Power Your Decisions with Natural Language Processing on Web Data.
100+ client use cases around the world
Unique data insights for quantitative or fundamental investment, due diligence,
portfolio monitoring, market research and more.
QuantMinds - ESG insights for Quantitative Investment
Discover how Natural Language Processing is leveraged to create ESG datasets based on web data and generate time series for quantitative use cases.
Fundamental Investment and Private Equity with Alternative Data
Complete presentation of our use cases including Sourcing and Idea Generation, Due Diligence, Risk Management and ESG.
Using Machine Learning to Extract Alpha from Alternative Data
In this paper, we apply SESAMm’s proprietary SignalReveal® Machine Learning pipeline on IHS Markit™ data to optimize a macro investment strategy with an efficient and high-value alpha creation process.
Big Data and AI for Attractive ESG Investment Solutions
- Explore and use textual data to construct short term ESG signals;
- Run unconstrained simulations and evaluate the purest potential of these signals to deliver performance;
- Design attractive long only and long/short strategies.
We analyze, in real-time, billions of articles and messages from the web using advanced Natural Language Processing techniques to analyze key trends. We also provide Machine Learning expertise to build analytics and investment strategies.
Ready-to-use Data Streams
Curated, granular data streams for investment professionals:
- Refined sentiment, ESG and retail trading time series for investment use cases
- History starting in 2008, covering thousands of stocks
- Daily data with financial identifier mapping
Modular API and Dashboards
Generate Alternative Data from text using NLP algorithms on a massive, ready-to-use data lake.
- Sophisticated NLP requests on an industry-leading data lake
- Sentiment, emotions, ESG and thematic analysis
- APIs and visualization dashboards
Investment Signals and Strategies
Create investment signals using Machine Learning algorithms.
- Modular and open Machine Learning pipelines
- Alternative Datasets evaluation & integration
- Quantitative signal creation