What is Pecunnia?
Pecunnia filters financial news and explains with AI what matters for the assets you follow. Save time and understand the markets better.
Pecunnia is a financial information tool for individual investors. It gathers, for each asset, its price and the news that concerns it, and answers questions about finance through a specialised artificial intelligence assistant.
What Pecunnia does
- One page per asset — stocks, ETFs, government bonds, cryptocurrencies, commodities and currency pairs — with the price and its history.
- News attached to the asset it names, sorted by scope: company, sector or market. Every news item links to its source.
- A finance-specialised artificial intelligence assistant that explains a mechanism, a concept or a news item from Pecunnia's data, and cites its sources.
- For stocks, companies' financial statements (income statement, balance sheet, cash flow) when available.
- A weekly market recap that reports facts.
Who it is for
Individuals who follow the markets or want to understand a news item, a balance sheet or a finance concept, from beginner to experienced investor. Pecunnia is not designed for trading-room professionals.
What Pecunnia does not do
- It gives no investment advice: it does not recommend buying, selling or holding an asset, and does not take your personal situation into account.
- It does not forecast prices and promises no return. Past performance does not predict future performance.
- It places no orders and manages no portfolio for you.
- Its assistant can be wrong: check important information at the source.
Where the data comes from
- Prices and asset profiles: public market-data providers.
- News: feeds from financial media; each news item keeps a link to its original source.
- Financial statements: companies' regulatory filings (the SEC in the United States, the ESEF format in the European Union).
- Macroeconomic indicators and central-bank decisions: data published by the institutions (for example FRED, the St. Louis Fed database).
- Assistant answers: a language model relying on this data and, when needed, on a recent web search.