Welcome to the Stock Price Prediction Project! In this project, we aim to predict the estimated closing prices of a stock listed in NSE (National Stock Exchange) using historical data and advanced Linear Regression Models. Additionally, we will explore the influence of lunar phases on the stock market.
Disclaimer: This Project is still under development phase and will require future updates.
Let's dive into the code and uncover valuable insights into stock price movements. Feel free to explore and analyze the implemented models. If you have any questions or suggestions, don't hesitate to reach out.
The project consists of a Python script (extract.py) that utilizes the yfinance library for fetching stock data and implements a Linear Regression model created in C to predict closing prices.
To use the project:
- Clone the repository: https://github.com/xaman27x/Stock-Market-Analysis-Using-Linear-Regression-and-Pertaining-Effects.git
- Run the Python script:
extract.py - Follow the prompts to enter the stock code and other parameters.
Make sure to have the required dependencies installed:
pip install yfinance
-> LUNAR EFFECT:
The project also considers the influence of lunar phases on the stock market. It provides insights into the potential impact of the moon on stock trends.
-> RESULTS:
After running the script, you'll get insights into the stock's daily high, weekly high, monthly high, and the mean. The linear regression coefficients are calculated, and an extrapolated closing price is provided along with a buy/sell opinion based on the predicted returns.
Conclusion
The project concludes with a comprehensive analysis, including a determination of whether to buy the stock based on various parameters such as weekly high, monthly high, lunar phase, and extrapolated price range.
Feel free to explore the generated GNUPLOT graphs for a visual representation of the stock's performance over the past 30 days.
Happy coding, and may your predictions be as accurate as the phases of the moon!
NOTE: Feel free to modify the content based on your specific needs and add any additional details or instructions as necessary.