RETRACTED ARTICLE: Stock market analysis using candlestick regression and market trend prediction (CKRM)

• Published in: Journal of ambient intelligence and humanized computing Vol. 12; no. 5; pp. 4819 - 4826
• Main Authors: Ananthi, M., Vijayakumar, K.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2021; Springer Nature B.V
• Subjects: Accuracy; Algorithms; Artificial Intelligence; Computational Intelligence; Deep learning; Engineering; Genetic algorithms; Investments; Literature reviews; Machine learning; Market analysis; Neural networks; Original Research; Predictions; Robotics and Automation; Securities markets; Sentiment analysis; Social networks; Stock exchanges; Stock prices; Support vector machines; Time series; User Interfaces and Human Computer Interaction; Wavelet transforms; Candle-stick pattern; Regression analysis; Stock price; Time-series data; Machine learning
• ISSN: 1868-5137; 1868-5145
• DOI: 10.1007/s12652-020-01892-5

Stock market data is a time-series data in which stock value varies depends on time. Prediction of the stock market is an endeavor to assess the future value of a company’s stock rate which will increase the investor’s profit. The accurate prediction of stock market analysis is still a challenging task. The proposed system predicts stock price of any company mentioned by the user for the next few days. Using the predicted stock price and datasets collected from various sources regarding a certain equity, the overall sentiment of the stock is predicted. The prediction of stock price is done by regression and candlestick pattern detection. The proposed system generates signals on the candlestick graph which allows to predict market movement to a sufficient level of accuracy so that the user is able to judge whether a stock is a ‘Buy/Sell’ and whether to short the stock or go long by delivery. The prediction accuracy of the stock exchange has analyzed and improved to 85% using machine learning algorithms.