CONCERT AI uses Artificial Intelligence and Neural Networks that are capable of learning and self-optimization.  This provides the advantages of market pattern recognition to select high risk-adjusted portfolio allocations, cash as a safe harbor to prevent loss during market downturns, and constant self-optimization of the process. 

Our CONCERT AI system can run any combination of ticker symbols to produce powerful results.

We measure and manage market exposure continuously.

  • Investment selections based on price pattern recognition improves the reliability of positive return outcomes.

  • A disciplined daily process allows for exposure modifications when necessary.

CONCERT AI = Technology + Frequency + Discipline + Experience

CONCERT AI is the result of 30 years of risk allocation experience with the best practitioners on Wall Street managing investments, trading accounts and hedge fund portfolios.

An example which will illustrate our methodology is the application of CONCERT AI to the S&P 500. Using the original selection process designed in 2004, the model produced an annualized return of 10.5% vs. S&P 500 6.3% over the past 11 years. All trades were machine generated and recorded in real time without human intervention since 1/1/07.  The system was free to pick from 9000 ticker symbols in its database. Algorithms for this layer of model were frozen in 2004. This early iteration of the model is the foundation upon which subsequent layers of the model were built and has not been modified since 2004. The chart below captures the historical performance of CONCERT AI relative to the S&P 500 Index over an 11-year period.


The next layer of model development was the addition of secondary neural networks as well as Monte Carlo iterations and investment rules.  Inputs for this layer of the model were frozen in 2007 but the neural networks continued to learn from daily market data.

To test the robustness of the system, we restricted the inputs to a more limited set of securities, looking first at the components of widely followed indices, and then at individual stocks. The model ‘knowing’ what it ‘knows’ today made historical selections looking back over time. These results are considered pro-forma.

The following chart illustrates CONCERT AI applied to the S&P 500 using the 9 Sector SPDRS.


In implementing CONCERT AI, Ferrell Capital developed and tested the system's neural networks, and then validated the performance in real market time.

Please review Disclosure Statement here.