The Paradigm shift from Econometrics to Machine Learning
Our technology stack is automating and unbiasing trading and quoting policies with the superior predictive characteristics of deep learning. We apply neural networks to the microstructures of auctions to exploit the maximum predictive value from all patterns inherent in the data feed and constantly adjust to new market regimes.
Since market making has gone under growing pressure from regulation and rapidly changing technology continuous process automation and risk minimization is rising the demand for artificially intelligent systems. Market makers can deploy AI systems to generate new quoting policies and creating risk monitoring systems for their existing models.
By viewing market making as an integrated process to be optimized as a whole, completely differentiable deep-learning algorithms are a promising approach for an entirely new market maker in emerging asset classes, such as Cryptos.
Our Solution Scope
AI policy systems for high-frequency products that minimize model risk without significant overhead. AI prediction systems for medium-frequency products which serve as an additional analytics tool for trade/quoting decisions.
Order optimization layer for execution management systems. Predictive inventory management layer for in-house order matching.
Data feed enrichment with deep learning based predictions, provision of complete (re-)simulation environments, liquidity monitoring, and detection of fraudulent behavior.
We are providing liquidity to crypto & their derivative markets by using neural networks to generate quoting policies and predictively manage the inventory. Crypto markets are a valuable opportunity for us to build up distinct expertise in a growing asset and represents an environment where we test our latest technology.