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README.md
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# invest-bot: Tech Giants Trading Bot
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## Algorithmic trading system using Alpaca API
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`invest-bot` is a sophisticated algorithmic trading bot designed to trade a diversified portfolio of 50 "Tech Giants" stocks. It employs a hybrid strategy combining momentum and mean-reversion principles, leveraging various technical indicators to generate precise trade signals. The bot supports both live paper trading and extensive backtesting with historical data, complete with a real-time web dashboard for monitoring performance.
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## Table of Contents
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- [Features](#features)
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- [Getting Started](#getting-started)
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- [Prerequisites](#prerequisites)
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- [Installation](#installation)
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- [Configuration](#configuration)
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- [Usage](#usage)
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- [Live Trading](#live-trading)
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- [Backtesting](#backtesting)
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- [Web Dashboard](#web-dashboard)
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- [Strategy Overview](#strategy-overview)
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- [Technology Stack](#technology-stack)
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- [Contributing](#contributing)
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- [License](#license)
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- [Acknowledgements](#acknowledgements)
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## Features
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- **Hybrid Trading Strategy**: Combines momentum and mean-reversion logic for robust signal generation.
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- **Multi-Indicator Analysis**: Utilizes a suite of technical indicators including:
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- Relative Strength Index (RSI)
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- Moving Average Convergence Divergence (MACD)
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- Exponential Moving Averages (EMA)
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- Average Directional Index (ADX)
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- Bollinger Bands
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- Custom Momentum Indicators
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- **Live Paper Trading**: Execute trades in a simulated environment using the Alpaca API, without risking real capital.
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- **Comprehensive Backtesting**: Test the strategy against historical data over custom periods (years, months) and initial capital.
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- **Real-time Web Dashboard**: Monitor portfolio performance, account statistics, and open positions through a responsive web interface.
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- **Configurable Timeframes**: Run the bot on `Daily` or `Hourly` data bars.
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- **Robust Logging**: Detailed logging for both console and file, aiding in monitoring and debugging.
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- **Error Handling & Rate Limiting**: Graceful error management and adherence to API rate limits for stable operation.
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## Getting Started
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Follow these instructions to set up and run the `invest-bot`.
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### Prerequisites
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- [Rust](https://www.rust-lang.org/tools/install) (latest stable version recommended)
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- [Alpaca API Key and Secret Key](https://alpaca.markets/) (for paper trading)
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### Installation
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1. **Clone the repository:**
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```bash
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git clone https://github.com/your-username/invest-bot.git
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cd invest-bot
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```
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2. **Build the project:**
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```bash
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cargo build --release
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```
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This will compile the optimized release binary in `target/release/invest-bot`.
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### Configuration
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The bot requires API credentials and can be configured via environment variables. Create a `.env` file in the project root directory:
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```
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ALPACA_API_KEY=YOUR_ALPACA_API_KEY
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ALPACA_SECRET_KEY=YOUR_ALPACA_SECRET_KEY
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DASHBOARD_PORT=5000 # Optional: Customize the dashboard port
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```
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**Note:** Replace `YOUR_ALPACA_API_KEY` and `YOUR_ALPACA_SECRET_KEY` with your actual Alpaca paper trading API keys.
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## Usage
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### Live Trading
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To run the bot in live paper trading mode:
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```bash
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cargo run --release
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# Or, if you have built the release binary:
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# ./target/release/invest-bot
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```
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By default, the bot runs with `Daily` timeframe bars. To specify `Hourly` bars:
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```bash
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cargo run --release -- --timeframe hourly
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```
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The bot will continuously analyze the market during trading hours, execute trades, and update the dashboard.
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### Backtesting
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To backtest the strategy with historical data, use the `--backtest` flag. You can specify the duration (years/months) and initial capital.
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- **Backtest for 3 years (default capital):**
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```bash
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cargo run --release -- --backtest --years 3
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```
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- **Backtest for 5 years with custom capital:**
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```bash
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cargo run --release -- --backtest --years 5 --capital 50000
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```
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- **Combine years and months:**
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```bash
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cargo run --release -- --backtest --years 1 --months 6
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```
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- **Hourly timeframe backtest:**
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```bash
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cargo run --release -- --backtest --years 1 --timeframe hourly
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```
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Backtest results, including equity curve and trades, will be saved to `backtest_equity_curve.csv` and `backtest_trades.csv` respectively.
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### Web Dashboard
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When running in live trading mode, a real-time web dashboard is automatically started. Access it in your browser at:
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```
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http://localhost:5000
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```
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(or your custom `DASHBOARD_PORT`). The dashboard displays:
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- Account summary (portfolio value, cash, buying power)
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- Real-time portfolio performance graph
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- Current open positions
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## Strategy Overview
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The `invest-bot` utilizes a dynamic hybrid strategy. It identifies potential trades using a combination of:
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- **RSI (Relative Strength Index):** To gauge overbought/oversold conditions and mean-reversion opportunities.
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- **MACD (Moving Average Convergence Divergence):** For trend identification and reversals.
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- **EMA (Exponential Moving Averages):** To determine short-term and long-term trends.
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- **ADX (Average Directional Index):** To measure trend strength.
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- **Bollinger Bands:** To identify volatility and potential price breakouts/reversals.
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- **Momentum:** Custom indicators to capture price acceleration.
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Risk management includes position sizing based on portfolio value and buying power, with integrated stop-loss and take-profit mechanisms.
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## Technology Stack
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- **Rust**: Primary programming language for performance and safety.
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- **Tokio**: Asynchronous runtime for concurrent operations (e.g., API calls, dashboard).
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- **Alpaca API**: For market data, account information, and trade execution (paper trading).
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- **Axum**: Web framework for building the real-time dashboard.
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- **Chart.js**: JavaScript library for interactive chart visualization on the dashboard.
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- **Serde**: Rust serialization/deserialization framework for JSON and CSV.
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- **Clap**: Command-line argument parser for a user-friendly CLI.
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- **Dotenvy**: For managing environment variables.
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- **Tracing**: Structured logging framework.
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## Contributing
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Contributions are welcome! Please feel free to open an issue or submit a pull request.
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## License
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This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details (if applicable).
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## Acknowledgements
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- [Alpaca.markets](https://alpaca.markets/) for their accessible trading API.
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- [Rust Community](https://www.rust-lang.org/) for an amazing language and ecosystem.
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- [Chart.js](https://www.chartjs.org/) for the powerful charting library.
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