Dynamic Stock Scanner

Overview

The Dynamic Stock Scanner is a Python-based tool designed to fetch historical stock data and analyze stock returns over a specified period. It allows users to dynamically set thresholds for return percentages and schedules the scanner to run daily at a specific time. This project is ideal for investors and analysts who want to identify stocks meeting specific return criteria.

Features

• Fetches historical stock data using the Yahoo Finance API.
• Calculates percentage returns over a user-specified time frame.
• Filters stocks based on a dynamically set return threshold.
• Schedules daily scans to run automatically at a specified time.
• Easy-to-use interactive input for return thresholds and time periods.

Requirements

To run this project, ensure you have the following dependencies installed:

• Python 3.7+
• yfinance
• pandas
• schedule

Install dependencies using:

pip install yfinance pandas schedule

Usage

Running the Scanner

1. Clone the repository or copy the script to your local environment.
2. Run the script using Python:

   python dynamic_stock_scanner.py

3. Enter the desired return threshold (e.g., 0 for 0% return) and the number of years for historical analysis when prompted.
4. The script will:
   • Fetch data for specified stocks (e.g., AAPL, MSFT, GOOGL).
   • Calculate their percentage returns over the specified period.
   • Display stocks meeting the criteria.

Scheduled Execution

The scanner is set to run daily at 6:00 PM by default. This can be adjusted in the script by modifying the line:

schedule.every().day.at("18:00").do(run_scanner)

Example Output

Enter return threshold (e.g., 0 for 0%): 0
Enter number of years: 7
Stocks meeting criteria: [('AAPL', -0.05), ('MSFT', 0.02)]
Stocks with 0% return: []

Functions

get_stock_data(stock_symbol, years)

Fetches historical stock data for a given symbol and period.

• Parameters:
  • stock_symbol (str): The ticker symbol of the stock (e.g., AAPL).
  • years (int): Number of years of data to fetch.
• Returns: A Pandas DataFrame of historical stock data.

calculate_return(stock_data)

Calculates the return percentage based on the stock’s initial and final closing prices.

• Parameters:
  • stock_data (DataFrame): Historical stock data.
• Returns: Return percentage (float).

stock_scanner(stocks, return_threshold, years)

Filters stocks based on return threshold over a specified time period.

• Parameters:
  • stocks (list): List of stock ticker symbols.
  • return_threshold (float): Desired return percentage.
  • years (int): Number of years for analysis.
• Returns: A list of stocks meeting the criteria.

run_scanner()

Runs the scanner for predefined stocks and logs results.

Customization

• Add More Stocks: Update the stocks_to_check list in the run_scanner function with additional stock symbols.
• Change Schedule Time: Modify the scheduled time in the schedule.every().day.at() function.

Limitations

• The script relies on Yahoo Finance data, which may have occasional outages or limitations.
• The return threshold uses absolute percentage values and may require further refinement for complex strategies.

License

This project is licensed under the MIT License. Feel free to use, modify, and distribute as needed.

Contributing

Contributions are welcome! Submit an issue or a pull request to enhance the functionality or fix bugs.

Acknowledgments

• Yahoo Finance API for providing financial data.
• Schedule Library for enabling easy scheduling.

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Start scanning stocks dynamically and uncover new investment opportunities with this script! 🚀