Deep Nexus applies advanced statistical methods to financial market data, generating a probability distribution for seemingly random markets. Our proprietary analytics deliver a predictive edge allowing us to trade any liquid market based on the probabilities while maximizing returns and minimizing risk.
Kevin has over 20 years of experience in financial markets while holding Series 7, 63, and 66 securities licenses. His trading experience includes stocks, bonds, options, futures, and currencies. In the 1990s, he began researching how to apply machine learning to financial markets. At Deep Nexus, he has been responsible for the development and coding of proprietary deep learning algorithmic trading models. Kevin studied economics and international relations and received his BA from Columbia University.
Deep Nexus is a multi-disciplinary collaboration among physicists, mathematicians, electrical engineers, computer scientists, and experts in algorithmic trading. The team employs the scientific method in the development and use of emerging technologies for the quantitative analysis of time-series data.