The well-established research process is a crucial driver of sustainable long-term performance
Every quantitative research starts with data. And we have lots of data in our high-performance database. Our team of engineers collect and store almost every piece of information which can be extracted from available data sources.
Our systematic trading strategies are based on machine learning and scientific concepts applied to financial markets. We follow a standardized research pipeline while creating a new strategy, regardless of whether it is trend-following or mean-reversion, intraday or HFT trading strategy.
Our goal is to deliver uncorrelated, absolute return performance. That is why our strategies operate across different markets, taking long and short positions in various time frames.
We strongly believe that understanding how to backtest a strategy brings the same amount of trading edge as a top-notch research process. In our proprietary backtesting platform, we loop through millions of data points to understand how transaction costs, slippage, and market impact may influence historical and future strategy performance.
We closely look at strategy risks and ways to protect our clients from drawdowns. Our risk management process goes way beyond traditional VaR and beta calculations – we use advanced position sizing, simulation, and portfolio allocation techniques to minimize the probability of a negative result.