Last Updated on 13 July, 2021 by Samuelsson
A lot of people would like to have their computer execute their trades for them but may find algorithmic trading a bit confusing. Many new traders find algorithmic trading hard to grasp and often wonder whether algorithmic traders actually make money.
Yes, algorithmic traders do make money, but most of them fail to do so. Trading is very hard, whether it is discretionary or algorithmic, and you need to put in a lot of hours to master the skills and stand a chance of making money. You should know that trading is not as easy as it is presented in mainstream media sites.
In this post, we will cover the following:
- Who algorithmic traders are and what they do
- How they make money
- How much they make on average
- Why algorithmic traders may make more money than discretionary traders
Who are algorithmic traders and what do they do?
As you already know, algorithmic traders, or algo traders, are traders who have automated their trading analysis and execution processes. They achieve this by running a script on their computers that execute their trades according to their written rules. Being a hands-off approach to trading, algorithmic trading affords the trader enough free time to do other things.
However, algo trading still involves a lot of work, except that the work is no longer about analyzing the markets, placing orders, and closing them. Instead, algo traders’ work is in the areas of market research, finding some trading edges, writing scripts to take advantage of the trading edges, backtesting the strategies, checking for their robustness, and setting them up to trade. Even after the trading algos are set up, the trader will have to keep checking the system from time to time to be sure that everything is running fine.
Nevertheless, algorithmic trading offers a lot of freedom compared to discretionary trading. The computer program takes care of the market analysis, scanning the market for trade setups that meet the rules written in their scripts, and executes trades when qualifying trade setups occur. With the algos running, all the trader does is periodically check the system to be sure it runs smoothly.
So, we think algorithmic trading is much better than any other form of trading in many respects. For instance, algorithmic traders can trade an almost limitless amount of strategies at once. At the Robust Trader, we trade over 100 strategies ourselves in many different markets since it is beneficial to diversify into many different strategies in different markets. Those strategies range from day trading to longer-term position trading, so algorithmic trading is not limited to any trading style.
The most difficult part of algo trading is researching to find trading edges, developing new trading strategies from the edges, and writing the scripts. Successful algo traders learn how to code in the language of the trading platform they are using to trade and tend to love market research a lot. Trading ideas can come from anywhere — fellow traders, things you read online, spur of the moment, etc. It is your job to develop this idea and code it, after which you backtest it to know if it has any merit and, then, test its robustness before bringing it to live trading.
Intending algorithmic traders who don’t want to go through the process of developing their own trading systems can buy good trading systems from the right sources.
How do algorithmic traders make money?
With the algorithmic trading approach, the one thing a trader needs to get right to make money is developing a robust trading strategy. To determine when the computer should enter and exit a trade, the trader must write a set of commands based on the rules that have shown to have an edge in the market. What we mean here is that the rules actually have been objectively proven to have worked well in the past.
This is the basic aspect of creating a reliable trading strategy. So, it might appear strange that anybody would trade strategies that have not been proven to generate profits in the past or even that have yielded losses in the past. But it is mainly a problem with some new traders, who assume that they may make out what works, and what doesn’t, using their common sense and intuition without doing the necessary research to find a proven edge. Poor trading strategies are the one biggest reason why as many as 95% of all traders lose money!
That is why experienced algorithmic traders make use of a rigorous method to ascertain what works and what doesn’t when creating their trading systems. All in all, algorithmic traders make money as a result of the following:
- Research: Algorithmic traders take their time to study the various markets, looking for trading edges. While some may do a random search, it is easier to have some trading ideas to research. One place traders find ideas to develop and work on is financial journals where academics publish their trading theories.
- Developing the strategy: When they find promising ideas, algo traders would modify them and create potential trading strategies by specifying the criteria for trade entry and exit, as well as the stop loss if necessary. These traders use the rules to write an executable script for the strategies, which gives the computer the commands on what to do.
- Backtesting: With the trading scripts written, the next thing is to test the strategies on the historical price action to see how well the strategies would have performed if they were traded at those periods in the past. Many trading platforms have advanced strategy tester for this purpose. The result of the backtesting would determine what next to do — discard the strategy, modify it, or move to the next phase.
- Forward testing: Here, algo traders test the strategies that performed well on the historical price action in a real-time market environment. Forward testing will tell the trader whether the strategy can perform well in a live market. The only problem with forward testing is that it can take a lot of time to get a reasonable sample size for reliable analysis, so a walk forward may be an alternative.
- Implementing the system: Strategies that are proven to perform well are implemented to execute trades, but they have to be monitored from time to time to be sure that they are performing as expected.
Now that we have seen what algorithmic traders do to develop profitable trading systems that make them money, let’s take a look at some of the most popular trading strategy categories. They include the following:
- Mean reversion
- Trend following
- Biased strategies
This strategy works on the theory that the price swings above and below its long-term mean and is likely to revert whenever it moves significantly away from the mean. When the price moves significantly above the mean, a short trade is generated, and when it moves significantly below the mean, a long trade is generated. There are different methods for identifying a significant move away from the mean, and they include the RSI2, Moving Average, Bollinger Bands, and others.
Also known as the momentum strategy, a trend-following strategy tries to ride the impulse price swings along the direction of the trend. Traders use different criteria to determine what constitutes a trade and code their scripts accordingly.
These are strategies that are specific to individual markets and they depend on the market’s tendency at that time.
How much do algorithmic traders make on average?
How much algorithmic traders make varies greatly. It obviously depends on a trader’s strategies and capital allocation. Those with superior strategies will make more money than those with mediocre strategies. Likewise, all things being equal, those who trade with bigger capital would make more money than those with small capital.
However, for most algo traders, the profit margin tends to be around 1-3 times the size of the trader’s acceptable drawdown. What this means is that if a trader uses a 30% maximum drawdown, with the right strategies, he or she is expected to be making about 30-90% in returns. This return is quite impressive considering that most discretionary traders don’t make half of that if at all they make money.
Why algorithmic traders can make more money than discretionary traders
There are many reasons why we believe that algorithmic trading is more profitable than discretionary trading and the better choice for you if you are willing to give it a try. These are some of them:
You know the odds of your trades
In algorithmic trading, everything is backtested and even forward-tested so you know the odds of your trading edge and can plan your capital allocation accordingly. As an algo trader, you don’t just guess your trades as does the average discretionary trader, who usually relies on guesses when considering how certain patterns should perform.
Rather, you rely on historical backtests to evaluate the profitability of the trading edge and can go ahead to maximize the chances that they will continue to work in a real-time market environment by forward-testing it. Based on this, it doesn’t come as a surprise that algorithmic traders make more money than discretionary traders if at all they do.
The computer never sleeps
Algorithmic trading systems run as long as the markets are open, which is of great advantage, especially when trading some markets like gold where there are multiple sessions around the world. This enables you to make more trades and increase the chances of winning.
It is even possible to have strategies that trade different sessions in the same market, to take advantage of how the market behavior changes throughout the session. This concept works for global commodities (such as gold), which, depending on what part of the world is currently trading it actively, may behave very differently.
Automated execution for all strategies
With the discretionary approach, trading multiple trading styles — scalping, day trading, swing trading, and position trading — at the same time is nearly impossible, but with computer programs taking the trades, it is now very much possible. Moreover, apart from being a convenient solution, it comes with quite some great advantages. Perhaps, the biggest advantage is that you avoid many of the mistakes that are common in discretionary trading, such as the difficulty in handling several price charts at the same time, which can result in erroneous orders (big finger effect) or poor trade management.
Definitely, there will be hiccups in algo trading, and there will be instances when your computer, your internet connection, or the broker messes things up a bit. But with some monitoring, this will just be a minor concern because most trading algos generally run smoothly. You can stay for six months without any significant hitch.
Reduced effect of trading emotions
The emotional and psychological stress associated with trading is one of the most challenging aspects of any trading style. Trading emotions can seriously affect discretionary trading. It is not uncommon to see discretionary traders struggle with placing the next trade or adhering to their set rules when they have a significant drawdown that is still below their preset maximum levels.
With the computer making the trades, algorithmic traders aren’t involved in the execution of their trading strategies, so their trading emotions have less effect on their trading outcome. However, algorithmic trading, by no means, relieves you of all emotional pressures and hardships — it only makes things a lot easier!
Easy to diversify across strategies, markets, and timeframes
Algorithmic trading makes it easy to diversify and, thus, reduce risk. With the computer executing the orders for you, you can expand your trading into more markets, timeframes, and strategies, which make for better risk management.
For example, it is possible to have your algo system trading gold, crude oil, market indexes, or stocks, all at the same time. So, if one or two of these markets behave strangely at one time, the others may be in profit and make up for those losses, which is why algo traders try to learn different algorithmic trading strategies.
At the Robust Trader, we trade as many as 100 strategies across different markets at the same time, so each strategy only risks a small portion of the capital, which makes it much safer for us.