Proprietary Models

Global Market Watch

Finding Patterns in Global Financial Markets

The Global Market Watch (GMW) is a proprietary pattern recognition model using machine learning algorithms to analyze global economic and financial market data.

Each time the GMW is updated with new data it benchmarks each instrument (or Covered Market) independently against a historical dataset that includes thousands of patterns to determine if there may be any that are reoccurring or newly forming.

While the GMW is robust on the back end, the front end output is formatted in a simple color and comment design.

The colors and comments are generated by the model based on activity it is picking up on as each week, month, quarter and year progress. The more history and data processed, the more the model is learning right up until each week, month, quarter and year are closed with a final assessment.

The objective of the Global Market Watch is to provide a relatively easy, quick reference tool in a birds-eye format so users can identify areas they may want to research further.

Also see the Indicating Ranges, the Energy Model, The Reversal System and Timing Arrays, along with price charts and various standard technical studies found within the Socrates Platform and available for research.

Global Market Watch