Editing Key ideas of MarketPawns

== The Driving Force Behind [http://wiki.marketpawns.com/index.php?title=Main_Page '''MarketPawns'''] ==

The driving force behind [http://wiki.marketpawns.com/index.php?title=Main_Page '''MarketPawns'''] is the intention to create an opportunity for people to combine their mind potential with the collective intelligence and power of technology to work with such a complex, multi-level object as financial markets. The effectiveness of this will be indicated by the real profit that a user can extract by implementing tools we have created. Here are the ideas that The driving force behind [http://wiki.marketpawns.com/index.php?title=Main_Page '''MarketPawns'''] has adopted as key to the implementation of the plan:

=== Universal Analysis System ===

[http://wiki.marketpawns.com/index.php?title=Main_Page '''MarketPawns'''] uses a universal system for analyzing quotes that uniformly describes any data according to strictly formalized rules. '''Universal Markets Geometry (UMG)''' is based on the key ideas of Tactica Adversa methods, retaining the approach of sequential selection of extremes on charts. These extremes are used to construct Trend Lines and Aim Lines, forming UMG technical analysis models.

=== Parameters for Model Classification ===

For each UMG model, dozens of calculated parameters are computed, which can be used to classify any model. Using software algorithms developed over several years we have compiled a database of several million models and for each one of them classification data is calculated.

=== Forecast Fulfillment Evaluation System ===

In addition to the calculated parameters, we have developed a system of parameters to describe the price development after a model appears on the chart. This stage is referred to as "model execution". The group of parameters characterizing model execution is collectively called "control parameters".

=== Model Classification ===

By comparing calculated parameters and control parameters on the historical preice data, models can be classified by types and probabilities of forecast fulfillment. In other words, by comparing calculated and control parameters in hundreds of thousands of cases, we can predict control parameters based on calculated ones before the "execution of the model" occurs.

=== Neural Networks ===

Over several years, we have tried several approaches to analyzing the statistics of model execution. Currently, the use of specially trained neural networks shows the most promise.

=== Community ===

This key idea served as the reason for creating the public resource [http://wiki.marketpawns.com/index.php?title=Main_Page '''MarketPawns''']. The universality and clarity of UMG encourages the search for new approaches to its use in analysis, for which we need your attention and, if it's possible, active participation. There is a Community Wall section, a platform for interaction between all those who wish to share their forecasts using UMG models (which are already calculated by automatic algorithms and provided to you with free access).