Stock Screener

This project is a stock screener that helps identify potential trading opportunities based on specific criteria.

Overview

The stock screener analyzes a list of stock symbols and filters them based on predefined conditions. It uses historical stock data and calculates various indicators to determine whether a stock should be considered for long or short positions.

Features

• Stock Screening: The program fetches historical stock data using the Yahoo Finance API, calculates percentage returns, and screens stocks based on user-defined threshold values.
• Pivot Calculation: The program calculates pivot points for short-listed stocks to identify potential support and resistance levels.
• Order Placement: The program places buy/sell orders for stocks that meet specific criteria, such as open price, previous day's high/low, resistance/support levels, and percentage change.

Setup

1. Clone the repository: git clone <repository_url>
2. Install the required dependencies: pip install -r requirements.txt
3. Configure the settings in the config.yaml file, including threshold values, target time, starting capital, and other parameters.
4. Provide a list of stock symbols in the data/universe.csv file.
5. Run the main script: python main.py

Configuration

The config.yaml file contains various settings and parameters for the stock screener. You can modify these values according to your requirements. Here are the key configuration options:

• threshold_positive: The threshold percentage for identifying stocks with positive returns. Currently set to: 4.7
• threshold_negative: The threshold percentage for identifying stocks with negative returns. Currently set to: -4.7
• target_time: The target time to start scanning for potential trades. Currently set to: '09:14:00'
• order_execution_time: The time at which the orders should be executed. Currently set to: '09:15:00'
• share_price_min_threshold: The minimum price for share to considered. Currently set to: 50
• share_price_max_threshold: The maximum price for share to considered. Currently set to: 3000
• stop_loss: The stop loss percentage for trades. Currently set to: 0.01
• target1: The first target percentage for trades. Currently set to: 0.005
• target2: The second target percentage for trades. Currently set to: 0.075
• target3: The third target percentage for trades. Currently set to: 0.01
• capital: The initial amount of capital available for trading. Currently set to: 1000
• buffer_entry: The buffer percentage for entry prices. Currently set to: 0.001
• buffer_trigger: The buffer percentage for trigger prices. Currently set to: 0.05

You can update these values in the config.yaml file based on your requirements.

Results

After running the script, the program will generate a DataFrame with the short-listed stocks and their respective pivot points. The program will also place buy/sell orders for stocks that meet the specified conditions.