How to build Automated Trading Systems

Thanks to advances in machine learning and artificial intelligence, it's now possible for investors to build automations into their everyday trading at a level never seen before. These automated trading systems have unlocked innovative approaches to investing that offer unique and attractive advantages.

For investors, one of the biggest attractions of automated trading systems is that they can be custom-built for specific purposes. No matter what asset you're interested in trading, there's likely a way to build an automated system to carry out those trading activities. The trick is understanding what goes into the construction of such a system. Here's what you need to know about how to build automated trading systems.

What is an automated trading system? 

An automated trading system is any collection of preconfigured computer programs that can make buy and sell orders for assets automatically, with little to no human intervention. Such a system makes heavy use of algorithms, which are processes or sets of instructions that a program follows to determine whether a specific asset should be bought or sold. These algorithms work by taking market data and comparing it to that list of instructions. When market conditions meet the preprogrammed criteria, a trade execution is triggered.

Why build an automated trading system? 

Automated trading systems offer several advantages to the savvy investor. Unlike the capabilities of human traders, an automated system performs at a much faster speed, which makes high-frequency trading strategies more viable. Automated systems also take human decision-making out of the process, which avoids the possibility of manual trading errors spurred by human traders making emotional decisions.

Automated trading systems make it easy to test and fine-tune a system by backtesting its performance with historical market data, meaning there's no need to unleash a new and untested system on a live market. Automated trading systems also help maintain discipline while trading, as the algorithms that comprise automated systems cannot deviate from their programming.

Drawbacks of automated trading systems

As powerful as automated trading systems are, they're not without their disadvantages. 

First, they can be susceptible to mechanical failures. These systems are dependent on technological equipment like computers and digital infrastructures like the electrical grid and the internet to function properly. Breakdowns in this equipment or infrastructure can result in disruptions to the system's ability to function.

Another drawback to an automated trading system is that while they are designed to operate independently, they do need to be monitored regularly to ensure they are working as intended. Without relatively close monitoring to ensure the system is making trades properly, investors run the risk of suffering financial losses in the event of a malfunction or service interruption.

Finally, automated trading systems can sometimes suffer from over-optimization. Systems that have been designed to be as perfect and flawless as possible may test well when presented with historical data but can often falter in live trading environments. This could be because humans have added excessive rules that make the process more complicated instead of making it simpler. Spending time and resources to optimize an automated system in this way often results in more failure states or malfunctions because of this over-optimization.

How to build your own automated trading system

Building your own automated trading system is straightforward, but it's not necessarily an easy task. Several steps require detailed skills and knowledge of how automated systems work. This is in addition to knowledge of market assets and trading strategies. Here's what you need to keep in mind if you're building your own system.

Define your investment strategy: An automated trading system makes use of preprogrammed trading strategies to drive its core function. As a result, you will need to select the trading strategy you wish to employ. Several strategies have been proven to be effective when combined with automation. These include mean reversion, trend following and index rebalancing. You'll also need to decide on the specific details of what assets you'll be trading and what thresholds will trigger trade executions. 

Create your system in Python: Automated trading systems make use of algorithms to function. These algorithms are created in a programming language, just as any other computer program is created. The industry leader in programming languages used to create automated trading algorithms is Python. You will need to learn Python, which can be a long and labor-intensive process. Alternatively, you can hire a skilled Python programmer. You can read more about this on the Composer blog.

Connect to a broker: To use an automated trading system, you need to partner with a direct-access broker. A direct-access broker acts as a digital middleman between your automated trading system and your chosen market, providing the access your system needs to interface with that market. You can choose from dozens of brokers, all of whom have different levels of service they offer to automated traders. A few considerations when selecting a broker could be cost, servicing support, and margin requirements (if applicable).

Deploy and monitor: Once you've designed your system and chosen a broker, it's time to deploy your automated system and monitor its performance. It's advisable to begin with a broker or platform that offers access to historical market data to backtest your system for initial troubleshooting. Once you're satisfied with its performance, it's time to provide your system with access to live markets and monitor it closely to ensure it's operating as you designed it to.

Choosing an automated trading platform

It's difficult to pinpoint the best automated trading platform, as each platform offers a different range of services. Depending on your goals as a trader and the capabilities of your automated system, a platform that might be ideal for you may not be for another trader with a differently designed system. 

Despite this, there are some qualities you can look for in a trading platform if you're searching for an ideal choice for your needs. The ability to perform backtesting is a definite advantage because this allows you to work out any bugs in your automated system before risking resources in live trading environments. You also should pay attention to the fees associated with the services a platform provides — you can make dozens of cost comparisons between platforms. 

Next, the ability to begin trading immediately through the use of a platform's own pre-programmed trading bots is also an advantage because this allows beginner traders to get a feel for automated trading as they learn the intricacies of coding algorithms in Python. An example of a related service is a platform like Composer, which offers a unique no-code solution to help investors begin using automated trading quickly and easily.

Automated trading systems have revolutionized the approach of many when it comes to asset investment. As these systems continue to become more advanced, there exists even more potential for automated trading to become a more effective tool for modern traders. This makes delving into the world of automated trading and building your own system an attractive proposition.

Understanding the processes behind building your own automated trading system is a crucial and necessary step to this process. You need to grasp the concepts behind automated trading, understand how trading algorithms are designed to work, how they can be programmed effectively and how to choose the right combination of trading strategies to capitalize on the unique characteristics of automated trading. If you want to learn more about this process, sign up for a free trial at Composer today!