I've spent several years exploring algorithmic trading. Through this journey, I realized that understanding market trends is crucial before developing algorithms to follow those trends. This insight led me to learn trading fundamentals and conduct extensive backtesting over the past few years.
As I gained proficiency in trading, I began questioning whether AI could replicate my approach. While it's challenging to train a model to mimic human traders due to the complexity involved in every price chart bar, I'm intrigued by the possibility of starting with basic pattern recognition.
My goal is to develop an AI model that can identify fundamental patterns in stock market data. This project aims to lay the groundwork for more advanced tools, including trend analysis, key levels identification, and momentum tracking. The ultimate objective is to create a comprehensive trading system that leverages AI capabilities while maintaining the depth of human analysis.
By focusing on pattern recognition as the first step, we can build upon this foundation to develop more sophisticated trading strategies. This approach aligns with my experience in trading and provides a structured path towards creating a robust AI-powered trading system.
This project represents my attempt to bridge the gap between traditional trading methods and cutting-edge AI technology, with the potential to revolutionize how traders analyze and execute trades in the stock market.
Below is a pattern called 2B or False Braekout. It will be the starting point of this project. I am planning to use VisionAI to train a pattern recognition model such that it could recgonise this pattern. There will be more update of the result and technology used once the data has been prepared.
