CryptoTrader

CryptoTrader allows easily development of investment strategies for cryptocurrency. It mainly simulate trading strategies against historical data to evaluate their performance.

Visualization Demo

CryptoTracker provide a visualization tool to easily trace the performance (i.e., the cumulated net profit) of your strategy.

Prerequisites

This project uses Python 3.10. Before running this project, ensure you have Python 3.10 installed on your system. Besides, install all required packages by executing the following command:

pip install -r requirements.txt

Setup

Before running the backtesting process, configure your directory paths in the .env.sh file. This file should contain the following entries:

export DATA_ROOT=/path/to/your/data/directory/
export RESULTS_ROOT=/path/to/your/results/directory/

Replace /path/to/your/data/directory/ and /path/to/your/results/directory/ with the actual paths to your data and results directories respectively.

After configuring the paths, execute the following command to load the environment variables:

source .env.sh

Usage

Before running the backtesting process, you need to specify your strategy configuration in a JSON file. Currently, we support two default strategies:

• grid_trading
• dca

Strategy Configuration

This is a sample configuration for grid_trading

Create a JSON file named strategy_config.json, with the following content:

{
    "name": "grid_trading",
    "config": {
        "budget": 200,
        "leverage": 30,
        "amount": 0.0001,
        "highest": 75000,
        "lowest": 60000,
        "num_interval": 20
    }
}

Adjust the parameters according to your desired configuration.

Backtesting

To initiate the backtesting process, use the following command:

python main --symbol <SYMBOL> --start_time <START_TIME> --end_time <END_TIME> --fetch_price

Parameters

• --symbol: Specifies the cryptocurrency pair you would like to invest in, for instance, btcusdt.
• --start_time: Specifies the start time for backtesting. Format: YYYY-MM-DD HH:MM:SS.
• --end_time: Specifies the end time for backtesting. If not specified, the current time will be used as the end time.
• --fetch_price: Optional flag. When included, the program will automatically fetch all required prices for testing on the specified time interval.

Example

python main --symbol btcusdt --start_time "2024-04-05 20:32:00" --end_time "2024-04-14 17:34:00" --fetch_price

This command will execute the backtesting process from 20:32:00 April 5th, 2024, to 17:34:00 April 14th, 2024, and fetch all necessary prices for testing.

Results

The results of the backtesting process will be stored in the specified RESULTS_ROOT directory. You can analyze these results to evaluate the performance of your investment strategy.