GitHub - LaurentiuGabriel/gpt-trading-agent: A trading AI agent based on Perplexity, QuantiQ and OpenAI models.

7 min read Original article ↗

AI Trading Agent

tldr: You can now use the SaaS version of this agent which is available on aivestor.tech. You can still use this OSS version of the agent following the steps below. I was just curious if AI can hallucinate where the market is going.

This agent uses Perplexity, GPT-5, QuantiQ.live and Alpaca to find small-cap stocks, provide analysis and recommendations, book orders on these stocks and track the performance of the portfolio. I also added Streamlit for a better user experience.

Features

  • AI-Driven Stock Discovery: Uses the Perplexity AI API to find interesting micro and small-cap US stocks.

  • In-Depth Financial Analysis: Fetches detailed financial data for specific tickers using the Quantiq API.

  • Intelligent Recommendations: Employs OpenAI's GPT-4o to analyze the financial data and provide BUY, SELL, or SHORT recommendations with justifications.

  • Interactive Chat Interface: A user-friendly chat allows you to request stock ideas and analysis.

  • One-Click Trading: Execute recommended trades directly from the chat interface. Trades are executed through the Alpaca API.

  • Portfolio Tracking: A dedicated page to view your complete trade history, current holdings, and overall portfolio performance, including value over time.

  • Persistent Portfolio: All trades are saved to a local portfolio.csv file, so your data is preserved between sessions.

  • Congress trades on specific stocks can be performed through the QuantiQ API.

Getting Started

Follow these instructions to get the application running on your local machine.

Prerequisites

  • Python 3.8 or newer

  1. Clone or Download the Project First, ensure you have all the project files (stock_picker_app.py, requirements.txt, portfolio.csv) in a single directory on your computer.

  2. Set Up API Keys This project requires three API keys. You'll need to store them in a .env file for security.

  • Create a new file named .env in the same directory as the project files.

  • Add your API keys to the .env file in the following format:

PERPLEXITY_API_KEY="your_perplexity_api_key_here"
OPENAI_API_KEY="your_openai_api_key_here"
QUANTIQ_API="your_quantiq_api_key_here"
ALPACA_API_KEY="YOUR_PAPER_API_KEY_ID"
ALPACA_SECRET_KEY="YOUR_PAPER_SECRET_KEY"
ALPACA_PAPER="true"
FMP_API_KEY=
FRED_API_KEY=
REDDIT_CLIENT_ID=
REDDIT_CLIENT_SECRET=
REDDIT_USER_AGENT=
NEWSAPI_KEY=

PERPLEXITY_API_KEY: Get this from your Perplexity AI account.

OPENAI_API_KEY: Get this from your OpenAI Platform account.

QUANTIQ_API: This is the API key from QuantiQ.live.

ALPACA_API_KEY: This is the API key from Alpaca trading platform

ALPACA_SECRET_KEY: This is the secret key from Alpaca that enables you to perform real trades

ALPACA_PAPER: Switch between the paper (virtual money) or the real Alpaca API

FMP_API_KEY: This is the API key for fetching economic events, such as Fed meetings. You can retrieve one from here.

FRED_API_KEY: This is the API key for fetching macroeconomic indicators. Fetch it from here.

REDDIT_CLIENT_ID: This is the Reddit client id for your account. Check out the section below on how to retrieve one.

REDDIT_CLIENT_SECRET: This is the Reddit secret for your account. Check out the section below on how to retrieve one.

REDDIT_USER_AGENT: A unique string used to get identified by Reddit. E.g.: "python:auto-invest:v1.0 (by /u/your_user)"

NEWSAPI_KEY: This is the API key of the NewsAPI. This service is used to retrieve news about specific tickers.

NOTE: The agent can interact with the Reddit API to get the latest posts about a stock from subreddits like r/wallstreetbets, or stocks. To enable this integration, follow these steps:

  • Go to https://www.reddit.com/prefs/apps
  • Create a new application (select "script" type)
  • Replace the placeholder credentials in the script with your actual credentials
  1. Install Dependencies

  • Open a terminal or command prompt.

  • Navigate to the project directory.

  • Install the required Python libraries by running:

pip install -r requirements.txt

This will install Streamlit, Pandas, Requests, OpenAI, yfinance, and python-dotenv.

  1. Run the Application Once the dependencies are installed and your API keys are set, you can start the Streamlit application.

  • In your terminal, make sure you are in the project directory.

  • Run the following command:

streamlit run stock_picker_app.py

Your default web browser will automatically open a new tab with the running application.

How to Use the App

The application has two main sections, accessible from the sidebar navigation: GUI image

Chat

This is the main interactive page. You can use natural language to ask the AI analyst to perform tasks. Try prompts like:

  • "find stocks": The assistant will use Perplexity AI to suggest a list of small-cap tickers.

  • "analyze AAPL": The assistant will fetch financial data for the specified ticker (e.g., AAPL), use GPT-4o to analyze it, and provide a recommendation. If the recommendation is actionable (BUY, SELL, SHORT), a button will appear to execute the trade.

  • "sell AAPL": If you have a position in the specified ticker, the assistant will ask for confirmation and provide a button to execute the sale.

  • "check house and senate trades for {ticker}" - shows all the trades done by Congress officials for that stock.

  • "get technicals {ticker}" - calculates the major technical indicators and shows them in nice graphs.

  • "get trends {ticker}" - uses GPT-4 to create Google searches related to the {ticker} and checks Google Trends for these queries.

  • "hedge" - Proposes a hedging strategy for your portfolio. Example output: 🛡️ Hedge Proposal: To hedge your portfolio, I recommend buying XYZ. Justification: Diversifies risk exposure to tech-heavy positions.

  • "get news {ticker}" - Fetches the latest news articles for the ticker and shows title, source, date, description and a link.

  • "get social sentiment {ticker}" - Fetches Reddit posts from r/wallstreetbets and r/stocks

  • check house and senate trades for {ticker} - Shows trades by U.S. Congress officials for the stock.

Portfolio Performance

This page provides a comprehensive overview of your investment activities. It includes:

  • Trade History: A complete table of every transaction you've made.

  • Current Holdings: A summary of the stocks you currently own, including the number of shares, current market value, and the unrealized gain or loss.

  • Total Portfolio Value: A metric showing the total current market value of all your holdings.

  • Portfolio Value Over Time: An area chart visualizing the growth of your portfolio's value since your first trade.

Backtesting Engine

This page allows you to test trading strategies on historical data to evaluate performance. It includes:

  • Strategy Simulation: Runs a Simple Moving Average (SMA) Crossover strategy:

    • Buy when the 10-day moving average crosses above the 30-day moving average.

    • Sell when the 10-day moving average crosses below the 30-day moving average.

  • User Inputs: Select a ticker symbol, date range, and initial cash amount.

  • Performance Metrics: After running a backtest, you’ll see key statistics such as:

    • Total Return [%]

    • Max Drawdown [%]

    • Sharpe Ratio

    • Win Rate [%]

  • Interactive Chart: A plot showing the buy/sell signals, equity curve, and benchmark performance.

  • Detailed Statistics: Expandable table with a full breakdown of backtest results.

Event Calendar

This page helps you stay informed about important market events for your portfolio. It includes:

  • Upcoming Earnings: Displays the next earnings reports for companies in your portfolio.

  • Dividend Dates: Lists upcoming dividend payment dates for your holdings.

  • Economic Events: Shows key U.S. economic events such as FOMC meetings, CPI releases, and other macro reports.

Each tab dynamically updates based on the tickers in your saved portfolio. If your portfolio is empty, the page prompts you to add stocks first.

Key Macroeconomic Indicators

This page provides a dashboard of U.S. economic health using data from the FRED (Federal Reserve Economic Data) API. It includes:

  • Real GDP (GDPC1): Measures inflation-adjusted economic output.

  • Unemployment Rate (UNRATE): Tracks the percentage of jobless workers actively seeking employment.

  • Consumer Price Index (CPI): A primary measure of inflation in consumer goods and services.

  • Federal Funds Rate (DFF): The central interest rate influencing U.S. monetary policy.

  • Consumer Sentiment Index (UMCSENT): Gauges consumer confidence in the economy.

  • Housing Starts (HOUST): Indicates new residential construction activity.

For each indicator, the page shows:

  • A latest value and date.

  • An interactive historical chart for trend analysis.

This project is free for everyone. If you'd wish to donate, use the following button: ☕ Buy me a coffee via PayPal