Proprietary Models

Global Market Watch (GMW)

Finding Patterns in Global Financial Markets

A common focus area of technical analysis is the study of financial markets to identify underlying patterns in price activity. While these patterns can present themselves within an existing upward or downward trend, they can also signify a new trend has formed.

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

As the GMW records new data from each financial instrument listed in the Socrates Platform (aka each Covered Market) it benchmarks each of them independently against a unique database with thousands of historical patterns it has cataloged over the years to determine if any patterns may be reoccurring, or if any new patterns may be forming.


The front-end output is formatted in a simple color and comment design.
The colors and comments are generated by the model based on the activity it is picking up on as each week, month, quarter and year progresses.

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.

Financial Market Pattern Recognition

The ability to identify patterns and trends in global financial markets can provide valuable insights and help make informed decisions. The Global Market Watch was purpose-built with machine learning algorithms to analyze vast amounts of global economic and financial market data to more easily recognize patterns as they are unfolding. The GMW provides a bird's-eye view of all activity it is identifying so users can quickly reference it and determine what markets they want to research further and when.

The Future of Financial Analysis

As financial markets continue to evolve, the need for sophisticated - yet easy to use - tools to process and interpret vast amounts of data becomes increasingly important. The Global Market Watch bridges the gap by providing users with a powerful yet easily understandable view of global financial market activity across daily, weekly, monthly, quarterly and yearly time levels.

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Ease and Speed of Analysis

One of the key advantages of Global Market Watch is its ease of use and quick reference format. The model systematically assigns different colors and text phrases to signify what potential activity it is observing in a market. Examples of computer-generated phrases include "entering breakout" or "knee-jerk reaction" or "phase transition" among others. At a glance, this user-friendly interface provides visual and contextual cues on potential patterns the models are recognizing.

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The Power of Machine Learning

At the core of the Global Market Watch's effectiveness lies its purpose-built machine learning algorithms and ability to process vast amounts of financial data on a global scale. This helps recognize complex patterns that may otherwise remain hidden for each financial instrument (aka Covered Market) in the Socrates Platform. And it does this across each time level (e.g. daily, weekly, monthly, etc), which translates into thousands of different points of output from the GMW alone after each market day.

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The Socrates Platform is designed to give anyone direct access to information that was originally intended for industry professionals. This easy-to-use software-as-a-service solution allows you to research what you want, when you want. With different levels of engagement, the Socrates Platform has a version that works for just about anybody.