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    Visualizing and Understanding Market Clusters

    This document outlines the development of an indicator based on Machine Learning (ML) and ML.Net for unsupervised learning. The primary objective is to cluster candles based on their raw OHLC (Open, High, Low, Close) data and additional information obtained from different technical indicators. The K-Means clustering algorithm is used to assign candles into clusters and differentiate each cluster by assigning a distinct colour.

    The K-Means Indicator indicator embodies a groundbreaking integration of technical analysis principles with the prowess of machine learning. This innovative tool operates as a catalyst, systematically identifying and delineating potential clusters within extensive historical price data. By providing traders with a comprehensive perspective, it facilitates the discernment of intricate patterns, subtle trends, and the underlying structures shaping the market.



    cTrader K-Means Indicator

    Using key data from technical indicators such as RSI, ADX, and ATR, the system performs a thorough analysis of market trends and movements. This meticulous analysis provides an in-depth understanding of market dynamics, enabling the development of more effective and data-based trading strategies.