Last Updated on 14 October, 2021 by Samuelsson

Trading is moving from the traditional manual trading methods to automated algorithm-based methods. Many discretionary traders are making the shift to a more automated way of trading, and you may be wondering if you can make money from automated trading or algorithmic trading.

Yes, you can make money with automated trading (also known as algorithmic trading), but like in any other form of trading, most traders fail to make money with it. Trading is hard, so you need to put in a lot of hours to have a chance at making money. The way trading is presented in mainstream media sites is misleading.

In this post, you will get to learn the following:

  • What automated trading is
  • How it works
  • Why it can make you money
  • The common strategies used in automated trading
  • Tips for making money with automated trading

What is automated (algorithmic) trading?

Automated trading, often used synonymously with algorithmic trading, is a method that uses a computer program to create buy and sell orders and automatically submits the orders to the market via the brokerage platform. The orders are generated in accordance with the predefined set of rules that model a specific trading strategy, which may be based on technical analysis, advanced statistical and mathematical computations, or fundamental data reports from electronic sources. In other words, computer algorithms search the markets for trade setups or use data from other sources to determine when it is time to enter a trade.

Once the algorithms are set up, they execute trades and manages them for you following the instructions in the codes, which tell the computer the conditions that must be met to enter a trade, the right position size, the direction to trade, and the conditions that must be met to close the trade.

When coding the trading algos, the trader tries to follow a specific strategy that has an edge in the market. It can be a technical analysis strategy, a quantitative trading method, or a fundamental analysis report (news feeds). Whatever the method of identifying a trading opportunity, the main thing is that the entire process of spotting the opportunity, executing it, and managing the trade is automated. Thus, even though both automated trading and algorithmic trading are used interchangeably, automated trading to be an all-encompassing term, while algorithmic trading tends to refer to a technical analysis-based automated system.

While there can different trading strategies with varying degrees of complexity, the simplest strategies tend to work the best. So, a strategy may be as simple as buy on the open of the next trading session following a 3-day low and sell on the open of the next session following a 3-day high. Such a simple strategy is easy to code, unlike quantitative methods that require high-level mathematical knowledge. Whether simple or complex, the strategy is what the computer program implements on behalf of the trader, so if the strategy is a profitable one, the system will be profitable, but if it’s not, the system won’t be.

It is possible to run multiple trading algorithms based on different strategies at the same time while trading in many different markets across multiple timeframes. This way, the trader diversifies risks across different strategies, markets, and timeframes.

How does automated trading work?

Automated trading works by the means of trading algorithms that gives your computer a trade instruction in the form of a trading script, which it implements automatically without your intervention. The algorithms monitor the markets or whatever data they are coded to monitor and execute the instructions when the right conditions are met. The trade instructions are based on any trading strategy the trader wishes to use, and of course, it must be a strategy with some proven odds of success.

The trader runs the algorithm on your computer, letting it monitor the markets for conditions that match the trading instructions. When the required conditions are met, the algorithm executes the trade, sending the preset order size to the market. Anytime the conditions for trade exit are met, the program sends an order to close the trade.

Before a trader launches an automated trading system, he or she will need to backtest the strategy to be sure it’s profitable on the historical data and then test it for robustness to know if the strategy can perform as well in a real-market environment. It is only a strategy that is robust enough that should be used in normal live trading.

Enrolling in an algo trading course will help you learn how to create an automated trading system. If you think that you can’t go through the process of developing your trading algorithm, you may buy from a trustworthy trading bot vendor. You have to be very vigilant, as there are many false trading vendors out there.

Putting it all together, in automated trading, a computer algorithm does your trading for you. But it has to be backtested and forward-tested to confirm its profitability and detect any bugs in the codes that might make the trading system to malfunction. After launching your automated trading system, you have to monitor the system from time to time to be sure that everything is working fine.

Why automated trading can make you money

You can make more money when you automate your trading strategies, and there are many reasons why it is that way. These are some of them:

1. You know that your strategy has a high probability of success

In the process of automating your trading strategy, you backtest and even forward-test your trading algorithm after creating it. Thus, you don’t only know that your strategy is profitable but also know the odds of your trades, so you know how to plan your capital allocation.

Rather than guess your trades as an average traditional trader does when choosing a pattern to trade, you backtest your automated trading system using historical market data to evaluate the profitability of the trading edge, and you can go ahead to test it for robustness in real-time market. Hence, you already know that your algorithmic trading system has a positive expectancy before setting it up to trade for you.

2. The computer trades as long as the market is open

When you set up your algorithmic trading systems, they scan the markets and make trades, as long as the markets are open. This is of great advantage when trading some markets like gold where there are multiple sessions around the world. So you get to make more trades and increase the chances of winning.

You can even have different strategies that trade different sessions in the same market so as to take advantage of how the market behavior changes throughout the session. This approach is great for global commodities, such as gold, which may behave differently depending on what part of the world where it is currently trading actively.

3. There is trading consistency

We know that in traditional trading, even after creating wonderful strategies and a good trading plan, adhering to the plans can be quite difficult due to sudden changes in the markets. Each time you struggle to plan your trades and trade the plan. But with algorithmic trading, you code the instructions which the trading algorithms execute with accuracy and consistency.

Thus, your trading remains consistent and disciplined in spite of the ups and downs in the markets. This consistency helps to ensure that your trading edge is preserved.

4. Your trading emotions won’t have much effect on your trade execution

There is bound to be some emotional stress in trading, which is one of the most challenging aspects of any trading style, including automated trading. Your emotions can seriously affect your trading outcome when you are using the traditional manual method of execution. For example, if you have a streak of losses, you may struggle with placing the next trade or adhering to your trade management rules.

However, with algorithmic trading, the effects of your emotions on your trading outcome are reduced. With the computer making the trades, you aren’t involved in the execution of your trading strategies, so your trading emotions have less effect on the outcome of your trades. But note that algorithmic trading, by no means, relieves you of all emotional pressures — you will still have the emotions if you keep checking your P/L section every day.

5. Automating your strategies reduces trading errors

Automated trading doesn’t just make trading convenient, it helps you to avoid many of the mistakes that are common in manual trading, such as the big finger effect (where you enter trades unknowingly), extra zero effect (where you mistakenly enter a far bigger position size), or poor trade management decision like taking profit early.

While there will be some glitches in algorithmic trading — for example, there will be instances when your computer, your internet connection, or the broker messes things up a bit — automated trading reduces the chances of trading errors, and you can stay for six months without any significant issue.

6. It is easy to diversify and reduce risk

With the discretionary approach, it is almost impossible to trade multiple trading styles — scalping, day trading, swing trading, and position trading — at the same time. However, with computer programs executing the trades, you can trade across multiple timeframes and different markets using multiple strategies at the same time. This diversification helps to reduce risk. For instance, it is possible to have your automated trading 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.

At the Robust Trader, we trade as many as 100 strategies across different markets at the same time. We risk only a small portion of our capital on each strategy, which makes it much safer for us.

The common strategies used in automated trading

Different traders use different strategies for their automated trading system, but the common strategy categories for algo trading are the following:

  • Mean reversion strategies
  • Trend following strategies
  • Breakout strategies
  • Biased strategies

Mean-reversion strategies

These strategies work based on the concept that the price of any security has a long-term moving average about which the price swings and that when the price moves significantly away from the average, it tends to revert. So, when the price moves significantly above the average, it will fall back to the mean, and this creates a selling opportunity. On the other hand, when the price falls significantly away from the mean, it will revert to the mean, creating a buying opportunity.

There are many methods of using this mean-reversion concept. A common one is the 2-period RSI method, where a fall below 10 indicates an oversold market with an upward reversal potential (a buy signal). Another method is the use of the Bollinger Bands, where a fall below the lower band signifies an oversold market (buy signal) and a rise above the upper band signifying an overbought market (sell signal).

Trend-following strategies

The strategies under this category try to benefit from individual impulse price swings in a trending market. Traders using these strategies use different methods to know when a pullback is about to end for a new impulse wave to start, which is their entry time. Some of the tools used are support and resistance levels, oscillators, and trend lines.

Breakout strategy

This strategy aims to ride the increase in price momentum that is often associated with breakouts. The key factor here is identifying the qualifying price levels. A breakout occurs when the price closes above that level. The strategy may be to place a trade on the open of the next price bar after the one that closed above that level of interest. This is coded into a trading algorithm that executes the trades when the conditions are met.

Biased strategies

This is category refers to the tendency of certain markets to behave in a certain way that cannot be typically categorized under any trading strategies we discussed above. For instance, a market may tend to move in a certain direction at a specific time of the trading day.

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