Technical Analysis of Stock Market using Data Science and its tools

This paper presents a technical analysis approach for the stock market using data science and its associated tools. The objective is to develop a systematic framework that leverages data science techniques to analyze stock market data and make informed investment decisions. The proposed methodology involves data collection, preprocessing, feature engineering, and the application of various machine learning algorithms for predicting stock prices and identifying potential trading opportunities. The study demonstrates the effectiveness of data science in enhancing traditional technical analysis methods and provides insights into the potential benefits of integrating data-driven approaches into stock market analysis. Experimental results on historical stock data validate the proposed approach's accuracy and highlight its potential for improving investment strategies.