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The Evolution of Technical Analysis: Machine learning to reinterpret classical chart patterns
In the world of finance, technical analysis plays a crucial role in predicting future price movements based on historical data. Traditional technical analysis relies heavily on chart patterns, such as head and shoulders, double tops and triangles, to make trading decisions. However, with the advancements in machine learning, we can now reinterpret these classical chart patterns in a more sophisticated and data-driven manner.
Introduction
In this tutorial, we will explore how to leverage machine learning techniques to analyze and reinterpret classical chart patterns using Python. We will use real financial data obtained from Yahoo Finance to demonstrate the application of these methods. By the end of this tutorial, you will have a solid understanding of how machine learning can enhance traditional technical analysis and potentially improve trading strategies.
To begin, let’s start by importing the necessary libraries and downloading the financial data for our analysis. We will use the yfinance library to fetch historical stock data for a diverse set of securities. Let's download the data for three different assets: Tesla (TSLA), Amazon (AMZN) and Bitcoin (BTC-USD) up until the end of February 2024.
