This is the name of our new course, and in this article, we will share more of our experience in algorithmic trading with cryptocurrency.
Challenges of Trading Cryptocurrency After the Boom
Cryptocurrency became popular after the boom in the last two years, but this is also the challenge. Only a few people benefited from holding cheap Bitcoin for years. The question now is, how can we trade it now that it’s already expensive?
Why Algorithmic Trading is the Solution
Algorithmic trading is the answer, especially as many brokers now provide access to popular cryptocurrencies like Bitcoin, Ethereum, and Ripple. It’s time to collect enough historical data to create robust trading strategies.
Collecting Historical Data from Brokers
To create successful strategies, it is crucial to collect historical bars from the broker we use. Open your MetaTrader platform and press the Home Key on each time frame. This action forces MetaTrader to load more bars.
However, for cryptocurrency, you might get only up to 100,000 bars on the M1 timeframe, which isn’t enough. To gather more data, you’ll need to leave MetaTrader running for weeks or months.
Inconsistent Broker Data and Its Impact on Expert Advisors (EAs)
Different brokers offer varying daily prices for Bitcoin, Ethereum, and Ripple. This disparity can make using EAs (Expert Advisors) purchased online almost impossible. Traders may see some profits at first but later start losing, not because the EA is unprofitable, but because it was created on a different broker with different price feeds.
Creating Hundreds of Strategies for Cryptocurrency Trading
Once enough history data is collected, the next step is creating hundreds of strategies. This is possible with professional strategy builders like EA Studio and FSB Pro. These tools feature powerful functions like the Generator and Reactor, which create strategies using the history data and predefined conditions. With just one click, you can export a strategy as an EA without needing to hire developers.
Testing and Diversifying Strategies
By having hundreds of cryptocurrency strategies, we can test them on demo accounts and only trade live with the top performers. The goal is to avoid relying on just one EA for Bitcoin, Ethereum, or Ripple. Diversifying strategies allows us to mitigate risk; if one strategy starts losing, we can replace it with others that are still profitable.
Selecting Cryptocurrencies for Algorithmic Trading
In the course, we focus on Bitcoin, Ethereum, and Ripple for a few reasons. This diversification spreads the risk across three different cryptocurrencies. We also look for other cryptocurrencies with significant volatility, not just Bitcoin.
Ethereum offers moderate volatility, an affordable price, and a medium spread, making it an ideal option. Ripple, currently inexpensive with a small spread, is another viable choice. This mix covers different risk levels and opportunities for algorithmic trading.
Course Overview and Conclusion
In the course, you’ll learn the entire process—from collecting data to testing strategies. We chose Bitcoin, Ethereum, and Ripple because of their volatility and potential for algorithmic trading. Cryptocurrency is a perfect asset for algorithmic trading, and our course will show you why.
The course is available here: Cryptocurrency Algorithmic Trading – The Revolution. We named it this way because we demonstrate how cryptocurrency’s volatility makes it an ideal candidate for algorithmic trading.
