Options trading volume, open interest, gamma and other metrics have become fundamental in following stock market order flow.
Our programs analyze options data along hundreds of parameters to identify risk patterns and directional trends.
Using the machine learning parameters, 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 this approach is stable growth over time. Our core models are not designed to "get rich quick." Our core models are designed to give peace of mind in investing.