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| | license: apache-2.0 |
| | --- |
| | |
| | This script is a command-line tool designed to predict a trading signal of the next day for a stock. |
| | You run it from your terminal or command prompt, not from within a Python IDE's run button without configuration. |
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| | ## Disclaimer: This is for informational purposes only and does not constitute investment advice |
| | The script is generated by Qwen-Max, Gemini Pro 2.5, and Grok4 Fast and test locally |
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| | ## Step 1: Install Prerequisites |
| | First, you need to install Python and all the necessary libraries. The most complex one is TA-Lib, which requires a separate installation before the Python wrapper. |
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| | Install the TA-Lib C Library: This is the underlying engine for the talib Python package. |
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| | Windows: Download the appropriate .whl file from Unofficial Windows Binaries for Python Extension Packages and install it using pip. |
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| | macOS: Use Homebrew: brew install ta-lib |
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| | Linux (Ubuntu/Debian): sudo apt-get install libta-lib-dev |
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| | Install Python Libraries: Once the C library is installed, you can install the required Python packages using pip. |
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|
| | Bash |
| | ``` |
| | pip install yfinance pandas numpy xgboost scikit-learn TA-Lib requests |
| | ``` |
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| | ## Step 2: Save the Script |
| | Save the code you provided into a file. Let's name it signal_generator.py. Make sure you save it in a directory you can easily access from your terminal. |
| | |
| | ## Step 3: Run from the Command Line |
| | Open your terminal (on macOS/Linux) or Command Prompt/PowerShell (on Windows) and navigate to the directory where you saved the file. |
| | |
| | The basic command structure is: |
| | python signal_generator.py [TICKERS] [OPTIONS] |
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| | Arguments Explained: |
| | tickers (Required): The list of stock ticker symbols you want to analyze, separated by spaces. The first ticker is the default target unless specified otherwise. |
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| | --target (Optional): Specifies which ticker from the list to generate the signal for. |
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| | --period (Optional): The amount of historical data to download. The default is 2y (2 years). Other valid options include 1y, 6mo, 3mo, 1d, etc. |
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| | ## Examples |
| | Here are a few examples of how to run the script: |
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| | ### Example 1: Basic Signal for a Single Stock |
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| | This will generate a signal for Apple (AAPL), using the default 2-year period. |
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| | Bash |
| | ``` |
| | python signal_generator.py AAPL |
| | ``` |
| | ### Example 2: Signal for a Target Stock with Market Context |
| | This command downloads data for SPY, QQQ, and NVDA but specifically generates the trading signal for NVDA. |
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| | Bash |
| | ``` |
| | python signal_generator.py SPY QQQ NVDA --target=NVDA |
| | ``` |
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| | ### Example 3: Including Market Indexes |
| | This command generates a signal for the QQQ ETF and includes the VIX (volatility), TNX (10-year treasury yield), and DXY (dollar index) for a richer market context. |
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| | Bash |
| | ``` |
| | python signal_generator.py QQQ VIX TNX DXY |
| | ``` |
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| | ### Example 4: Using a Shorter Historical Period |
| | This generates a signal for Microsoft (MSFT) using only the last 6 months of data. |
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| | Bash |
| | ``` |
| | python signal_generator.py MSFT |
| | ``` |
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| | After running any of these commands, the script will print the final signal directly to your terminal. |
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