Automated Trading: The Comprehensive Guide

Starting off on your investing journey is not difficult. All you need is access to an investment marketplace and the necessary resources to begin making trades on that market. But becoming a successful investor is another goal altogether. That’s why it is important to understand everything you can about how markets work, what different types of investment strategies exist and how to implement these strategies properly.

One of these strategies is automated trading. When used properly, it's an incredibly powerful investing approach. But the key word is "properly." You need to understand this specific strategy thoroughly, including how it works, what makes it so powerful and the toolkit required for it to be effective. If you're interested in learning more about automated trading, our guide will walk you through everything you need to know to get started.

What is Automated Trading? 

Automated trading is a specific type of trading system that makes it easier for investors to make buy and sell orders, by automating processes. Automated trading works by creating complex programs that codify specific trade entry and exit rules, that can then be executed by the click of a mouse or the press of a button. 

Automated trading offers a number of advantages over making investments manually. Computers can look through market data much faster than a human investor can, and this allows computers to find the information needed to make a buy or sell decision extremely quickly. Relying on raw data to make decisions also eliminates some of the emotional responses human investors might make, as a trade is automatically placed whenever a preprogrammed event occurs, such as an asset reaching a specific threshold or value.

Automated Trading vs. Algorithmic Trading  

Automated trading is often also referred to as algorithmic trading by investors and traders. While both concepts have a lot in common, in reality they are quite distinct. 

Both automated and algorithmic trading are concerned with automating the trading process, but the differences become clear upon closer inspection. In this case, algorithmic trading is one of the many components that make up a complete and integrated automated trading system. 

Algorithmic trading uses complex computer algorithms to automate the data gathering and analysis process. These algorithms are then used in an overarching system to supply the information needed for yet another program to decide whether the preset conditions of buy and sell orders for specific assets have been met. Components like quantitative modeling, tracking indicators and portfolio risk monitoring, in addition to algorithmic trading, are all a part of automated trading. 

The Pros and Cons of Automated Trading

In practical settings, automated trading is relatively straightforward. First, you choose a specific platform that provides you with automated trading services. A number of different platforms exist, and we'll list a few later to help you with this step. After you've selected your platform, you need to specify the details of your trading strategy, in terms of the rules and conditions you want to set. These parameters are then fed to the algorithm running behind the scenes.

Once you launch your algorithm, that's it — the computer take over. The algo monitors market conditions and looks for the criteria you set. Once all those criteria are detected, the algorithm follows the instructions you set out for it like clockwork — faster and more efficiently than a human trader can.

The benefits of automated trading include:

Minimizing Emotional Errors: People make mistakes all the time — that's what it means to be human. Investors, however, can't afford to make mistakes, especially when those mistakes are the result of negative emotional influences. Automated trading systems take many of the decisions out of the hands of human traders, which helps minimize the mistakes that result from emotionally charged decisions. Instead, a computer program just makes decisions based on the data it's supplied with and the instructions it's given.

Backtesting: Backtesting is a method of evaluating an investment strategy by looking at how it would have performed in historical market conditions. You should never just start using an automated trading system without testing it thoroughly first. Because of the nature of the system, you can use historical market data to see whether it's been programmed correctly without exposing yourself to any risk. Backtesting lets you evaluate the performance of your automated system and provides opportunities to fine-tune it before implementing it under real world conditions.

Disciplined strategy: Volatile markets often erode discipline among traders. The desire to avoid taking losses or to squeak out just a little more profit from a trade might lead to some windfalls occasionally, but these decisions can also lead to disastrous situations. Using an automated trading systems helps traders preserve discipline because trading rules are preprogrammed, and trades are automatically executed, which means that preconceived trading plans will be followed to the letter. In trading, no wiggle room is often a benefit rather than a drawback!

Faster order entries: No human being can ever compete with the response time of a computer. Programs are implemented at levels of speed recorded in microseconds, and that means the lag between a market condition changing and a trade order being executed upon trade criteria being met is practically nonexistent. Even a second or so counts when it comes to making trades — when markets move at the speed of thought, keeping pace with that speed is crucial to success.

Trade Diversification: Diversifying your investments is always going to be a sound trading strategy, no matter what type of system you're using. Automated trading systems can make it easier to use multiple strategies or accounts at the same time, and can help create opportunities to mitigate your risk by diversifying your approach across various assets. At the same time, you can also use this diversification to hedge against any losing positions. This amount of complexity, easily the work of half a dozen human traders, can be handled by a single computer. Trade diversification also helps avoid the risk of black swan events.

As powerful as automated trading is, there are some disadvantages to using such a strategy.

Potential drawbacks of automated trading include:

Mechanical Failure: Automated trading only works when the infrastructure it needs is properly in place. The loss of an internet connection or complete loss of power can interrupt some automated trading systems if the instructions for that system are located on a local computer instead of on the server housing the trading platform. 

Ongoing Monitoring: Automated trading systems are, in theory, designed to run without any interference. On a practical level, however, it's important to check on an automated system regularly to ensure everything is running as it should be. This is necessary because the proper operation of these systems requires all the components to be working in sync with one another. If one component isn't working properly, the results could include missing, duplicate or incorrect orders. 

Over-Optimization: This isn't necessarily a drawback that's exclusively the realm of automated trading, but it's often the case with such systems that over-optimization of automated systems can occur. When too much time is spent optimizing performance during backtesting, the possibility exists that when the system is exposed to a live market, it suddenly falls apart. The "perfect" trading plan is unlikely to be viable.

Examples of Automated Trading Strategies 

Automated trading strategies can be highly effective, making them quite popular with traders. Here are a few of the most popular, including:

Pairs Trading / Long-short equity

Pairs trading, often also referred to as long-short equity, involves matching the long position of two highly correlated stocks with their short position. The strategy is best used when correlation discrepancies are identified. Because historically the two assets tend to maintain a highly correlated relationship, a change in the value of one is often considered an indicator that the other asset is about to follow suit. Programming an automated system for these conditions will automate trades accordingly.

Mean Reversion          

Mean reversion strategies are based on how temporary high and low asset prices are. The concept is that assets will revert to their average (or mean) value over a set period.  The trick is to identify when the next mean reversion is about to take place and then to take action to make a profit. If a reversion is going to increase the price of an asset, automated systems can be configured to buy; likewise, if the price is about to drop because of a mean reversion, the same system should sell.

Portfolio Rebalancing

Investment portfolios often leverage index funds, and each individual fund is linked to its benchmark index. These funds have periods where they rebalance their holdings to bring them in line with the index they're linked to, and when this occurs, automated trades during this rebalancing period can lead to successful investment growth.

Automated Trading with Composer

Composer is unique as it's not just an automated trading platform. Composer's capabilities go much further than that. One of the biggest benefits to using this platform is that it's a no-code solution to using automated trading. This removes one of the biggest barriers-to-entry in getting started with this type of trading — having to learn Python to program the algorithms used in automated trading systems.

That's why many algo traders who are just starting out, turn to Composer as their algo trading platform of choice. Having the option to begin actively trading with Composer's unique and powerful tools while still working on and testing your own algorithm behind the scenes, offers the best of both worlds to algorithmic traders.

The world of automated trading is fascinating and diverse. The ability to preprogram trading strategies via a computer and then set the strategies to run automatically represents nearly limitless possibilities for better, more successful trading.