Case Details

Our strategies are based on quantitative analysis methods, which allow us to choose the most promising out of tens of thousands of financial instruments, then, using fundamental analysis methods and using alternative data technologies, we select those favorites on which we bet.

We implemented Alternative data analysis in stock market to obtain insight into the investment process. Alternative data sets are information about a particular company that is published by sources outside of the company, which can provide unique and timely insights into investment opportunities.

We use machine learning approach and big data solutions for collecting, storing and handling data. We collect an alternative data set from various sources such as financial transactions, sensors, mobile devices, satellites, public records, and the internet. Alternative data can be compared with data that is traditionally used by investment companies such as investor presentations, SEC filings, and press releases.

For quantitative analysis, we use our own library of algorithms, all the possibilities that modern multithreaded and multiprocessor computing systems, operating systems and programming languages such as R, Python and C ++ provide.

In the process of developing algorithms, all methods of modern mathematics are used: game theory, theory of probability and statistics, digital signal processing, Kelly criterion, Bayesian statistics, fuzzy logic.

We create trading models, testing and verification, which allows us to control risks in the real market.