In this project I will be making a Stock Market Prediction about a particular stock by reviewing its previous stocks trends.It will involve using historical stock data (e.g., opening price, closing price, volume, high, low) to forecast future prices.Aim is to analyse patterns in stock prices and develop models to predict future trends. This project will demonstrate time series forecasting, which can be valuable for investors and traders.
The inspiration for this project is because I am interested in Learning about Stock Market and this will be helpful to invest in correct stock.This will influence the purchase of the stocks and I will be trying to add more predictions to this project . ●Description: Predict stock prices using historical data (time series forecasting). ●Key Techniques: LSTM, ARIMA, Linear Regression.
Data Collection: Using Yahoo Finance to download stock price data. Data Preprocessing: Scaling, splitting data, and preparing sequences for training. Model Building: Using LSTM (Long Short-Term Memory) neural network for time series prediction. Model Training: Training the LSTM model on historical stock data. Model Evaluation: Testing the model and comparing predictions to actual stock prices. Visualisation: Plotting predicted vs. actual prices. EDIT: UPDATION WITH TIME AND KEEP ON TRAINING, TAKE NEWS INFLUENCE ,TAKE INFLUENCE OF NEWS, MAKE OTHERS PRO YOURS