Key ideas of MarketPawns

The Driving Force Behind MarketPawns

The driving force behind 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 MarketPawns has adopted as key to the implementation of the plan:

Universal Analysis System

MarketPawns uses universal system for analyzing quotes that uniformly describes almost any market data according to strictly formalized rules. It's called Universal Markets Geometry (UMG). UMG is based on the basic ideas of Tactica Adversa methods, retaining the approach of sequential selection of extremes on charts. These extremes are used to draw Trend Lines and Aim Lines, which formi UMG technical analysis models.

In contrast to Tactica Adversa, which largely relies on its own axiomatic apparatus, the core principle in developing UMG rules is: "Every idea has the right to exist, but must be thoroughly examined multiple times."

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 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 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).