https://github.com/daniil0518/tradingbot_alpaca
Automated Trading Bot using Moving Average Crossover Strategy
https://github.com/daniil0518/tradingbot_alpaca
alpaca alpaca-trading-api bot moving-average ordering python trading trading-strategy
Last synced: about 1 year ago
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Automated Trading Bot using Moving Average Crossover Strategy
- Host: GitHub
- URL: https://github.com/daniil0518/tradingbot_alpaca
- Owner: daniil0518
- Created: 2024-06-20T13:39:22.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-06-20T14:58:22.000Z (almost 2 years ago)
- Last Synced: 2025-02-06T14:38:16.250Z (over 1 year ago)
- Topics: alpaca, alpaca-trading-api, bot, moving-average, ordering, python, trading, trading-strategy
- Language: Python
- Homepage: https://github.com/daniil0518/tradingbot_alpaca
- Size: 7.81 KB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Automated Trading Bot using Moving Average Crossover Strategy
## Overview
This project implements an automated trading bot in Python that utilizes a moving average crossover strategy to make buy/sell decisions in financial markets. The bot is designed to execute trades based on the crossing of short-term and long-term moving averages, a popular strategy used by traders to identify potential trend reversals.
## Features
- Fetches real-time market data using the Alpaca API.
- Calculates short-term and long-term moving averages of asset prices.
- Generates buy signals when the short-term moving average crosses above the long-term moving average.
- Generates sell signals when the short-term moving average crosses below the long-term moving average.
- Implements risk management measures to control position sizing and minimize losses.
- Provides backtesting functionality to evaluate the bot's performance using historical data.
## Setup
1. Clone the repository:
```bash
git clone https://github.com/daniil0518/tradingbot_alpaca.git
cd tradingbot_alpaca
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
3. Obtain API keys:
- Sign up for an account on Alpaca and obtain your API key and secret key.
4. Update configuration:
- Replace `'your_api_key'` and `'your_secret_key'` in the code with your actual Alpaca API key and secret key.
5. Run the bot:
```bash
python main.py
```
## Usage
- Customize the asset symbol and moving average periods in the code according to your preferences.
- Monitor the bot's output to receive buy/sell signals and execute trades accordingly.
- Backtest the bot's performance using historical data to evaluate its effectiveness.
## Acknowledgements
- This project utilizes the [Alpaca API](https://alpaca.markets/docs/api-documentation/) for accessing real-time market data and executing trades.
## Disclaimer
- This project is for educational and informational purposes only. Automated trading bots involve risks, and past performance is not indicative of future results. Use at your own risk.
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