Repository of NLP papers useful for applying NLP techniques to financial markets.
Direct applications of NLP research to financial markets.
- Analyzing Stock Market Movements Using Twitter Sentiment Analysis
- Deep Learning for Financial Sentiment Analysis on Finance News Providers
- Deep Learning for Stock Prediction Using Numerical and Textual Information
- Giving Content to Investor Sentiment: The Role of Media in the Stock Market
- The Impact of Structured Event Embeddings on Scalable Stock Forecasting Models
- Leverage Financial News to Predict Stock Price Movements Using Word Embeddings and Deep Neural Networks
- More Than Words: Quantifying Language to Measure Firms’ Fundamentals
- Predicting Stock Market Movement with Deep RNNs
- Predicting Stock Movement through Executive Tweets
- Sentiment Analysis in Financial News
- Sentiment Predictability for Stocks
- Textual Analysis of Stock Market Prediction Using Breaking Financial News: The AZFinText System
- Twitter mood predicts the stock market
- Natural Language Processing - Part 1: Primer
- An Analysis of Verbs in Financial News Articles and their Impact on Stock Prices
- Trading Strategies to Exploit Blog and News Sentiment
- From Word to Time Series Embedding
- The Effects of Conference Call Tones on Market Perceptions of Value Uncertainty
- The Capital Market Consequences of Language Barriers in the Conference Calls of Non-U.S. Firms
- Words versus Deeds: Evidence from Post-Call Manager Trades
- Linguistic Complexity in Firm Disclosures: Obfuscation or Information?
- When Managers Change Their Tone, Analysts and Investors Change Their Tune
- Buy-Side Analysts and Earnings Conference Calls
- Are Founder CEOs more Overconfident than Professional CEOs? Evidence from S&P 1500 Companies
- Speaking of the Short-Term: Disclosure Horizon and Managerial Myopia
- Finding Value in Earnings Transcripts Data with AlphaSense
- Using Unstructured and Qualitative Disclosures to Explain Accruals
- Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media
- Differences in Conference Call Tones: Managers Versus Analysts
- The Blame Game
- Can Investors Detect Managers’ Lack of Spontaneity? Adherence to Pre-determined Scripts during Earnings Conference Calls
- Predicting Returns with Text Data
Fundamental NLP research that could find applications in the financial markets. Fundamental research on Question Answering could be applied to credit analysis (default probability given a set of documents). Document Classification could be applied to ESG analysis to predict whether a company is sustainable or not. Sentiment Analysis could be applied to predict the impact a given document will have on the stock price.
- Reading Wikipedia to Answer Open Domain Questions
- Ask Me Anything: Dynamic Memory Network for Natural Language Processing
- Neural Generative Question Answering
- Question Answering Using Deep Learning
- Convolutional Neural Networks for Sentence Classification
- Enriching Word Vectors with Subword Information
- Fine-tuned Language Models for Text Classification
- From Word Embeddings To Document Distances
- Neural Text Generation: A Practical Guide
- A Deep Reinforcement Model for Abstractive Summarization
- Domain Adaptation using Stock Market Prices to Refine Sentiment Dictionaries
- Lancaster A at SemEval-2017 Task 5: Evaluation metrics matter and Code
- WayneDW/Sentiment-Analysis-in-Event-Driven-Stock-Price-Movement-Prediction
- v0d1ch/financial-news-scraper
- petrovsimeon/Financial-News-scraper
Contributions more than welcome :-)