The Laboratory is carrying out its research, development and educational activities in the following principal directions: 

— methods of formal software verification, including distributed ledger (blockchain) systems and algorithmic trading strategies

 — stochastic methods for analysis and forecasting of financial time series, including digital assets

 — methods, strategies and technologies for algorithmic financial trading, based on Financial Mathematics and Machine Learning

 — financial derivatives (options) and volatility models for financial markets

 — numerical and analytical-numerical methods of Financial Mathematics

 — functional programming and domain-specific programming languages in Financial Technologies. 

The teaching activities of the Laboratory span all levels including BSc, MSc, PhD and continues professional education.