Stock Prediction and Analysis

This repository contains Python code for stock price prediction and analysis. It includes exploratory data analysis (EDA), time series visualization, predictive modeling using machine learning algorithms, and backtesting of prediction models.

Contents:

1. Exploratory Data Analysis (EDA): Visualize stock prices, calculate average prices, and compute Relative Strength Index (RSI) for stocks.
2. Predictive Modeling: Utilize Random Forest Classifier for single stock prediction and refine the model for multiple stocks in the dataset. Also, employ Linear Regression for predicting closing prices.
3. Sample Data: Predict closing price for a given date based on provided opening, high, low prices, and volume.

Requirements:

1. Python 3.12.x
2. Libraries: numpy, pandas, matplotlib, scikit-learn

Usage:

1. Clone the repository.
2. Ensure the required libraries are installed from the requirements.txt file.
3. Run the Python scripts for analysis and prediction.