Last Updated on 14 October, 2021 by Samuelsson
Most new traders tend to start with the traditional form of trading wherein they analyze the market by themselves, identify potential trading opportunities, and manually place their trades. However, many would want to know how good algo trading is before they decide to give it a try.
Yes, algo trading is good because it reduces the chances of human errors that are commonly seen in discretionary trading. Moreover, with algo trading, you also have better control of statistics since your trading edge and the odds even before launching your algo trading system.
In this post, you will learn the following:
- What algo trading means
- How it works
- Why it is the best way to trade in today’s market
- Its merits and demerits
- Algorithmic trading tips that can help you
What algo trading means
Algo trading (algorithmic trading) is an automated form of trading where a computer program executes trades on behalf of the trader. This program, often called a trading script or algorithm, runs on the trader’s computer or is hosted on a remote server and execute trades in accordance with the strategy it models. Algo trading is a hands-off approach to trading, as the trader is not directly involved in identifying a trade setup and executing the trade.
So, algo trading is unlike discretionary trading where the trader has to analyze the market, place orders, and close them by himself or herself. Instead, it only requires the trader to set up trading algorithms on the computer; the algorithms then scan the markets for trade setups and execute them in line with the instructions regarding position size and others.
On the surface, algo trading may seem easy, but it is not. It can be difficult to set up and maintain. You will need to do a lot of market research to find some trading edges, which you have to convert into tradable strategies, and then code the algorithms to take advantage of the trading edges. When you are done with the coding aspect, you will have to backtest the strategies and test them for robustness before launching them to trade for you. After launching the system, you still have to keep checking it from time to time to be sure that the algos are working as they should.
Despite the difficulty with creating an algorithm, we think algorithmic trading is much better than any other form of trading in many respects. Since the computer is doing the trading, algo traders can trade an almost limitless amount of strategies at once. We, at the Robust Trader, trade over 100 strategies ourselves in many different markets, and we trade many timeframes, from day trading to longer-term position trading, since algorithmic trading is not limited to any trading style.
The most difficult part of algo trading is finding the right trading ideas with a proven edge to develop into trading algorithms. This requires you to learn how to code in the language of the trading platform they are using to trade. The trading ideas to develop can come from your market research. You may have to modify the ideas you find online and test them to see how well they perform. If developing your own trading algorithms seems hard, you can buy one from a trading bot vendor; just make sure you are getting it from the right source and test it for robustness before using it to trade.
How algo trading works
As you can see from our discussion so far, algo trading is just about the computer implementing your trading strategies for you. For this to happen, you have to code a trading algorithm, instructing the computer on what a qualifying trade setup is, the position size, when to enter a trade (session’s open or close), the conditions to close a trade in profit, and when to close a losing trade. With these instructions, the computer algorithm monitors the markets where they are loaded, and when they identify the trade setups, they make the necessary trades.
In essence, for algo trading to work, you must have coded an algorithm that identifies a certain market condition based on the strategy you are using. But you will have to backtest the strategy after converting it to an algorithm to be sure it has some merits. The backtesting will show you how the strategy performs in historical price action, so you have an idea of its profitability. But then, you have to also test the strategy for robustness to be sure that its performance on the historical price action is not out of too much curve-fitting, which can impair its performance in real-time market action.
To put it all together, algo trading works by providing your computer or a remote server with some trading instructions with which it searches for matching trade setups and executes the trades on your behalf. So, it removes your input on a trade-by-trade basis, minimizing the effects of your trading emotions, such as fear, greed, and others, on the execution of your trades.
If you have a profitable strategy, your trading algorithms will precisely execute them and make you money without your emotions standing in the way. But to be sure that your algo system is profitable, it has to be tested both in historical and real-time market action to rule out bugs and ascertain trading performance.
The easiest way to learn algo trading is to enroll in an algo trading course. If you can’t go through the process of developing your own trading algo system, you may buy from a trustworthy trading bot vendor. However, you have to be careful since there are many false trading vendors out there. Even when everything is set up and running smoothly, you will need to be monitoring your algo system every now and then.
Why algo trading is the best way to trade in today’s market
The truth is that the financial markets have become more efficient in recent times, so it is becoming increasingly more difficult to trade discretionarily. It is no longer like in those days when you could trade a strategy as simple as moving average crossovers and consistently make easy money.
With the markets getting so efficient, trading edges are getting so few that you probably need something more accurate than your ability to spot patterns in the market, which is why algo trading is the right solution because the trading edge is pretested and not just an assumption. By creating a trading strategy that is tested on historical data, you may be able to uncover market behaviors, or edges, that you cannot identify by observing the market patterns visually.
However, it doesn’t mean that it’s only complex strategies that work in algorithmic trading. In fact, it is more of the opposite — the things that work the best tend to be the simplest. So, the simpler your trading strategy, the better it is to code an algorithm that can perfectly execute it with much more accuracy and speed than you will ever have.
The merits and demerits of algo trading
Algo trading comes with a lot of merits, but there are also some demerits too. Let’s take a look at some of them.
Here are some of the merits of algo trading:
- Known probability of the trade outcome: Algo trading systems are backtested using historical price data, so you know the odds of your trades before setting up the system to trade in the real-time market.
- Fast execution: In algo trading, computer algorithms scan the market for trade setups and make the trades a lot faster than a trader can manually execute the trades even if he/she identifies the setups. Speedy execution ensures proper entry and reduces slippages.
- No execution mistakes: Algo trading ensures accuracy in execution and prevents the possibility of mistakes, such as placing a wrong order size or entering a trade when there is no setup.
- Round-the-clock trading: Computer algorithms can trade all the time, as long as the market is open and there are no power or connectivity issues.
- Reduced impact of your trading emotions: With the computer executing trades for you, your trading emotions, such as greed and fear, won’t affect how the trades are executed.
- Easy to diversify: You can set up multiple algorithms to trade different strategies in different markets and across different timeframes. This way, you will be reducing your risk exposure in one strategy or market.
- A fully automated process: Algo trading systems can be fully automated — from selecting the stocks to trade to placing orders and closing them. It all depends on the instructions in the algorithms.
- Trading consistency: Algos are consistent in their execution, irrespective of the market situation. This can be good or bad, depending on the situation.
The demerits of algo trading include the following:
- Too much reliance on tech: Everything about algo trading depends on technology — computers, high-speed internet connection, and all the rest. If there is a power failure or a loss of internet connection, your entire algo system will be in trouble.
- Lack of human control: Once the system is set up, you don’t intervene on a trade-by-trade basis even when you think a particular trade would end in a loss due to the prevailing market condition. The algorithms execute with consistency and can’t identify irrational markets.
- The need for coding skills: You will need to have coding skills to be able to convert your trading strategies to algorithms.
- Risk of over-optimization: There is a high risk of over-optimization in the backtesting, which will make the system to flop in the real-time market.
- Not suitable for every strategy: It is not every trading strategy that can be coded into an algorithm. Such strategies have to be traded manually.
- Quite expensive: Setting up an algorithmic trading system can be expensive even if you write the algorithms yourself. You will need a computer with high processing speed, a fast internet connection, a remote server, and data — all these cost money.
Algo trading tips that can help you
There are some algo trading tips that can help you in your journey to becoming an algo trader. These are some of them:
- Start small and keep things simple: With the algo trading method, you can trade multiple markets, but it’s better to start with one market. It may be the stock market or another market but start with one. When you are comfortable in one market, you can then try other markets.
- Be good in decision-making: In algo trading, you will be making important decisions that won’t just be affecting one trade but all the trades your trading algorithm makes. From what market to trade to the strategies to use, you need to decide without overthinking the unimportant details.
- Establish a risk management plan: Trading is a very risky business, so you should have a plan for managing risk, even though your algo trading system is automated. First, you have to know how much of your account balance you can comfortably risk per trade — about 1% of your account balance is fine as a new trader. The next thing is to calculate the dollar value and use it to calculate your position size if you know your stop loss estimate. You should also have a maximum daily loss limit, which, when your algo system gets to, it would stop trading for the day. You surely won’t want to lose all your funds in one bad day, so a circuit breaker is a good element of risk management. Traders commonly set their daily loss limit at 3% of the account balance or 3 consecutive losses if they are risking 1% per trade.
- Create multiple strategies: One strategy will probably not be enough for you. While you have your first strategy running, create more strategies and algorithms so that you have different options. You can have different algorithm categories.
- Diversify across markets and timeframes: Another way to reduce risk in algo trading is to run different strategies in different markets and timeframes simultaneously. You should do this only when you have gotten enough experience in algo trading so that you don’t overwhelm yourself in the early stages.
- Record your trades: It is important to have a spreadsheet where your system can automatically record all the trades it has made and their outcomes. Keeping a record of your trades makes it easy for you to look back and see how your system is performing so that you can address any setbacks in time.