Forecasting of Stock Market Trends using Machine Learning Techniques

In this study, we examine existing stock market prediction algorithms before proposing new ones. We approach the topic from three separate angles: fundamental analysis, technical analysis, and machine learning. We discover evidence to support the weak form of the Efficient Market Hypothesis, namely, that the market is efficient. Out of sample, prior prices do not offer valuable information. Data has the potential to anticipate. Any news that is significant to a publicly traded company has an impact on stock movement. We demonstrate the potential of Fundamental Analysis and Machine Learning used to help investors make decisions Machine Learning approaches can help here. Understanding the numerical time analysis Intelligent investors can use machine learning techniques to predict the stock if the series produces close results