plutex 0.2.1

plutex: An AI-powered trading system using multiple agents

plutex

This is a proof of concept for an AI-powered trading system. The goal of this project is to explore the use of AI to make trading decisions. This project is for educational purposes only and is not intended for real trading or investment.

This system employs several agents working together:

1. Ben Graham Agent - The godfather of value investing, only buys hidden gems with a margin of safety.
2. Bill Ackman Agent - An activist investor, takes bold positions and pushes for change.
3. Cathie Wood Agent - The queen of growth investing, believes in the power of innovation and disruption.
4. Charlie Munger Agent - Warren Buffett's partner, only buys wonderful businesses at fair prices.
5. Peter Lynch Agent - Legendary growth investor who seeks "ten-baggers" and invests in what he knows.
6. Phil Fisher Agent - Legendary growth investor who mastered scuttlebutt analysis.
7. Stanley Druckenmiller Agent - Macro legend who hunts for asymmetric opportunities with growth potential.
8. Warren Buffett Agent - The oracle of Omaha, seeks wonderful companies at a fair price.
9. Valuation Agent - Calculates the intrinsic value of a stock and generates trading signals.
10. Sentiment Agent - Analyzes market sentiment and generates trading signals.
11. Fundamentals Agent - Analyzes fundamental data and generates trading signals.
12. Technicals Agent - Analyzes technical indicators and generates trading signals.
13. Risk Manager - Calculates risk metrics and sets position limits.
14. Portfolio Manager - Makes final trading decisions and generates orders.

graph LR
    subgraph Input
        Start((Start))
    end

    subgraph Agents
        direction TB
        A1[Ben Graham Agent]
        A2[Bill Ackman Agent]
        A3[Cathie Wood Agent]
        A4[Charlie Munger Agent]
        A5[Phil Fisher Agent]
        A6[Stan Druckenmiller Agent]
        A7[Warren Buffett Agent]
        A8[Valuation Agent]
        A9[Sentiment Agent]
        A10[Fundamentals Agent]
        A11[Technicals Agent]
    end

    subgraph DecisionPipeline
        RM[Risk Manager]
        PM[Portfolio Manager]
        TD(make trading decision)
    end

    subgraph Actions
        B[Buy]
        C[Cover]
        S[Sell]
        SH[Short]
        H[Hold]
    end

    Start -- "[1] pick agents" --> A1
    Agents -- "[2] trading signals" --> RM
    RM -- "[3] risk signals" --> PM
    PM --> TD
    PM -- "[4] take action" --> B
    PM -- "[4] take action" --> C
    PM -- "[4] take action" --> S
    PM -- "[4] take action" --> SH
    PM -- "[4] take action" --> H

    %% style B fill:#90ee90,stroke:#333,stroke-width:2px
    %% style C fill:#90ee90,stroke:#333,stroke-width:2px
    %% style S fill:#f08080,stroke:#333,stroke-width:2px
    %% style SH fill:#f08080,stroke:#333,stroke-width:2px
    %% style H fill:#add8e6,stroke:#333,stroke-width:2px
    %% style Agents fill:#ffe4b5,stroke:#333,stroke-width:2px
    %% style RM fill:#ffe4b5,stroke:#333,stroke-width:2px
    %% style PM fill:#ffe4b5,stroke:#333,stroke-width:2px
    %% style Start fill:#d3d3d3,stroke:#333,stroke-width:2px
    %% style TD fill:#d3d3d3,stroke:#333,stroke-width:1px,stroke-dasharray: 5 5

Note: the system simulates trading decisions, it does not actually trade.

Disclaimer

This project is for educational and research purposes only.

• Not intended for real trading or investment
• No warranties or guarantees provided
• Past performance does not indicate future results
• Creator assumes no liability for financial losses
• Consult a financial advisor for investment decisions

By using this software, you agree to use it solely for learning purposes.

Table of Contents

• plutex
  • Disclaimer
  • Table of Contents
  • Prerequisites
  • Setup
  • Usage
    • Running plutex
    • Running the Backtester
  • Project Structure
  • Contributing
  • Feature Requests
  • License

Prerequisites

• Python >= 3.11: This project requires Python 3.11 or newer.
• uv: This project uses uv for environment and package management. Install it if you haven't already: https://github.com/astral-sh/uv#installation

Setup

1. Clone the repository:

   git clone https://github.com/shaneholloman/plutex.git
   cd plutex
   

2. (Optional) Install Python 3.11+ using uv: If you don't have a suitable Python version installed, you can install one managed by uv:

   # Example: Install Python 3.11
   uv python install 3.11
   # List available/installed versions
   uv python list
   

3. Create and activate the virtual environment: This command creates a .venv directory using the specified Python version (or a compatible one found by uv) and activates it.

   # Use the specific version you want (e.g., 3.11)
   uv venv --python 3.11
   source .venv/bin/activate
   # On Windows use: .venv\Scripts\activate
   

4. Install dependencies: This installs all packages listed in pyproject.toml into your virtual environment.

   uv sync
   

5. Set up environment variables: Copy the example file and add your API keys.

   cp .env.example .env
   

   Now, edit the .env file and replace the placeholder keys with your actual API keys:

   # .env file contents:
   ANTHROPIC_API_KEY=your-anthropic-api-key
   DEEPSEEK_API_KEY=your-deepseek-api-key
   GROQ_API_KEY=your-groq-api-key
   GOOGLE_API_KEY=your-google-api-key
   FINANCIAL_DATASETS_API_KEY=your-financial-datasets-api-key
   OPENAI_API_KEY=your-openai-api-key
   

   Important: You need to set the API key for at least one LLM provider (ANTHROPIC_API_KEY, GOOGLE_API_KEY, OPENAI_API_KEY, GROQ_API_KEY, DEEPSEEK_API_KEY) for the application to work. You will be prompted to choose a model from the available providers when running the script.

   Financial data for AAPL, GOOGL, MSFT, NVDA, and TSLA is free via the Financial Datasets API. For any other ticker, you must set the FINANCIAL_DATASETS_API_KEY.

Usage

Ensure your virtual environment is activated (source .venv/bin/activate).

Running plutex

Run the main script, providing the required --tickers argument. You will be interactively prompted to select analysts and an LLM model.

# Basic run with specific tickers
python -m src.main --tickers AAPL,MSFT,NVDA

# Run with reasoning shown
python -m src.main --tickers AAPL,MSFT,NVDA --show-reasoning

# Run for a specific date range
python -m src.main --tickers AAPL,MSFT,NVDA --start-date 2025-01-01 --end-date 2025-03-01

# Run with specific initial cash (e.g., $50,000)
python -m src.main --tickers AAPL,MSFT,NVDA --initial-cash 50000

# Run with a specific margin requirement (e.g., 50%)
python -m src.main --tickers AAPL,MSFT,NVDA --margin-requirement 0.5

# Run and save the agent graph visualization (saves as [analyst_name(s)]_graph.png)
python -m src.main --tickers AAPL --show-agent-graph

Example Output: (Output format may vary)

python src/main.py --ticker AAPL,MSFT,NVDA
? Select your AI analysts. [Cathie Wood]

Selected analysts: Cathie Wood

? Select your LLM model: [gemini] gemini-2.5-pro

Selected Gemini model: gemini-2.5-pro-exp-03-25

 ✓ Cathie Wood         [NVDA] Done
 ✓ Risk Management     [NVDA] Done
 ✓ Portfolio Management[NVDA] Done

Analysis for AAPL
==================================================

AGENT ANALYSIS: [AAPL]
+-------------+----------+--------------+--------------------------------------------------------------+
| Agent       |  Signal  |   Confidence | Reasoning                                                    |
+=============+==========+==============+==============================================================+
| Cathie Wood | BEARISH  |        70.0% | While Apple is undeniably a technology leader with           |
|             |          |              | impressive scale and profitability, its current trajectory   |
|             |          |              | doesn't align with our core focus on disruptive innovation   |
|             |          |              | poised for exponential growth. The analysis indicates R&D    |
|             |          |              | investment sits at only 6.8% of revenue. For companies truly |
|             |          |              | shaping the future and creating new markets, we typically    |
|             |          |              | look for much more aggressive investment in breakthrough     |
|             |          |              | technologies – often exceeding 15-20%. While positive free   |
|             |          |              | cash flow and operating leverage are noted, these metrics    |
|             |          |              | reflect a mature, optimizing company rather than one on the  |
|             |          |              | cusp of exponential disruption. Apple appears focused on     |
|             |          |              | incremental improvements within its established ecosystem,   |
|             |          |              | lacking the clear, game-changing technological shifts or     |
|             |          |              | platform launches we seek that could unlock multi-fold       |
|             |          |              | growth from here. Furthermore, the current valuation         |
|             |          |              | suggests the market has already priced in significant        |
|             |          |              | success, potentially limiting the asymmetric upside          |
|             |          |              | potential we target over a 5+ year horizon. We need to see   |
|             |          |              | clearer evidence of investment in truly transformative areas |
|             |          |              | – like autonomous systems, next-generation AI integration    |
|             |          |              | beyond current capabilities, or novel hardware platforms –   |
|             |          |              | to become bullish on Apple as a core disruptive innovator    |
|             |          |              | for the next decade.                                         |
+-------------+----------+--------------+--------------------------------------------------------------+

TRADING DECISION: [AAPL]
+------------+--------------------------------------------------------------+
| Action     | SHORT                                                        |
+------------+--------------------------------------------------------------+
| Quantity   | 89                                                           |
+------------+--------------------------------------------------------------+
| Confidence | 70.0%                                                        |
+------------+--------------------------------------------------------------+
| Reasoning  | Bearish signal with 70.0 confidence. Opening a short         |
|            | position. The quantity is capped at the max_shares guideline |
|            | (89) for risk management, treating it as a position size     |
|            | limit. The margin requirement is 0.00, so margin             |
|            | availability is not a constraint for this trade size         |
|            | (Position Value: 89 * $222.57 = $19,808.73; Margin Used:     |
|            | $0.00).                                                      |
+------------+--------------------------------------------------------------+

Analysis for MSFT
==================================================

AGENT ANALYSIS: [MSFT]
+-------------+----------+--------------+--------------------------------------------------------------+
| Agent       |  Signal  |   Confidence | Reasoning                                                    |
+=============+==========+==============+==============================================================+
| Cathie Wood | NEUTRAL  |        65.0% | Microsoft stands at the critical intersection of two major   |
|             |          |              | disruptive forces: Cloud Computing via Azure and Artificial  |
|             |          |              | Intelligence, particularly through its integration of        |
|             |          |              | generative AI like Copilot across its vast software suite.   |
|             |          |              | This positioning taps into enormous, expanding TAMs. We see  |
|             |          |              | evidence of their commitment to innovation with increasing   |
|             |          |              | R&D intensity, now at 13.5% of revenue, fueling advancements |
|             |          |              | in these key areas. Their impressive operating margins       |
|             |          |              | (38.9%) and consistent Free Cash Flow generation provide     |
|             |          |              | substantial resources to reinvest in maintaining             |
|             |          |              | technological leadership and scaling these innovations       |
|             |          |              | globally. However, the provided analysis indicates a         |
|             |          |              | significant valuation premium, with the market               |
|             |          |              | capitalization far exceeding calculated intrinsic value      |
|             |          |              | (-50.13% margin of safety). While we firmly believe          |
|             |          |              | traditional valuation metrics often underestimate the        |
|             |          |              | exponential growth trajectories of true disruptors over our  |
|             |          |              | preferred 5+ year horizon, the current valuation demands a   |
|             |          |              | degree of caution. We remain watchful; Microsoft's AI        |
|             |          |              | integration holds transformative potential to reshape        |
|             |          |              | productivity and enterprise operations, creating entirely    |
|             |          |              | new value streams. While the current signal is neutral based |
|             |          |              | on valuation metrics, its strategic positioning in AI and    |
|             |          |              | Cloud keeps it high on our conviction list, pending evidence |
|             |          |              | of AI adoption translating into accelerating growth that     |
|             |          |              | justifies the premium or a more favorable entry point.       |
+-------------+----------+--------------+--------------------------------------------------------------+

TRADING DECISION: [MSFT]
+------------+-------------------------------------------------------+
| Action     | HOLD                                                  |
+------------+-------------------------------------------------------+
| Quantity   | 0                                                     |
+------------+-------------------------------------------------------+
| Confidence | 65.0%                                                 |
+------------+-------------------------------------------------------+
| Reasoning  | Neutral signal (65.0 confidence) indicates no strong  |
|            | directional bias. Holding position as per the signal. |
+------------+-------------------------------------------------------+

Analysis for NVDA
==================================================

AGENT ANALYSIS: [NVDA]
+-------------+----------+--------------+--------------------------------------------------------------+
| Agent       |  Signal  |   Confidence | Reasoning                                                    |
+=============+==========+==============+==============================================================+
| Cathie Wood | BULLISH  |        85.0% | NVIDIA isn't just a semiconductor company; it's the engine   |
|             |          |              | powering the artificial intelligence revolution, a           |
|             |          |              | technological shift we believe is among the most             |
|             |          |              | transformative in history. Their GPUs are the critical       |
|             |          |              | infrastructure enabling breakthroughs across deep learning,  |
|             |          |              | data centers, autonomous systems, and beyond – truly         |
|             |          |              | disruptive innovation at its finest. The data shows          |
|             |          |              | accelerating revenue momentum and, crucially, a massive      |
|             |          |              | commitment to R&D, now at 23.5% of revenue and significantly |
|             |          |              | increasing. This isn't just spending; it's investment in     |
|             |          |              | maintaining leadership and expanding the technological moat  |
|             |          |              | in a market with an almost unimaginable Total Addressable    |
|             |          |              | Market (TAM) as AI integrates into every facet of the global |
|             |          |              | economy. While traditional valuation metrics, like the       |
|             |          |              | calculated intrinsic value showing a large negative margin   |
|             |          |              | of safety, might seem daunting, they often fail to capture   |
|             |          |              | the sheer scale and exponential nature of the S-curve        |
|             |          |              | adoption we anticipate for AI compute over the next 5-10     |
|             |          |              | years. NVIDIA's consistent positive free cash flow fuels     |
|             |          |              | this innovation engine, allowing them to reinvest heavily in |
|             |          |              | future growth platforms like CUDA and their full-stack       |
|             |          |              | solutions. We see NVIDIA as a foundational holding for       |
|             |          |              | exposure to the exponential growth trajectories unlocked by  |
|             |          |              | artificial intelligence, accepting near-term volatility for  |
|             |          |              | the potential of significant long-term, multi-year           |
|             |          |              | appreciation as they continue to execute on their visionary  |
|             |          |              | roadmap.                                                     |
+-------------+----------+--------------+--------------------------------------------------------------+

TRADING DECISION: [NVDA]
+------------+------------------------------------------------------------+
| Action     | BUY                                                        |
+------------+------------------------------------------------------------+
| Quantity   | 183                                                        |
+------------+------------------------------------------------------------+
| Confidence | 85.0%                                                      |
+------------+------------------------------------------------------------+
| Reasoning  | Strong bullish signal (85.0 confidence). Opening a long    |
|            | position. Buying the maximum allowed shares (183) as the   |
|            | total cost (183 * $109.12 = $19,948.96) is well within the |
|            | available portfolio cash ($100,000.00).                    |
+------------+------------------------------------------------------------+

PORTFOLIO SUMMARY:
+----------+----------+------------+--------------+
| Ticker   |  Action  |   Quantity |   Confidence |
+==========+==========+============+==============+
| AAPL     |  SHORT   |         89 |        70.0% |
+----------+----------+------------+--------------+
| MSFT     |   HOLD   |          0 |        65.0% |
+----------+----------+------------+--------------+
| NVDA     |   BUY    |        183 |        85.0% |
+----------+----------+------------+--------------+

Portfolio Strategy:
Bearish signal with 70.0 confidence. Opening a short
position. The quantity is capped at the max_shares guideline
(89) for risk management, treating it as a position size
limit. The margin requirement is 0.00, so margin
availability is not a constraint for this trade size
(Position Value: 89 * $222.57 = $19,808.73; Margin Used:
$0.00).
  plutex 3.11.11  shaneholloman @ bird.yoyo.io  plutex  main 

Running the Backtester

Run the backtester script similarly:

python src/backtester.py --tickers AAPL,MSFT,NVDA

# Backtest over a specific date range
python src/backtester.py --tickers AAPL,MSFT,NVDA --start-date 2025-01-01 --end-date 2025-03-01

Example Output: (Output format may vary)

Project Structure

plutex/
├── src/
│   ├── agents/                   # Agent definitions and workflow
│   │   ├── bill_ackman.py        # Bill Ackman agent
│   │   ├── fundamentals.py       # Fundamental analysis agent
│   │   ├── portfolio_manager.py  # Portfolio management agent
│   │   ├── risk_manager.py       # Risk management agent
│   │   ├── sentiment.py          # Sentiment analysis agent
│   │   ├── technicals.py         # Technical analysis agent
│   │   ├── valuation.py          # Valuation analysis agent
│   │   ├── warren_buffett.py     # Warren Buffett agent
│   ├── tools/                    # Agent tools
│   │   ├── api.py                # API tools
│   ├── backtester.py             # Backtesting tools
│   ├── main.py                   # Main entry point
├── pyproject.toml
├── uv.lock                     # Lock file generated by uv
├── .env.example                # Example environment variables
├── .env                        # Your environment variables (ignored by git)
├── docs/                       # Documentation
│   └── initial_setup_notes.md  # Notes from initial setup
├── archive/                    # Archived scripts
│   └── fix_unions.py           # Script used during Python 3.9 -> 3.11 transition
├── ...

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

Important: Please keep your pull requests small and focused. This will make it easier to review and merge.

Feature Requests

If you have a feature request, please open an issue and make sure it is tagged with enhancement.

License

This project is licensed under the MIT License - see the LICENSE file for details.