Why Is Robotic Trading Gaining Popularity?

Trading with robots has opened up a world of possibilities in different approaches and strategies that no person could ever fulfil on their own. The robotic trading industry requires experienced chartists who understand market dynamics at a complex level and can translate this into a profitable automated system. 

9 min read


We live in a world of constant digital transformation where computers are handling processes that used to be performed by humans.

This concept is nothing new in the financial world, but robotic trading has recently gained prominence. And it’s not only limited to your everyday ‘bedroom’ trader. Large financial institutions like investment banks and hedge funds have been using robots for a long time. As technology has gotten more sophisticated, so have investors. 

We have too many moving parts in online trading. When you first start, you spend months practicing on a demo account, watching videos, and reading written material. 

Then you’ll need to develop your strategy and incorporate complex analysis to make decisions. Just when you think you’re done, you still have to watch your charts and keep track of your positions.

Many of these tasks are repetitive and time-consuming, not to mention the human error element involved. On the other hand, trading robots are more efficient, faster, and time-saving than self-directed traders.

What is robotic trading?

Robot trading is using computers or software programs to trade a financial market instead of manual execution.  By financial market, we refer to instruments like crypto, forex, metals, options, stocks, and commodities, among others.

When we speak of robotic trading, we speak of trading with robots, algos, algorithmic trading, automated trading, or bots; it’s all the same. However, robots are most popular with the currencies market on the MetaTrader platform, where we call them ‘expert advisors’ or EAs.

Robot traders are plug-and-play solutions designed to automate the entire execution process from start to finish without manual intervention. A skilled developer programs these systems according to predefined mathematical parameters extensively tested from existing profitable strategies.

Such strategies can range from scalping (or day trading), mean reversion, and trend-following to more advanced systems like high-frequency trading and arbitrage.

Trader robots will work around the clock, scanning for opportunities. Once they have identified set-ups, they will automatically open a position and close it where necessary for a profit or loss. Robots know how much money to allocate for every order based on what has been programmed by the developer. 

Robotic traders have several purposes. The first one is that they strip away human emotions. Also, they can place positions at an incredible speed no person could achieve naturally. When you use a robot for trading, you can dabble in other markets simultaneously while saving time and effort from executing orders.

This allows for much wider and more efficient diversification, increasing your profit potential. Despite the incredible automation benefits, it’s not without many flaws. Many experts still believe a human is the most advanced trader. 

However, the slow rise of artificial intelligence may change this narrative. Still, manual discretion is not easy to implement with robotic software for trading in situations where it’s necessary. 

There is also the risk of over-optimisation or curve fitting to achieve a near-perfect or flawless trading system. Finally, unless you plan to purchase an existing robot trader, you need some solid programming or coding experience to develop automated systems.

Types of robotic trading systems

We mean various things when we speak of using a robot for trading. They are capable of simple trend-following stuff all the way to complex arbitraging and trading high-impact news events.

Mean reversion robot traders

Mean reversion is the idea that the prices of a financial asset return to an average level in the long term. This level acts as a support or resistance zone the market returns to in the future.

Mean reversion simply describes the nature of trending markets to move in a step-like motion of retracements. Algo robotics geared towards this trading style often incorporate a moving average, a standard indicator for mean reversion. 

A moving average (MA) is a line based on the average prices (typically the closing prices) over a specific period. The developer will program their bot for opportunities when the market touches the MA.

The image below shows the 100MA on the 15-minute chart of EURGBP. This means that the moving average is the average closing price on this time frame over the past 100 days. Notice that the price kept increasing every time it bounced on the MA, reinforcing the simple concept of mean reversion.

Mean reversion robotic trading

Other indicators implemented in mean reversion trader robots include the MACD (Moving Average Convergence Divergence), Bollinger Bands, RSI (Relative Strength Index) and many others.

Reversal robot traders

While others prefer to stay with the trend, others find opportunities to go against it with reversals. These will be programmed usually based on common indicators settings for counter-trend movements.

One simple strategy is using the moving average crossover system. The idea is to implement two MAs of two periods, a higher period and a lower setting. When either intersects the other, it suggests a trend change. 

Below is an example of a 10 and 20MA crossover system on the EUR/AUD 30-minute chart.

Crossover with robotic trading

Similar to trend trade robots, developers can incorporate several archetypal technical tools individually or combined with others.

Hedging robot traders

Hedging is the practice of buying or selling two markets with a shared directional correlation to offset losses. You can hedge in many financial instruments. Yet, FX is the simplest market to hedge because you deal with pairs.

A hedging trader robot in forex may use a simple direct hedge on EUR/USD by applying a sell position first and a buy position immediately after. When the first order shows a floating loss, it will close it at some point while the other position runs at a profit.

This is the basic idea of hedging, but, of course, it’s not so simple. However, hedging robotic traders can go further by strategically placing orders above and below the current price until they can close at a small profit.

Scalping robot traders

Robot trading scalpers specialise in opening multiple, often high-volume positions in a session and closing them in seconds for a small profit. While high frequency is a key in scalping, you must be strategic about the time you scalp.

It works best in highly active and volatile periods. Scalping robots usually look for opportunities on smaller time frames, given the regular price action they contain. It’s also essential for the scalping robot to scalp on markets with the lowest spread to reduce transaction costs.

High-frequency robot traders

High-frequency robots

Unlike most robot traders that place orders at relatively the same frequency as the average person, HFT (high-frequency trading) systems are the opposite. We characterise these by ultra-fast speeds where multiple and massive orders are opened and closed in fractions of a second.

HFT is often associated with institutional traders like hedge funds and other large financial organisations. This is because HFT systems are sophisticated and require the most advanced infrastructure development, logic, and co-location.

HFT robot traders are a subset of their own with several speculative strategies falling under them:

Market making

Market making

Any market is a function of liquidity providers or market makers. These organisations provide a massive ‘inventory’ (worth millions or billions of dollars) of a particular financial instrument at different traded prices.

They get compensation from transaction costs (usually the spread). Due to the sheer size of the inventory and the number of traders in a country or worldwide, high-frequency robot trading is necessary to offer liquidity at the fastest speeds possible without delays.


This is where you take advantage of slight price differences in a financial market by buying it from one institution at a cheaper value and selling it at another for a higher value. The most advanced form of arbitrage is called statistical arbitrage.

It’s a strategy where you capitalize on narrow price gaps or deviations between two or more markets through mathematical and computational models.

News trading

Impactful news announcements, whether scheduled or random, can have a massive effect on the prices of a market. High-frequency robotic traders can crawl through many sources of such news from outlets like Bloomberg and even feeds from Twitter.

They can incorporate this data semantically through keywords, company names, etc., and trade news events faster than a human could process this information individually.

Spoofing and layering

Both of these are manipulative tactics with serious legal consequences for the offenders. People often use spoofing and layering interchangeably, although they are technically different.

Spoofing creates fabricated inflated supply/demand of a particular instrument. It’s cancelling before execution. For instance, a trader robot could place multiple massive sell orders at a specific price to attract sellers. The robot will then cancel the order when the market gets nearer to that value.

This event would cause an imbalance where a dramatic sell-off ensues. Once the price is at a certain point, the ‘spoofer’ can then buy at a much lower cost and profit when the market goes up.

Layering is a form of spoofing to gain a more favorable price than other participants. Here, a robot creates multiple live orders at close-by incremental value tiers. This layering causes the spread to diverge from its midpoint.

At this stage, it becomes more optimal to cancel the first orders and enter with opposite positions (in this case, buy orders).

AI and machine learning-based robot traders

AI and machine learning-based robot

Even though automation is involved in a robot for trading, many of these are not based on human perception or artificial intelligence. A basic bot is usually created from existing technical tools set in stone.

However, these cannot apply sentient discretion, which is one significant drawback of automated trading. AI in traded markets is still opaque and in its development stage. Yet, the aim is to have robots that can think like humans and do more sophisticated stuff like

  • Predictive analytics to anticipate anomalies like ‘black swan’ events ahead of time
  • Updating to economic changes in real-time
  • Providing investment-related insights

Why consider robotic trading?

Let’s look at the main reasons why robotic trading is gradually becoming sought-after:

It saves a lot of time

As they say, time is money. Although manual trading may be an interesting endeavour for some people, it can be highly time-consuming. Trading with robots allows investors to create an income stream and focus on other activities, whether a full-time job, a side hustle, a business, or simply having fun.

Tireless connectivity

As a manual trader, it is possible to experience temporary internet downtime, resulting in missed set-ups and entries. Other limitations may include a time zone clash. This is an opportunity cost if you’re asleep when others are busy with the charts.

A robot can stay online for a trading day or week if you’re using the fastest internet connection or a virtual private network.

Allows for much faster and more voluminous execution

If you have an existing scalping strategy, adding automation can allow you to achieve split-second execution without delays. Timing is everything in online trading. A millisecond can have a massive effect on your entry and, ultimately, your bottom line.

It’s not only about the speed but the volume, which also affects the potential size of your gains. You cannot add multiple orders in succession without lag in between with manual execution. Also, it requires effort and a stable internet connection.

You can diversify into various markets

If you prefer to be active in more than one financial instrument, trading with robots is the way. Time-saving is an element related to this quality. However, a robot is like having copies of yourself in different markets simultaneously, all from a single creation.

Reduces emotional errors

Even if you are intelligent, maintaining discipline can be challenging at times. Trading any financial market is just as much about psychology as excellent chart reading.

Without the right mindset and emotional control, traders can commit mistakes that may cost them profiting opportunities or, worse, lose them money. On the other hand, robots can stick to rules with no deviation or uncertainty; everything is simply black or white.

Should you build or buy your own robotic trading system?

That is the question. Both approaches have pros and cons related to time, infrastructure, and experience.

Benefits of purchasing an existing robot:

  • The most straightforward reason to understand here is that it saves months and sometimes years of development time. All you need to do is follow a simple set of instructions laid out by the creator.
  • This approach is accessible to newcomers in the industry of robotic software for trading.

Drawbacks of buying an existing robot:

  • If you have little online trading knowledge, understanding how a robotic trader works will result in a steep learning curve.
  • As a user, you have no customisation in how the robot performs. There may be cases where the developer has not described the models behind the programming.
  • The creator can present fabricated or over-optimized results.
  • Lastly, depending on the vendor, the most advanced robotic traders are expensive and may not be publicly available.

The alternative is, of course, to build your own bot. Here are some reasons you may prefer doing so:

  • Your robot trading system will perform according to your specifications if you are skilled enough.
  • Even after your bot has gone live, you can make any changes to it when it malfunctions or doesn’t perform as expected.
  • If your robot can show a sustainable track record of profitable performance, you can sell it to other investors for a healthy sum.

Still, manual development has some drawbacks:

  • It is time-consuming.
  • Creating a robot for trading requires exceptional programming AND chart-reading skills. It is a rare trait to find a trader that is brilliant with manual trading and coding at the same time.
  • Depending on the complexity, building can cost some money, which may apply during the initial phase and for future improvements.

Is robotic trading profitable?

Most people new to the subject wonder if robotic trading works. A better question is whether it is profitable. It depends. An automated system is only as good as the person or people that programmed it.

One major drawback of trading with robots is many lack awareness to identify changing market conditions that only the human eye can discern. Most bots are generally designed to excel in specific circumstances but perform badly in other scenarios.

Yet, a manual trader can tell when it’s time to get out when things aren’t looking favorable based on instinct and experience. The other problem is the commercial aspect. There is no regulation in virtually all financial markets about the sale of automated systems.

Many robots available to retail clients don’t live up to expectations. Well-off investors or institutional traders can access much better-performing robots that the average person couldn’t afford.

So, to summarise, a robot can make profits. However, it depends on its strategy and how well it has been shielded from unfavorable conditions. Also, many publicly available bots sold by other traders could be of better quality.


Trading with robots has opened up a world of possibilities in different approaches and strategies that no person could ever fulfil on their own. The robotic trading industry requires experienced chartists who understand market dynamics at a complex level and can translate this into a profitable automated system. 

This is why even long-time investors prefer doing things the old-fashioned way through manual trading. Ultimately, it’s all about your goals and what is most effective in profiting.

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