Coca-Cola-Stock-Analysis-Project

Project Description

This project focuses on analyzing and predicting Coca-Cola (KO) stock prices using historical stock market data.
The goal is to identify trends, perform technical analysis, and use machine learning models to forecast future stock prices.

Stock market analysis helps investors and analysts understand company performance, risks, and growth opportunities.
This project applies data analysis and machine learning techniques to support data-driven investment decisions.

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Features

• Historical stock price analysis
• Exploratory Data Analysis (EDA)
• Technical indicators (Moving Averages, Volatility)
• Data visualization
• Machine Learning price prediction
• Model performance evaluation
• Future stock price prediction

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Tools & Technologies

• Python – Main programming language
• Pandas & NumPy – Data cleaning and analysis
• Matplotlib & Seaborn – Data visualization
• Yahoo Finance API – Stock data collection
• Machine Learning (Random Forest) – Price prediction
• Excel & SQL – Data handling and analysis

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Dataset

• Source: Yahoo Finance
• Stock: Coca-Cola Company (KO)
• Data includes:
  • Open, High, Low, Close prices
  • Volume
  • Dividends
  • Stock Splits

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Methodology

1. Collected Coca-Cola stock data from Yahoo Finance
2. Cleaned missing and incorrect values
3. Performed Exploratory Data Analysis (EDA)
4. Created technical indicators such as Moving Averages
5. Built and trained a Random Forest model
6. Evaluated model performance using MAE and MSE
7. Predicted future stock prices

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Results

• Long-term stock trends show stable growth
• Moving averages help identify bullish and bearish trends
• Random Forest model achieved low prediction error
• Backtesting shows strong long-term returns
• Machine learning model provided accurate predictions

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How to Run the Project

1. Clone the repository:

   git clone https://github.com/Yashu-teach/Coca-Cola-Stock-Analysis-Project.git