Robot with blue eyes.

At the most basic level, algorithmic trading strategies use computer code to trade assets in an automated manner. Algorithmic trading strategies are often called automatic trading strategies, and, in retail markets, are generally referred to as trading bots.

In this guide, you will discover four popular algorithmic trading strategies you can use to trade digital assets.

Why Trade Using Bots?

Algorithmic trading comes with several advantages over “human trading.”

First of all, trading bots continue to run until stopped. This is excellent in the digital asset markets, which never close, so the bots can trade 24/7/365.

A second advantage is the speed of algorithmic trading. Trading bots can open and close trades faster than the blink of an eye.

Thirdly, and perhaps most importantly, algorithms trade without emotions. No greed, no fear, no elation or depression. They simply process trades according to the instructions they’ve been programmed with.

All of these things help algorithms maintain profitability, so which algorithmic trading strategies are best for trading digital currencies?

Algorithmic Trend Following Systems

If you are experienced with technical analysis from other assets, you likely already recognize trend following systems. Any trend following systems used for equities, commodities, or forex can also be used for digital currencies.

Trend following systems work on the premise that markets have momentum that you can take advantage of as a trader. There are a number of indicators used to identify trending markets and their direction.

The most common and easiest to understand are Moving Average Crossovers. This is when a slower moving average, such as the 20-day, crosses over a slower moving average, such as the 50-day. When the faster-moving average crosses above the slower moving average, it is an indication of increasing buying momentum and a bullish signal. A cross below the slower moving average is bearish.

Mean Reversion

While markets can and do trend strongly at times, these strong trends are outliers, and a move back to the mean or average levels almost always follows.

In other words, if you see that price has made an extremely large move higher, or lower, there’s a good chance that it will be followed by a move back to normal levels soon.

Mean reversion strategies use historical averages and can be set to use a longer or shorter historical average depending on the trader’s expectations or needs.

Standard Deviation Reversion

The idea of standard deviation comes from statistics, and it is simply an average movement away from the mean.

In trading, two standard deviations are most frequently used, and the Bollinger Bands indicator is the most popular tool for trading based on standard deviations. Bollinger Bands are two lines that enclose price action, one above and one below, with each line being two standard deviations from the mean.

Whenever price reaches one of these bands, it is considered overbought or oversold and is then expected to revert back to the mean.

Algorithmic Arbitrage Trades

Arbitrage has been one of the most popular and most successful algorithmic trading opportunities. In arbitrage trading, you take advantage of mispricing across exchanges to collect risk-free profits.

With hundreds of exchanges, it is almost guaranteed that prices for the same asset will differ from one exchange to the next, making it simple enough to buy the asset at a lower price at one exchange, and then sell it immediately for a profit at another exchange.

Of course, to take advantage of these price differences, you need to be quick since they might only exist for a few seconds. And that’s where algorithm trading shines.

In Consideration of Open-Source Bots

If you are just getting started with coding a bot for algorithmic trading, you should know there are quite a few open-source trading bots already available to use as a codebase. A few of the most popular and well-known free, open-source bots include Gekko, Zenbot, and Freqtrade.

If you’re familiar with MetaTrader and its MQL4/MQL5 programming languages, you can even code algorithms for trading there. If you’re just getting started, help can be found at the MQL4 Community or at the MQL5 Community.

In Conclusion

It’s true that algorithmic trading in the digital asset markets is becoming more competitive, but there are still opportunities available, especially with technical indicators and reversion strategies. Arbitrage has been mostly taken over by high-frequency traders using powerful servers and latency-free connections.

The truth is if you have a strategy that works, there’s a very good chance, it can be coded into an algorithm to trade automatically. Remember though that while algorithm trading is automatic, it still needs to be monitored. Market conditions can change, and the algorithm will continue trading, even if every trade is a loss-making transaction.

That said, as long as you’re diligent, an algorithmic trading strategy can be an excellent way to approach the cryptoasset markets.

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