SMA Crossover Strategy

This Django project fetches stock data from a Google Sheet, validates it, and uses a Simple Moving Average (SMA) crossover strategy for buy/sell signals.

Features

1. Stock Data Import:

   • Imports stock data from Google Sheets and stores it in the database.
   • Validates the data to ensure correct types (decimals, integers, strings, datetime).

2. SMA Crossover Strategy:

   • Implements a strategy to identify buy/sell signals based on short and long SMA windows.

Setup

Prerequisites

• Python
• PostgreSQL

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/stock-data-sma.git
   cd stock-data-sma

2. Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install the dependencies:

   pip install -r requirements.txt

4. Set up the .env file. A .env.example file is provided. Rename it to .env:

   cp .env.example .env

5. Edit the .env file and add your PostgreSQL database credentials and the URL for the Google Sheet you want to import. Here's the format:

   DATABASE_URL=postgresql://USERNAME:PASSWORD@localhost:PORT/DATABASE_NAME
   GOOGLE_SHEET_URL=https://docs.google.com/spreadsheets/d/__SPREADSHEET_KEY__/export?format=csv
   

   For example:

   DATABASE_URL=postgresql://postgres:password@localhost:5432/stock_db
   GOOGLE_SHEET_URL=https://docs.google.com/spreadsheets/d/1oCyKT2SFZlw3Ac3GXj0Y1IYcWG183IRgNCNytFojkWA/export?format=csv
   

6. Set up the Django application:

   python manage.py migrate

7. Migrate Data from Google Sheets to Database:

   After migrating the database schema, use the custom management command to fetch stock data from the Google Sheet and populate the database:

   python manage.py import_stock_data

Running the Application

1. Start the Django server:

   python manage.py runserver

2. Visit the following URL to view the SMA crossover strategy:

   http://127.0.0.1:8000/stock/sma-crossover/?short_window=30&long_window=365
   

3. SMA Crossover Strategy Screenshot:

   Below is a screenshot showing the SMA crossover strategy output:

   

Running Unit Tests

Unit tests are provided to validate stock data fetched from Google Sheets, ensuring that the data types are correct (decimals, integers, strings, and datetime).

Running the Unit Tests

You can run the tests using the Django test command:

python manage.py test stock_data

Below is a screenshot showing the SMA crossover strategy output: