Structured data for investments solutions

Financial data and models, machine learning, financial superservices.

Our product

API. Financial statements of US public companies

API with structured reporting on 500+ U.S. public companies by sector and industry

Data source — reports filed by companies and sent to the Securities and Exchange Commission (SEC)

Quarterly and annual reports plus TTM (trailing twelve months) aggregated data

Flexible

Customized reporting formats

Reliably

High quality data, daily update

Fits

Personal selection and segmentation

Consistent

Data storage depth 10 years with expansion option

REST API • Open API specificationAPI key authentication

API in numbers

Balance sheet
30+ parameters

Income statement
15+ parameters

Cash flows
30+ parameters

Ratios
15+ parameters

In the now distant 2018 The Economist published an article about how Goldman Sachs hired a team of 200 IT professionals to create a stock price forecasting and valuation computer program.

That program was based on machine learning algorythmns was a breakthrough at that time in both technological and business approaches. As a result bank was able to dismiss 300 financial analysts who historically performed a similar function, replacing them with exact that program and got the same or even better performance. Yes, we can very roughly call that computer program an analogue of artificial intelligence or more percise proto artificial intelligence. That idea of human intellegence substitution in the field of finance by innvovative technology has finally entered in our heads.

We saw a further development of the idea in the creation of a fully digital «wealth management» product with which you can manage your assets efficiently and without large monetary costs, inspired the study of this topic. It turned out that it might be possible to make such a product that will is now available only to billionaires but with low cost.

But it turned out that to build such a product data is required. Financial data and the more the better. And there we got our first real big obstacle.The study showed that there is no data on company reporting with required quality. More precisely, there is data available, but either not deep enough, or contain errors.

We assembled a team, and now, after three years, we have made a separate product that can collect high-quality structured data from the official financial statements of US public companies. The first step has been taken. In development…, in plans… more to come!

Structured data of US public companies financial statements

Ratios

💡 We are here 

Insider purchases 

Equities valuation models

Contact us

for any questions

team@hypersphere.pro

10152, Estonia, Tallinn, Vesivärava 50-201

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