ML-based automated issue management, defect classification and bug triaging.
A curated list of awesome software engineering resources.
Peter Gagarinov shares his experience with integrating Apache Ignite with external machine frameworks.
Peter shares his Apache Ignite experience. He will show how one can minimize the number of blocks in a complex, scalable backend for an ML-based, automated issue-management system (Alliedium), as you stay within the Java ecosystem and the microservice paradigm.
ML-based semi-automatic market making and position trading system utilizing statistical arbitrage opportunities in volatility index – equity index future spreads on US market.
Broker-side stress-testing and optimization system for both aggregating and scaling multiple traders/strategies operating with options, futures, ETFs and stocks into a single portfolio for a better profitability/risk ratio for a broker.
Simulation platform for trading finance. It can simulate exchange functionality, exchange behavior, smart order routers, client behavior, market data sources and all interactions between them with a high degree of realism and consistency. A high-frequency exchange simulator uses a set of ML-based models to replicate a realistic behavior of the market. An integrated order-matching engine allows for tested trading strategies be surrounded by a realistic trading environment which can simulate various stress-testing scenarios (including exotic ones) while still keeping things realistic.
Exchange Simulator built for major European investment bank program trading desk which models reaction of market participants on user intrusions (activity that is absent in historical data files) by replaying historical orders flow, processing orders submitted by users according to exchange rules and modeling the market response on these user orders using probability-driven empirically justified models. The simulator uses a set of ML-based models to replicate a realistic behavior of the market. Having a wide range of behavioral settings allows to simulate various (including exotic) scenarios while still keeping things realistic due to an integrated order matching logic and fine-tuned ML models.
Energy StatArb Portfolio Management System. Semi-automatic trading system built for US energy hedge fund for generating trading recommendations on the market of energy/energy resources futures based on methods of Theory of Probability, Mathematical Statistics and Theory of Graphs, Time Series Analysis.