What is Algorithmic Trading?

Robots are dominating Forex trading, and the algorithmic trading industry has developed in an extraordinary way. To put this in perspective, imagine that almost 30% of the London’s trading is now made by robots. Sudden spikes and dips are seen in the market when an important news item is released. These moves are caused by robots trading in the same direction at the same moment in time. It is not possible for human traders to do that, but robots can execute thousands of trades per second, in complicated algorithms based on quantum maths. Human traders are thus following behind the robots. It is well known that ahead of important economic events, no matter what your analysis, if the news in interpreted as bullish by the robots, the price will jump. As with any market, the Forex market is subject to supply and demand imbalances, and these are mostly seen during important events. Algorithmic trading is noticeable when important events are released, such as Non-Farm Payrolls, the Federal Open Market Committee (FOMC) Statement, ECB press conferences, etc. Because of the huge volume that is traded on the Forex market daily, these sudden spikes and increases in volatility are largely attributed to robots rather than human traders. However, these robots are programmed by humans, and so in a way human nature is incorporated, and the error factor is still there.

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Why Using Algorithmic Trading?

One reason for using algorithmic trading is to take in all the trading signals that a trading strategy can offer. As a human trader, one cannot trade 24/5, all the time the Forex market is open; but a strategy for this can be coded and programmed. Not all of them can be coded, but the ones based on technical indicatorssuch as oscillators and the like, can. Such a robot is instructed to buy or sell when specific conditions are met. If the indicators or the inputs are giving a signal, the robot will take it. You should be careful before stating that a strategy works, and back-test it both manually and automatically. Moreover, the results may still be different, due to slippage that can appear. Even more, results in a demo account will be different from those in a live account, because the execution is different. As an example, imagine an Electronic Communication Network (ECN) broker. Such a broker has tight spreads most of the time in a trading day, except for periods when volatility is high and when positions are rolled over onto the next trading day. If there is a trade to be taken during these times, slippage and the costs associated with the trade (spreads) will result in an additional cost. These costs are not seen when back-testing a strategy. Nevertheless, retail traders who are not able to watch the market, and are not doing this for a living, prefer to trade with robots. It has advantages and disadvantages, and traders will answer differently to such a question. The ones who oppose algorithmic trading will say that there is no robot that can see what the human eye can see. Those who favour this trading type will say that emotions are left aside, and greed and fear will not intervene in trading anymore. Fear and greed are the biggest enemies in trading, and mistakes caused by them are avoided with algorithmic trading. This doesn’t make trading perfect, though. Another reason why algorithmic trading is used by big investment houses is that in this market, the one who is the first to execute the trade will get a bigger chunk of the profit. There is an ongoing race between investment houses for the best technology to be used, as this offers a giant competitive advantage. Competition is so stiff in this area, though, that it is difficult to be the first over the line. Even fractions of a second make the difference between successful and losing trades.

Algorithmic trading is also called high-frequency trading.

This is because of the huge number of trades that are taken by these robots in a very short period of time. These robots are programmed to buy or sell based on the economic news that is released. If the actual news differs from the expected data, the trading algorithms are programmed to buy or sell a currency/currency pair. The bigger the difference, the bigger the resulting move. Also, trading algorithms buy and sell a currency based on snippets in a news item, looking for words that may signal a change in the monetary policy of a central bank. If the central bankers are using hawkish words in their statements, the algorithms will buy that currency. On the other hand, if the message is perceived as dovish, the trading algorithms will sell a currency. All in all, if you’re looking for someone to blame for the sudden spikes when economic news is released, you have found the main suspect. The following are regular news items where algorithmic trading can be spotted:
– The Non-Farm Payrolls in the United States
– The European Central Bank’s interest rate decision
– The FOMC Statement
– Other major central banks’ interest rate decisions and press conferences
– Any speech held by major central banks, etc.
What is Algorithmic Trading
To sum up, look for red events in the economic calendar to see trading algorithms spotting for the probable move. Human traders should avoid reacting to this news and, instead, should focus on the bigger picture. Trading bigger timeframes is the way to go, as this will filter out the daily noise and fake moves caused by algorithmic trading. Moving forward, expect the trend to become even more aggressive. The new MiFID II regulation is about to be introduced in the United Kingdom starting in January 2018 as a result of Brexit. While this affects mainly UK brokers, it has ramifications in other jurisdictions as well, as UK traders are not bound to trade only in the UK. One of the changes refers to slippage and execution, so algorithmic trading, at least on the retail side, will change once again. Most likely, in time, other jurisdictions will move in the same direction, again changing the way in which markets are traded.

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