Handling Multiple Pairs and Portfolios with freqtrade

In the fast-paced world of cryptocurrency trading, automated trading bots like freqtrade allow traders to efficiently manage multiple pairs and portfolios. By leveraging freqtrade, traders can execute strategies across a wide range of cryptocurrency pairs, distribute risk, and optimize returns. This article will guide you through the steps required to handle multiple pairs and portfolios using freqtrade.

What is freqtrade?

Freqtrade is a free and open-source cryptocurrency trading bot that provides powerful tools for developing and implementing custom trading strategies. It’s designed for both beginner and advanced traders, offering a wide range of configuration options to tailor the bot to specific trading needs.

Setting Up freqtrade

Before diving into multiple pairs and portfolios, ensure you've set up freqtrade and have a basic understanding of its features. If you haven’t installed freqtrade yet, follow these quick steps to get started:

# Install freqtrade
$ git clone https://github.com/freqtrade/freqtrade.git
$ cd freqtrade
$ ./setup.sh -i

# Configure your environment
$ freqtrade new-config --config config.json

Managing Multiple Trading Pairs

One core strength of freqtrade is its capacity to manage trades across multiple pairs. You can specify the trading pairs in the configuration file. Here’s a simple example of how to list multiple trading pairs in the documentation:

{
    "pairs": [
        "BTC/USDT",
        "ETH/USDT",
        "LTC/USDT",
        "XRP/USDT"
    ],
    "stake_currency": "USDT",
    "stake_amount": 10,
    "tradable_balance_ratio": 0.99,
}

Adding multiple pairs in your config.json increases diversity and spreads your risk across different assets, thereby maximizing potential profitability while limiting exposure to a single asset's downturn.

Portfolio Management

With freqtrade, portfolio management becomes substantially easier. By managing multiple strategies and market conditions, you ensure that your bots keep working optimally even during market fluctuations. Here’s how you can optimize your bot for various portfolios:

• Strategy Mixing: Create and apply different strategies according to current market trends.
• Risk Allocation: Diversify across multiple pairs but also decide on appropriate risk levels per trade and per strategy.

For example, you might have one portfolio aggressive with high-risk assets during bull markets and another conservative one for bear markets.

Developing and Testing Strategies

A key step includes coding your strategy and testing it thoroughly using freqtrade's backtesting capabilities. Here's a simple Python example of a strategy:

from freqtrade.strategy import IStrategy

class MyStrategy(IStrategy):
    minimal_roi = {
        "40": 0.10,
        "20": 0.05,
        "0": 0.02
    }

    stoploss = -0.10
    timeframe = '5m'

    def populate_indicators(self, dataframe, metadata):
        # Example: Add some indicators
        dataframe['sma'] = ta.SMA(dataframe, timeperiod=20)
        return dataframe

    def populate_entry_trend(self, dataframe, metadata):
        dataframe.loc[(dataframe['close'] > dataframe['sma']), 'buy'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe, metadata):
        dataframe.loc[(dataframe['close'] < dataframe['sma']), 'sell'] = 1
        return dataframe

Backtesting and Performance Evaluation

Frequent backtesting using historical data is essential for optimizing trading strategies. Freqtrade provides commands for quick strategy assessments:

# Run backtesting
$ freqtrade backtesting --config config.json --strategy MyStrategy

This process provides insights into potential profitability and risk, allowing traders to fine-tune their approaches before deploying them in live environments.

Conclusion

Through freqtrade, handling multiple pairs and portfolios offers flexibility and scalability crucial for automating profitable trading activities. By understanding and utilizing its features such as configuration, strategy diversification, backtesting, and performance evaluation, traders are equipped to navigate the challenges and opportunities within the cryptocurrency markets.