Options trading volume, open interest, gamma and other metrics have become fundamental in creating stock market order flow.
Our programs analyze options data along hundreds of parameters to identify risk patterns and directional trends.
Using machine learning techniques, our models adjust the position size of a target ETF once per day to avoid tail risk. In the back-test, these models often result in higher return and lower volatility.
The goal with our equity algorithms is stable growth over time. Our models are designed for "peace of mind," not "get rich quick."