Analysis of Stock Market Prediction Through the Application of Machine Learning Techniques

Trends in stock market forecasting are acknowledged as a noteworthy and fruitful field of study. Smart investors can profit handsomely from the ups and downs of stock prices. Investors have a formidable obstacle when trying to forecast the stock market: data that is either stagnant or uncertain. For investors seeking to optimize profitability, stock market forecasting poses a significant difficulty. Mathematical methods and state-of-the-art learning technologies are employed to produce stock market projections. Computing methods, Machine Learning (ML) algorithms, performance variables, and reputable publications are just a few of the many subjects covered in this paper's review of different research articles. Therefore, the chosen articles are helping to advance datasets and ML algorithms that are used to predict how the stock market will move in the future. Predictions about the stock market are often made with the help of Neural Networks (NNs) and Artificial Neural Network (ANNs) algorithms. Unfortunately, there are still a lot of problems with the way the stock market is currently predicted. The principal premise of the research is that there are many interrelated factors that should be given greater weight when making stock market predictions.