Last Updated on 10 February, 2024 by Rejaul Karim
Everyone wants a better way of doing things, and traders are not an exception in any way. They, too, want a better way to ply their trade. Having been used to the traditional way of trading and now encountering algo trading, traders want to know if algo trading is better.
Yes, algo trading is better because it eliminates human errors, which is a common problem in traditional discretionary trading. In addition to that, algo trading affords you better control of statistics as you will know your trading edge and the odds of success for the strategy you are using.
No matter how we look at it, we will always choose algo trading above discretionary trading, but let’s find out why. In this post, you will learn the following:
- What algo trading is
- Why it works
- Why we think it is better than discretionary trading
- What you should know about algo trading
- The tips that can make algo trading work for you
What is algo trading?
Normally known as algorithmic trading, this is a trading approach where the trader uses a computer program (a trading algorithm) to execute trades. A trading algorithm is a set of commands, modeled after a specific strategy, which tells the computer when to enter a trade, when to exit, and the trade size.
That is to say that the code for the algorithm defines what a trade setup is and the criteria for it. So, the algorithm scans the market for conditions that meet a trade setup, and when it sees one, it places a trade according to the instruction for the trade size. When conditions for exit are met, it closes the trade.
Algo trading may seem easy, but it is not as easy as might think. Setting up and maintaining the algo trading system is quite difficult. You will need to do a lot of market research to find some trading edges, code algorithms to take advantage of the trading edges, backtest the strategies, test them for robustness, and launch them to trade. After setting up the trading algos, you still have to keep checking the system from time to time to be sure that everything is running fine.
In spite of the hard work involved, algo trading is much better than discretionary trading in many respects because, with algo trading, you can trade an almost limitless amount of strategies at once. At the Robust Trader, we trade over 100 strategies ourselves across different markets and timeframes to reduce our trading risk through diversification.
Why does algo trading work?
Algo trading works very well because the system is built around an identifiable edge in the market. In creating an algo trading system, the trader must have taken time to find an edge in the market, which he or she tries to exploit. The trader does this by creating a strategy from the trading edge by specifying the criteria for a trade entry and exit.
With these criteria, the trader writes a computer code for a trading algorithm, telling the computer what a trade setup is and how to trade when it sees one — including the trade size. The code also tells the computer the conditions that must be met for closing the trade.
When the trader is done with the coding, he/she tests it on the historical price action — probably of up to 10 years. This is known as backtesting; it shows the probable odds of success for that strategy. How the algo performs in backtesting would determine whether the trader tests it for robustness or tweak it a little for better performance. A strategy that shows a high probability of success in both backtesting and robustness testing will be good to try out in a real account.
In essence, algo trading works because you already know that it has a high probability of success and you allow it to execute trades for you without intervention. However, you still need to monitor the system from time to time to be sure that it is still working fine. Creating an algo trading system is quite difficult, but you can learn it from a good algorithmic trading course.
Why is algo trading better than discretionary trading?
To us, algo trading is much better than the traditional discretionary method of trading. Algo trading offers a lot of benefits such as the following:
- Algos can trade all the time: The computer never sleeps; algos can trade at all times, as long as the market is open. This offers a great advantage over discretionary methods, which depends on when the trader is available to trade — so the trader can miss many trades because he/she cannot possibly monitor the market all the time. With a functional algo trading system, there is no missing any qualified trade setup.
- Trades are executed very fast: Algo trading offers a good speed in executing trades, as the algorithms can analyze a variety of parameters and technical indicators in a split second and execute the trade immediately. This speed is very important in fast-moving markets or intraday trading styles where any delay can lead to poor entry price and poor trade outcome.
- Algos mean more accuracy and fewer mistakes: Since there is minimum human intervention in algo trading, there is less chance of dangerous trading mistakes, like entering abnormally large position sizes or entering trades unintentionally. With discretionary trading, these mistakes are very common, but unless the algorithm has a bug, it executes orders as instructed with maximum accuracy.
- The impact of human emotions is minimized: The most important benefit of algo trading is that it reduces the impact your trading emotions, such as fear, greed, and hope, can have on the trading process since the entire process is automated. You have already provided the computer the instructions to trade with, and that is what it’s going to do, provided you don’t intervene.
- The ability to backtest helps you to ascertain the performance: When developing a trading algorithm, you have to backtest it using historical price and volume data to know if the strategy can be profitable. Also, you get to know the odds of the trade setups identified by the strategy. With this, you can plan your capital allocation better.
- It makes diversification easy: Since algo trading uses algorithms and computers, multiple trades can be executed at the same time using multiple strategies across multiple markets in different timeframes. This would never be possible if you are manually analyzing each market and executing the trades. Trading algorithms can easily scan a range of markets, assets, and instruments and place orders simultaneously. In essence, algos makes it possible for you to easily diversify across several markets and strategies.
- Algo trading improves market liquidity: Algo trading makes it possible for large volumes of shares to be bought and sold within a fraction of a second. This increases the overall volume and liquidity of the market, making the market better for everyone.
- It ensures trading consistency: In discretionary trading, the most difficult aspect is to plan the trade and trade the plan. Even after creating wonderful strategies and a good trading plan, adhering to the plans can be quite difficult due to sudden volatility changes in the markets. Algo trading deals with these issues by keeping to the instructions coded into the trading algorithms. This helps the traders remain consistent and disciplined in spite of the ups and downs so that the rationality of the strategy remains upheld and does not get derailed due to the effect of impulses like fear and greed.
- The asset selection process is automated: Algo trading automates the entire process of asset selection, order execution, and entry and exit, so your trading is systematic. With algos, trading is just a step-by-step execution of instructions, so everything is objective and streamlined.
Related reading: How Good Is Algo Trading?
Related reading: How Hard Is Algo Trading?
What you should know about algo trading
Despite all the benefits that algo trading offers, it comes with some drawbacks, which you should be aware of. These are some of the drawbacks:
- Algo trading is technology-dependent: One major issue with algo trading is that it depends so much on technology, which could present a problem if technology fails. For instance, when your algos make trade orders on your computer, it has to be transmitted to the broker via the trading platform. So, if the internet connection is lost, the order will not be sent for execution. In this case, you miss an opportunity to make money, but the order could be for a trade exit (instead of entry), which means that you might lose money. Furthermore, algos from different traders may act the same way in certain market conditions, leading to huge flash crashes of the entire market.
- There is no human control: Algo trading is completely automated, which removes the ability of the trader to intervene on a trade by trade basis. While this may be beneficial in some ways, it could be a problem when the trader knows the market condition is not favorable for the strategy the algo is using.
- It requires constant monitoring: Thinking that algo trading is just to launch a preset program on your computer and go your way is simply idealistic. After your algo system is up and running, you still have to monitor the system to look for potential mechanical issues like connectivity, power losses, and so on. Even though the strategies are integrated into the servers, they need to be monitored to ensure successful execution to avoid missing orders, duplicate orders, or wrong orders. But it doesn’t mean that you have to be with your system all the time; you can check things once in a few hours with your smartphone.
- You need to have programming skills: Most likely, you will want to develop your trading algorithms yourself. In this case, you will need to have some programming skills. But you don’t go about learning all programming languages; just focus on the coding language of the trading platform you are using to trade.
- There is a risk of over-optimization: One peculiar issue with algo trading is that the strategies may not turn out to be successful and effective during live trading despite doing well in backtesting. This is called over-optimization, and it results from modifying the strategies a lot to fit the historical price action, which will definitely be different from the live market.
- It requires a huge expenditure on resources: While algo trading may help in the reduction of the transaction costs, it requires a lot of expenditure to start. You will need to be equipped with high-end resources, get access to a private server that will host your system, and must develop the algorithms, which cost money. Moreover, there is also the cost of data feeds used in developing intraday strategies.
- Not all strategies can be automated: While some excellent strategies can easily be converted to trading algos, not all strategies can be automated and converted into an algorithm. So, if you only want automated trading, you won’t have the opportunity to use those strategies.
- Algorithms have a short life span: Trading algos don’t work in one market forever. In fact, about 98% of the algorithms have a very short lifespan. You will frequently have to fix or reinvent your trading algos, which means you have to keep checking on them to know when they need to be fixed.
- Algorithms can’t understand irrational markets: Since algorithms are simply automated instructions, they cannot understand when the market situation has changed. Algo trading can lose a lot of money when the market is acting irrationally.
Tips to make algorithmic trading work for you
Here are some of the tips that you can use to make algo trading better:
- The simpler, the better: While you can trade multiple markets with your algo system, it’s better to start with one market — probably the stock market. When you are comfortably making money in one market, you can then try other markets.
- Know how to make decisions: Algo trading requires you to make some important decisions along the line — what market to trade, selecting a watch list, choosing a good spreadsheet template, and many others. So, you need to learn how to make rational decisions without overthinking the unimportant details.
- Have a plan for managing risk: Naturally, trading is very risky, so you should know how to manage trading risks, especially as regards algo trading. The first thing is to know how much of your account balance to risk per trade — experienced traders often suggest 1% of your account balance. With this, you can get the dollar value and use it to calculate your position size if you know your stop loss estimate. Another aspect of risk to consider is your circuit breaker. What we mean here is the maximum daily loss limit. You won’t like to lose all your funds in one bad day, so you should have a limit for the day where your algo system stops to trade for that day. Most traders set their daily loss limit at 3% of the account balance or 3 consecutive losses when risking 1% per trade.
- Record your trades: You want to have a spreadsheet where your system can automatically record your trades and their outcomes. Keeping a record of your trades is very important. With good records, you can easily look back and see how your system is performing so that you can address any setbacks in time.
What benefits does algo trading offer over traditional methods?
Algo trading provides advantages such as 24/7 trading capability, fast trade execution, increased accuracy with minimal mistakes, reduced impact of emotions, effective backtesting for performance assessment, ease of diversification across markets and strategies, improved market liquidity, and systematic trading through automated asset selection and execution.
How does algo trading handle the risk of technology failures?
Algo trading is technology-dependent, and the risk of technology failures is acknowledged. Traders need a stable internet connection to ensure orders are transmitted to brokers. Constant monitoring is advised to address potential issues like connectivity and power losses, even though strategies are integrated into servers. Traders can check their systems periodically using smartphones.
How long do trading algorithms typically last, and why?
Trading algorithms often have a relatively short lifespan, with around 98% experiencing this. Algorithms may need fixing or reinventing due to changes in market conditions. Traders need to keep checking and assessing algorithms to determine when adjustments or reinvention is necessary for continued effectiveness.