Stock Screener and Trading Simulator

This project combines a stock screener for NASDAQ/ASX stocks with a trading simulator, allowing users to identify potential trades and test various trading strategies using historical data.

Table of Contents

1. Installation
2. Stock Screener
   • Usage
   • Settings
   • Limitations
3. Trading Simulator
   • Running Simulations
   • Configuration
4. Google Sheet Configuration
5. Troubleshooting

Installation

1. Clone this repo: git clone https://github.com/illi4/asx-screener.git
2. Install Python 3 (3.6+) and virtualenv if not already installed.
3. Change to the cloned folder, create and activate a Python 3 venv:

   python3 -m venv venv
   . venv/bin/activate  # On Windows, use: venv\Scripts\activate
   

4. Install required libraries: pip install -r requirements.txt
5. Place your eodhistoricaldata API key in .envrc under variable API_KEY

Stock Screener

The stock screener helps identify potential bullish trading opportunities based on various technical indicators and market data.

Usage

Run python scanner.py --h to view context help

• Update stocks list:

  python scanner.py --update [-date=YYYY-MM-DD]
  

• Scan and shortlist:

  python scanner.py --scan -method=anx [-stocks=STOCK1,STOCK2,...] [-num=100] [--use_existing_price_data]
  

Note that new prices must be fetched on a new day to get the most recent OHLC data. However, if you are running the scanner again and want to reuse the fetched data, you can run the scanner with the parameter --use_existing_price_data. This will keep the prices table untouched.

Helper scripts (requires Google credentials):

• Monitor exit conditions:

  python monitor.py -method=anx
  

• Auto-fill paper trade entries:

  python paperfill.py -method=anx
  

• Daily routine:

  python paperfill.py -method=anx
  python monitor.py -method=anx
  python scanner.py --update
  python scanner.py --scan -method=anx
  

Settings

See config.yaml for settings including:

• Market selection
• Price range for stocks
• Minimum volume threshold
• Overextended threshold
• Other conditions and rules

Limitations

• Tested on Australia/Sydney timezone
• Requires Python 3.6+
• The shortlist should only guide your research, not be interpreted as 'signals'

Trading Simulator

The trading simulator uses historical data to test various trading strategies and parameters.

Running Simulations

To run the simulator:

python simulator.py -start=YYYY-MM-DD -end=YYYY-MM-DD -method=anx [options]

Example:

python simulator.py -start=2023-12-10 -end=2024-04-01 -method=mri --plot

Required Parameters:

• -start=YYYY-MM-DD: Start date for the simulation
• -end=YYYY-MM-DD: End date for the simulation
• -method=anx|mri|earnings: Method of shortlisting

Optional Parameters:

• --plot: Generate and include plots in the output Excel file
• --forced_price_update: Force update of price data in the database
• -stock=STOCK_CODE: Specify a single stock to simulate
• --sampling: Enable sampling mode for multiple simulation runs and averaging the results
• --rnd: Use to run the simulation on the RND sheet which has a structure different from the post-RND one

Configuration

The config.yaml file contains important simulation parameters:

• capital: Initial capital
• commission: Commission fee per trade
• simultaneous_positions: List of maximum simultaneous positions to simulate
• numerical_filters: Filters for technical indicators (e.g., Fisher, Coppock)
• take_profit_variants: Different take-profit strategies to simulate

Example take_profit_variant:

take_profit_values:
  - level: 5%
    exit_proportion: 25%
    move_stop_price: False
  - level: 10%
    exit_proportion: 25%
    move_stop_price: True
    move_stop_from_tp_level: 5%

Output

Results are saved in sim_summary.xlsx, containing:

• Summary of performance metrics for each variant
• Monthly breakdown of capital values
• Plots of capital over time (if --plot is used)

Google Sheet and Google Project Configuration

To log stocks and use monitor and paperfill features:

1. Create a sheet similar to this example
2. Configure API access
3. Save credentials under .config\gspread\service_account.json

Note: This is not required for using only the scanner (scanner.py)

Troubleshooting

• There's a known warning when using gsheets, which doesn't affect outcomes. See this issue
• For other issues, ensure all required Python packages are installed and up to date
• Check that your Google Sheets is properly formatted and accessible if using related features