https://github.com/yllvar/interactive-broker-sma-crossover
Trading On IKBR: SMA (Simple Moving Average) crossover. By analyzing the moving averages of asset prices, we can determine entry and exit points for our trades. The goal is to buy when the short-term moving average crosses above the long-term moving average and sell when the opposite occurs.
https://github.com/yllvar/interactive-broker-sma-crossover
Last synced: about 1 year ago
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Trading On IKBR: SMA (Simple Moving Average) crossover. By analyzing the moving averages of asset prices, we can determine entry and exit points for our trades. The goal is to buy when the short-term moving average crosses above the long-term moving average and sell when the opposite occurs.
- Host: GitHub
- URL: https://github.com/yllvar/interactive-broker-sma-crossover
- Owner: yllvar
- Created: 2024-04-17T06:53:40.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-04-17T07:05:03.000Z (about 2 years ago)
- Last Synced: 2025-02-17T23:42:02.319Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 14.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# SMA-Crossover Algorithmic Trading with Interactive
By analyzing the moving averages of asset prices, we can determine entry and exit points for our trades. The goal is to buy when the short-term moving average crosses above the long-term moving average and sell when the opposite occurs.
# Algorithmic Trading with Interactive Brokers API
Welcome to the repository for algorithmic trading using the Interactive Brokers API! In this project, we explore the world of automated trading strategies using Python and Interactive Brokers API.
## Getting Started
Follow these steps to set up the project on your local machine:
### 1. Clone the Repository
```bash
git clone https://github.com/yourusername/algorithmic-trading.git
```
### 2. Install Jupyter Notebook
If you haven't already installed Jupyter Notebook, you can do so using pip:
```bash
pip install notebook
```
### 3. Install Libraries and Dependencies
Navigate to the project directory and install the required libraries and dependencies using pip:
```bash
cd algorithmic-trading
pip install -r requirements.txt
```
### 4. Set up Interactive Brokers API
Before running the code, you need to set up the Interactive Brokers API:
- Visit the Interactive Brokers website and sign up for an account if you haven't already.
- Obtain your API credentials from Interactive Brokers.
- Configure your API settings in the `config.py` file.
### 5. Safety and Disclaimer
It's essential to understand the risks involved in algorithmic trading:
- Algorithmic trading involves financial risk, and past performance does not guarantee future results.
- The strategies implemented in this project are for educational purposes only and should not be considered financial advice.
- By using this code, you agree that you are solely responsible for any losses incurred during trading.
## Disclaimer
I am not responsible for any losses incurred while using this code. Use it at your own risk.
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