An Effective Algorithm for Share Trading and Bit-coin Prediction using AIML

The Share market is a platform where shares of publicly listed companies are traded. Investors aim to predict price movements to maximize profits and minimize losses. Utilizing advanced technology like AI can enhance stock price prediction. However, in exploring strategies and variables, we found that machine learning algorithms such as Random Forest, LSTM, SVM, and ANN were underutilized. This model proposes a more accurate approach to predicting stock movements. Firstly, we consider data from the previous year's stock market prices, historical currency and commodity market prices, and news headlines. The datasets are pre- processed to prepare them for analysis, which is a key focus of our model. Secondly, we review major AI techniques for the processed data and their productive results. Moreover, our proposed system evaluates the forecast system's application to real-world scenarios and the associated problems with the accuracy of the provided total values. Combining the results of all algorithms and considering all factors affecting stock prices led to high accuracy and profitability. Successful stock price valuation prediction can greatly benefit stock market firms and provide practical solutions for individual investors' stock market challenges