[Update 1]

• I am currently working on adding more features and a GUI. Likely to be completed by 5th September.
• I will be integrating portfolio visualization tools, stock screener & F&O indicators.

RSI Implementation with Python

This project is a simple implementation of RSI (Relative Strength Index) analysis using Python. The script fetches historical stock data for a given ticker symbol, calculates the RSI, and plots both the adjusted close price and the RSI on a graph. This project demonstrates basic data manipulation, calculation, and visualization techniques in Python.

What is RSI?

The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. RSI oscillates between 0 and 100 and is typically used to identify overbought or oversold conditions in a stock. An RSI value above 70 is generally considered overbought, while an RSI value below 30 is considered oversold.

Project Structure

The project includes the following components:

• Fetching historical stock data using yfinance.
• Calculating the daily price changes and separating them into gains and losses.
• Calculating the average gain and loss over a specified period (14 days by default).
• Computing the RSI based on the average gains and losses.
• Plotting the adjusted close price and RSI on a graph using matplotlib.

Learnings from this Project

Through this project, I have gained insights into:

• Fetching financial data using the yfinance library.
• Data manipulation and rolling window calculations with pandas.
• Visualizing financial data using matplotlib.
• Understanding and implementing the RSI calculation.
• Enhancing the plot aesthetics to improve readability.

To-Do

• Add a UI with Streamlit and host the application.
• Add a search option to allow users to input different ticker symbols.
• Add more options and better labels on the plot to enhance the user experience.
• Integrate anomaly detection program here based on user parameters.

Usage

To run this project, you need to have Python installed along with the following libraries:

pip install pandas pandas_datareader matplotlib yfinance

Example

Here is an example of how the plot looks:

• This is just a very basic implementation, I am working to add more features soon to make it aesthetically better and more insightful with appropriate finance data.