MarketPsych produces the global standard in financial sentiment and ESG data from the news and social media information flow. We serve global funds, corporations, banks and brokerages in over 25 countries. Our products are distributed exclusively, and in partnership, with Refinitiv, a global provider of financial market data and infrastructure.
MarketPsych's proprietary NLP engine evaluates thousands of market-moving themes, which are further aggregated into scores. The scores form time series that are updated every 60 seconds. Each score represents the scale and direction of the media focus on complex themes, including sentiments, sustainability and price. They can be translated directly into spreadsheets or charts that can be monitored by traders, risk managers or analysts – or they can be plugged straight into your algorithms for low frequency, longer-term asset allocation or sector rotation decisions.
For more details check out our website.
- Wide coverage:
- 252 countries and territories
- 110,000+ global companies, sectors, and ETFs
- 62 stock indexes and sovereign bonds
- 44 currencies
- 51 commodities
- 500+ cryptocurrencies
- Long history: 1998 to the present
- Multi-language: sources in 13 languages
- AI-based: machine learning based natural language processing engine
- Highly granular: 100+ scores (including sentiment, business and ESG topics)
- Real-time: scores are produced every 60-seconds
- Sources: 6,000+ news and social media sources (selected from a pool of 300,000)
pip install marketpsych
If using Jupyter Notebook, be sure to have version >= 6.0. If using Jupyter Lab, be sure to have version >= 3.0.
This library assists with loading your trialling data from SFTP directly into a Jupyter notebook.
This library provides widgets through which you can set your data parameters inside a Jupyter Notebook.
The data can also be downloaded here.
For the first contact with the data, we suggest having a look at our tutorials. They consist of Jupyter Notebooks, which can be run in Colab, and assist you with understanding the data.