The stock prediction system has data collection, preprocessing, feature selection, model training and evaluation modules. It generates real-time trading signals based on trained models.
Data Collection Module: This module will be responsible for fetching historical stock data from a reliable source such as Yahoo Finance or Alpha Vantage. It will retrieve the necessary data, such as open, high, low, close prices, and volume, for the specified stock symbol and time period.
Data Preprocessing Module: In this module, we'll perform data preprocessing tasks such as handling missing values, removing outliers, and transforming the data if necessary. We'll also calculate additional features like technical indicators (moving averages, RSI, stochastic oscillator, Bollinger Bands, MACD) based on the historical stock data.
Feature Selection Module: This module will focus on selecting the most relevant features from the preprocessed data. We can use techniques like variance thresholding or SelectKBest with statistical tests to identify the most informative features for training our machine learning models.
Model Training Module: Here, we'll train different machine learning models on the preprocessed and selected features. We can experiment with various algorithms like Logistic Regression, Random Forest, Support Vector Machines, and Gradient Boosting to find the best-performing model for stock prediction.
Model Evaluation Module: This module will evaluate the trained models using appropriate evaluation metrics such as accuracy, precision, recall, and F1 score. It will provide insights into the model's performance and help us compare different algorithms.
Real-Time Prediction Module: Once the model is trained and validated, this module will be responsible for real-time predictions. Given the entry price provided, the module will analyze the current market data, apply the trained model, and generate trading signals (entry point, exit point, stop-loss levels) based on the model's predictions and predefined profit and stop-loss percentages.