AnalytiStock

This is a Python program for analyzing stock data using various technical indicators and implementing a simple trading strategy. The program allows the user to input a stock symbol, start date, and end date, then loads historical data for the specified period, applies technical analysis indicators, and provides investment and profit/loss information based on a trading strategy.

Table of Contents

• Features
• Update 1
• Prerequisites
• Installation
• Usage
• Testing
• Code Coverage
• Contribution

Features

• Retrieve historical stock data using Yahoo Finance API.
• Candlestick Chart visualization of support and resistance levels.
• Apply technical analysis indicators, including RSI, simple moving averages, support and resistance levels.
• Implement a trading strategy based on the SMA20 and SMA50 crossover and support/resistance levels.
• GUI implemented using Tkinter for user-friendly interaction.

Update 1

• Unit testing using unittest and pytest.
• Code coverage analysis.
• Exception handling.
• File handling.
• Backtesting algorithm on multiple stocks and time ranges.
• Cleaned candlestick chart visualization.
• Advanced trading algorithm utilizing multiple indicators.
• Enhanced user-friendly GUI with additional charts.
• Improved code and file structure

Prerequisites

Before you begin, ensure you have met the following requirements:

• Python 3.7 or higher installed.
• Required Python packages can be installed using requirements.txt.

Installation

1. Clone the repository:

   git clone https://github.com/codevshl/Trend_Finder_Updated.git
   
   

Usage

Run the main program:

• Run GUI file using required commands

• The GUI will open, allowing you to input the stock symbol, start date, and end date.

• Click the Submit button to retrieve and analyze the stock data.

• It will display the processed data and investment/profit information.

• Click the Display Dataframe button for get data of ticker symbol you provided

• Click on dropdown button and click on Plot Data to get required charts

Testing

1. For unittest:

cd "required_path"
python "your_filename"

Replace your_test_directory/ with the actual directory where your test files are located and your_filename with the actual filename.

2. For pytest:

If you haven't already installed pytest, you can do so using pip:

pip install pytest

cd "required_path"
pytest "your_filename"

Replace your_test_directory/ with the actual directory where your test files are located and your_filename with the actual filename.

Code Coverage

1. Install coverage.py:

If you haven't already installed coverage.py, you can do so using pip:

pip install coverage

Run coverage.py with pytest or unittest:

Use coverage.py to run your tests and collect coverage data. You can execute the following command:

coverage run -m pytest/unittest your_test_directory/

Replace your_test_directory/ with the actual directory where your test files are located and choose pytest or unittest accordingly.

2. Generate Coverage Report:

After running the tests, you can generate a coverage report by running:

coverage report -m

This command will display the code coverage report in the terminal, including the percentage of code coverage achieved for each module and function.

Contribution

• Contributions are welcome! If you have any suggestions, bug reports, or feature requests, please open an issue on the GitHub repository.