Our Process
Distilling the impact of information on markets
With accessible datafeeds, applications, and AI tools
1
Investors form opinions based on news, research, transcripts, and online discussions
2
Media & Corporate Reporting deliver new information and amplify opinions, creating feedback loops
3
MarketPsych’s Text Tagging Engine provides AI-assisted analytics across millions of news articles, filings, transcripts, and online posts in real-time
4
Datasets & Analytic Tools are created by identifying key themes and sentiments expressed about millions of entities across time frames
5
Workflows supported include alpha generation, research, ESG, monitoring, and risk management
6
Web App & Python Notebooks render analytics easily utilized with visualizations, web tools, code samples, and predictive models
Our Mission
Empowering Finance through NLP and AI Solutions
What We Do
Since 2004 MarketPsych has been leading research into natural language processing (NLP) and AI for financial applications. We are known for producing high-quality, rigorous, and point-in-time sentiment data. And we do much more…
We help organizations extract value and insights from large amounts of text - quickly and easily. Our products enhance client returns, reduce risk, and unearth key insights. Our clients are among the most sophisticated investment funds, banks, research firms, and agencies globally.
Our analytics identify and publish thousands of events, topics, perceptions, and sentiments in the information flow about millions of entities and assets. We map assets point in time across all common identifiers.
We help organizations extract value and insights from large amounts of text - quickly and easily. Our products enhance client returns, reduce risk, and unearth key insights. Our clients are among the most sophisticated investment funds, banks, research firms, and agencies globally.
Our analytics identify and publish thousands of events, topics, perceptions, and sentiments in the information flow about millions of entities and assets. We map assets point in time across all common identifiers.
Our Team
MarketPsych is a contraction of Market Psychology. Our team’s background is rooted in quantitative finance, behavioral economics, and technology. We share a passion for advancing AI technology, finance research, and having a positive impact.
As quantitative analysts, our founders identified a hole in traditional financial data. If information flow moved markets, where could a quant find reliable data reflecting the beliefs, expectations, and events moving markets - market psychology? Over the next 20 years our team endeavored to produce the most reliable and robust sentiment and event data from unstructured text.
As quantitative analysts, our founders identified a hole in traditional financial data. If information flow moved markets, where could a quant find reliable data reflecting the beliefs, expectations, and events moving markets - market psychology? Over the next 20 years our team endeavored to produce the most reliable and robust sentiment and event data from unstructured text.
Check out our books on behavioral markets
Clients with Public Testimonials
Academic Papers Published With Our Data
Latest Developments
Correlation Between War/Violence References and the Oil Price
Over the last decade, spikes in "war" and "violence" references in media have consistently preceded oil price rallies: from Russia invading Ukraine, to Houthi attacks on Red Sea shipping, to the Iran conflict today. Conversely, declines in media focus on war have preceded energy price declines. At MarketPsych, we quantify these text signals across 1,000+ news and social media sources in real time. A simple moving average crossover strategy on war mentions applied to DBO (an oil ETF) shows significant outperformance vs buy-and-hold. Geopolitical risks portrayed in the media: war, supply constraints, political instability, etc., can create actionable signals for quants. Methodology explained in our whitepaper: "Leveraging Reuters News for Predicting Commodity Prices" (Teodoro & Peterson, 2025).
April 24, 2026
Excited to announce our new launch of the MarketPsych Research Accelerator!
Excited to announce our new launch: *MarketPsych Research Accelerator* in partnership with LSEG Data & Analytics 🚀 Trialing #AltData generates new alpha, but testing and integration can consume months of time. Our new MarketPsych Research Accelerator solves this: • 12 months of unrestricted trial access
April 22, 2026
Using Claude to Plot Sentiment Using LMA and Connecter.
Claude's intuitive power is amazing here. Despite a basic prompt, Claude created tools to expand the plot lines (attached). It has based it on media volume and provided us with insightful commentary. The most dramatic declines were in Oman, Bahrain, Kuwait, and the UAE.
April 13, 2026
From Data to Alpha: AI Strategies for Taming Unstructured Data
We'd love to see you at our upcoming April 16th webinar → "From Data to Alpha: AI Strategies for Taming Unstructured Data" Please register here: https://lnkd.in/gNWanBQe
April 13, 2026
Which Stocks Are Benefiting and Suffering from the Iran War?
Non-GCC Oil Majors: Shell, ExxonMobil, and Chevron are among the most discussed names with positive sentiment, as supply disruption fears drive expectations of higher oil prices for producers outside the Gulf region. U.S. Defense Contractors: Palantir and Lockheed Martin are seeing a surge in positive mentions, consistent with typical defense sector tailwinds during geopolitical escalation. On the other end of the spectrum, companies with direct exposure to the region are bearing the brunt of negative sentiment: Middle Eastern Airlines & Airport Services: Qatar Airways and InterGlobe are among the most negatively discussed, as airspace closures and travel uncertainty weigh on the sector.
March 15, 2026
Companies Associated With Private Credit, Ranked.
Companies associated with Private Credit in the media the week of March 8th to March 14th. They are ranked from top to bottom. Listed by most positive sentiment to most negative, by the average sentiment of the references. Oracle at the bottom, with the most negative associations to private credit.
March 14, 2026
Leveraging NLP to Extract Behavioral Insights from the Labubu Phenomenon
Our latest blog on Labubu. Read more in our latest blog: https://bit.ly/4pqf09f
January 20, 2026
Webinar: Transforming Financial Text Into Structured Data
New webinar next week - using Gen AI in finance for summarization, analysis, and prediction with LSEG Data & Analytics.
January 12, 2026
We Are Hiring!
Interested in NLP, AI or Quant Research? Our team is continually seeking talent with the same interests as us!
Contact Us Now NLP Engineer
Develop, implement, and optimise NLP systems for sentiment analysis and classification tasks to monitor market moods and trends
Python Developer
Create tools and solutions that drive data analysis and research, client services and infrastructure support
System Administrator
Monitor and optimize infrastructure, improve systems robustness across multiple servers and services