a standard financial database over the baseline system using only the historical price information.