The Technology Behind Automated Trading: How Does it Help Investors?

The practice of automated trading has become increasingly dominant throughout the digital age, even within more traditional markets and asset classes.

For example, throughout the US stock market and similarly developed financial markets across the globe, up to 75% of the total trading volume is generated through algorithmic trading.

According to Deutsche Bank, approximately 90% of equity-futures trades and 80% of cash equity orders are also executed algorithmically, without any kind of human input or interaction at all.

But what exactly do we mean by algorithmic trading, and how does the technology that underpins this practice benefit traders? Let’s find out!

What is Automated Trading and How Does it Work?

In simple terms, automated trading describes a method of financial market investment that leverages software and algorithms to execute orders.

Of course, such algorithms are programmable, enabling you as a trader to establish predetermined entry and exit conditions based on your wider market analysis. Theoretically, this strikes the ideal balance in the relationship between humans and technology while it also enables a high volume of trades to be executed quickly and efficiently.

Because of this, automated trading is primarily favored by scalpers and day traders, as it maximizes their ability to open and close multiple orders within a matter of minutes.

But how does automated trading work?

Well, it relies heavily on your existing knowledge and insight as an individual trader, as well as your ability to conduct thorough technical analysis and set informed parameters for the positions that you open (and subsequently close).

This can also include instructions such as trailing stops and stop losses, the latter of which automatically close a position once it has incurred a predetermined level of loss. Once the parameters have been refined and set, your positions are managed automatically and intuitively, minimizing your involvement and negating the need to constantly track price movements.

At this point, it’s also important to define precisely what we mean by ‘technical’ analysis. This is a trading discipline that’s employed to evaluate investments and identify new market opportunities, while it’s driven primarily by the study of past trading activity and price movements.

These are believed to be valuable and insightful indicators of future trends and shifts, especially in response to specific geopolitical events (such as national elections) and certain macroeconomic conditions.

You’ll also come to rely on a number of technical indicators when carrying out this type of analysis. These refer to mathematical calculations that are built on historic trading data (such as asset price and volume), and they can be used to identify moments when assets are being overbought or oversold in the marketplace.

One of the most common technical indicators is an ‘oscillator’, which tracks the distance between two points on a technical analysis graph and can be leveraged to track momentum or identifiable trends.

An Example of Automated Trading

As automated trading typically favors scalpers and investors with a similarly short-term outlook, this practice is commonly used to engage in speculative trading and predict whether an underlying market price will rise or fall in a predetermined period of time (without requiring you to assume ownership of the underlying financial instrument).

When conducting technical analysis and setting the parameters of your trade, timing is the key consideration. This will determine exactly when your position should be opened and closed while stipulating the precise quantity and volumes involved.

For example, your parameters may instruct the algorithm to ‘buy 100 Microsoft stocks when its 50-day moving average moves above its 200-day average’. The moving day average is a common form of oscillator, while in this instance, it helps to create a clearly defined entry point and buying instruction.

Informed market analysis, understanding, and clarity are all key here, as, despite their increased reliance on technology, algorithmic trading is only ever as successful as the quality of human input that goes into it.

The Benefits of Automated Trading for Investors

Of course, human investors are also well-placed to reap the benefits of automated trading, especially scalpers or day traders who look to generate incremental profits from a high volume of individual orders.

So, let’s take a closer look at the benefits of automated trading and how they can translate into greater success for investors.

●     #1. Backtest Your Systems: The concept of backtesting is a crucial one, as it applies trading rules to historical market datasets in order to evaluate the viability of a particular strategy or idea. By backtesting your own parameters and trading algorithms, you can ensure that all rules are absolute and leave no room for interpretation, as this optimizes the chances of your trades being profitable over time. As a result, it’s a key risk management measure that can curb potential losses ahead of time.

●     #2. Negating the Impact of Negative Emotion: On a fundamental level, automated trading software is highly deterministic, as it’s completely data-driven and understands the underlying rules that govern change in the marketplace. Because of this and its ability to seamlessly manage trades from start to finish, automated trading minimizes the threat posed by emotive trading and makes it much easier to adhere to a predetermined strategy. In this respect, it preserves discipline and focus, which are key characteristics if you’re to succeed in highly volatile marketplaces.

●     #3. Optimizing Order Entry Speeds: As I’ve already touched on, scalpers and day traders regularly utilize automated trading to execute a high volume of orders within relatively short epochs of time. One way in which algorithmic trading helps in this respect is by optimizing order entry speeds without compromising on accuracy or the quality of input. This also enables traders to leverage short-term price shifts in the market, whether these are caused by temporary broker errors or external market conditions.