In every sense, trading is a game. There is directly accessible fundamental information. There is important indirect information that must be handicapped. There are very specific rules of execution. And, most importantly, there is a score (ROI) to be kept. Despite all of the technological advances in trading, information is still processed through a human (or human directed) filter. Ultimately, it is the behavior of traders stimulated by data that dictates price movements.

Modern computing power can enable this game to be played at a very high speed with an enormous depth of data. Our methodology incorporates a “clean slate” analysis of plausibly causative factors in combination with advanced statistical, mathematical, machine learning and behavioral modeling techniques.

Powerful tools require equally powerful discipline. Cognitive biases can disrupt the accuracy of apparently successful trading models. Through our multi-tiered validation approach, we can accurately access the effects of randomness and provide compelling evidence of potential edge before the implementation of live trading.

Our Approach

In a similar fashion to how computers are programmed to learn how to play chess, the Edj decision model gathers business and organizational context for a specific decision and identifies all of the possible outcomes based on an existing data set.

The Data

What is the accessible information?

How is it changing
in real time?

The Rules

What are the constraints of the decision making process?

The Goal

Informed decisions for better trades.

Model Opportunities