We developed an autonomous trading system called Enigma, which principally uses machine learning models for the technical analysis of market data. Model training, API integration and trade execution are all part of the larger system which falls into the high-frequency category. However, in contrast to other high-frequency systems, it is not reliant on frontrunning, arbitrage, or millisecond delays in trade execution. Rather, it consumes only data that is publicly available to make predictions about future price movements on a variety of timeframes.
As an alternative option to Enigma's high-return-high-volatility performance, arbitrage strategies offer low-risk stable performances. These vary greatly in terms of sophistication, using techniques which range from simple (such as funding rate arbitrage) to complex (such as cross exchange future arbitrage - under development).
We have a market-neutral mandate. Our strategies allow us to thrive in bull or bear markets, particularly when volumes and volatility are high.