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Algo-trading or Algorithmic Trading in a new recent concept in financial markets, and thanks to the existence of technology and science in this field, traders are showing interest every day. Computers and technology have changed everything—financial markets are no exceptions.

In this article, Algorithmic Trading will be discussed in details. Moreover, how to become an algorithmic trader will be answered by providing a roadmap.


What is Algorithmic Trading?

According to different sources like, “Algorithmic Trading (also called automated trading, black-box trading, or algo-trading) means using a computer program that follows a defined set of instructions.”

To put it simply, the computer program (the automated trading system) accepts the responsibility of executing trades in the financial markets, and human intervention becomes almost zero, and there is no role for a trader in opening and closing trades, defining profit and stop loss, volume (lot) calculation, etc.

The main difference between algorithmic trading and traditional (manual) trading is the amount of human involvement. Some statistics say that today more than 80% of the trades in financial markets are filled automatically; meaning manual trading might be entirely put aside in the future.

For confirmation, Wikipedia says: “in the twenty-first century, algorithmic trading has been gaining traction with both retail and institutional traders. It is widely used by investment bankspension fundsmutual funds, and hedge funds that may need to spread out the execution of a larger order or perform trades too fast for human traders to react to. A study in 2019 showed that around 92% of trading in the Forex market was performed by trading algorithms rather than humans.”


The Main Application of Algorithmic Trading 

Studying algorithmic trading from scientific and individual aspects, gives interesting results.

Scientifically speaking, since no human is involved in algorithmic trading and computers do all the work, the error rate is almost zero. In addition, processors perform calculations thousands of times faster than humans. In fact, computers—although deprived from the ability of deduction—are built to quickly perform repetitive tasks that require high precision. In the financial markets, sometimes a small mistake can cost a huge loss. Fortunately, there are almost no chances for fatal errors in algo-trading.

Markets are always subject to volatilities due to various reasons such as news, events, etc. Making the right decision in times of market volatility, and reacting in the correct way so that the least damage is suffered, is the most important thing. If there are proper defensive barriers against market ups and downs in an automated trading systems, then the trader can be rest assured that his/her trading account will almost never be lost due to, even extreme, fluctuations.

Money management, undoubtedly, can be considered one of the sides of success in the markets. But how a trader manages his/her trades in terms of money management is vital, and in many cases, the inability to properly manage causes severe losses. The main reason for the mentioned inability of management is human emotions such as anxiety, anger, revenge, etc. Traders generally take emotional decisions, or sometimes try to take revenge instead of controlling themselves after a loss.

However, when the money management is entrusted to an automated trading system, the system will never be involved in the excitement of profit or loss or anything similar. So, a positive rating for algorithmic trading can be considered here.

Individually speaking, algorithmic trading has many advantages over manual trading. Traders are not empty of feelings. As somehow mentioned, emotions are very involved in trading. Many traders will be disappointed after a (heavy) loss. At this time, it might be very difficult to return to the market, having a positive hope for the next trade.

Daily life, its events are also impossible to remove from the life of a trader. Sometimes a bad news, unrelated to the market, can affect all the future trades. Even the noise of children inside the house may reduce the concentration, and it is quit a fact.

But with algorithmic trading, anger, stress, revenge, lack of concentration, even getting cold, and all the issues that exist in every human’s daily life, will disappear and will not have any effect on the trading process.‌ Remember that computers are perfect for performing quick repetitive tasks with a high precision.


Simple Examples of Algo-Trading 

  • In the Forex market, long 2 lots of EUR/USD (Euro vs. US Dollar) if the EUR/USD falls below 1.2012. For every 10 pip fall in EUR/USD, cover the long by 0.5 lots. For every 10 pip rise in EUR/USD, increase the long position by 0.5 lot.
  • Buy 50,000 shares of Apple (AAPL) if the price falls below 150. For every 0.1% increase in price beyond 150, buy 1,000 shares. For every 0.1% decrease in price below 150, sell 1,000 shares.

These two are simple automated trading systems (not useful in reality of course), that perform money management at the same time.


How to start algo-trading?

To enter the world of algorithmic trading, no exact path can be suggested because financial markets and trading are not absolute. But according to the experiences the proposed route can be determined to a good extent.


Skills Required 

As a retail investor, algo-trading can be started with:

  1. Understand the Market

The very first step to start algorithmic trading is understanding the market and its specifications. Technical and fundamental analysis are commonly known as the two key tools to understand the mechanism of financial markets. Of course, each market has its own features. For instance, the option market requires the trader to be familiar with the terms and definitions of the market. The same is true for the Forex market.

  1. Having a Trading Strategy

Trading strategy means entering the trade and exiting it at the right time. But knowing the right time of entry and exit is not easy. By using tools such as technical analysis indicators, the trader can have a good entry and exit, and create a trading strategy.

Also, if building a trading strategy is time-consuming, software such as StrategyQuant X are available, so that the job of building a trading strategy can be done automatically by the software.

  1. Backtest the Trading Strategy

Backtest means analyzing the performance of the trading strategy in the history of the market, or using historical market data. It is impossible to evaluate the performance of a strategy in the future of the market. So, the past can be a criterion to check the performance of the strategy (in the past) and hope that this performance will continue in the future. Therefore, it is also very important to do backtesting correctly.

Learn how to backtest a trading strategy correctly

  1. Choose the Right Platform

Choosing a good trading platform and broker that can meet all the needs of a trader and at the same time is up-to-date is very necessary and of course requires a little research. Generally, platforms like Metatrader4 and 5, TradeStation and TradingView are the answer to all needs.

Fig 1. TradeStation Trading Platform. One of the Bests.



  1. Demo and Live Trading

Every trading strategy must first be tested on a demo account for a while and its effectiveness should be checked. It is not recommended to transfer trading systems directly to real accounts because if there is a problem in the strategy, it might be impossible to compensate the losses coming after.

After passing the test in the demo account, a real account with a small balance can be the beginning of a trading strategy in the financial markets. If there is no problem in the performance of the trading system, the capital can be increased little by little.

  1. Keep Evolving

Quality improvement is endless. Trading strategies cannot be useful forever in the market and every trading system has an expiration date. Markets are constantly changing. Thus, trading strategies should be optimized from time to time, so that the parameters adapt to new market conditions.


If you are not familiar with the above-mentioned skills, you can either learn the required skills gradually, or you can use an algo-trading software like StrategyQuant X to automate all the stages of building, backtesting, and optimizing a trading strategy.

The output of the StrategyQuant X software is a ready-made trading system file that should only be executed by the trader on the trading platform.

Fig 2. Suggested Skills for Algorithmic Trading.

Fig 2. Suggested Skills for Algorithmic Trading.


Is programming required?

The answer is no. You don’t need to learn programming at the beginning of your career. Of course, knowing a related programming language like Python, or MQL4/5 can give you high maneuverability and remove many challenges for you. However, if for any reason you are not interested in learning programming, you can ask a programmer to do the work for you.



Algorithmic trading is developing every day and more and more traders are showing interest in this field. Many advantages can be considered for algorithmic trading and automated trading systems. Among them, many challenges such as the involvement of human emotions in the trading process are eliminated. Trading robots never get tired, they don’t need to rest and they don’t get involved in emotions, they don’t make mistakes either.

In other words, automated trading systems have brought more freedom to humans, and a trader with his/her own automated trading system only has to monitor the performance of the trades. In future articles, different aspects of algorithmic trading will be discussed in more details.

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