HFT (High-Frequency Trading) in Forex Markets
The High-Frequency Trading (HFT) industry is the one that is usually being blamed for all the bad things that are happening in the Forex market. Brokers blame the HFT algorithms and trading setups when volatility increases and they are not able to provide stable rates as promised to customers. Traders blame HFT because they are being stopped with violent moves as these moves are being triggered by these algorithms as well. And finally, central bankers chose their language very carefully as not to create violent turbulences on the financial markets. What is the cause of such turbulence? High-Frequency Trading, of course. Despite the general belief, the returns in this industry are not that big. A simple Google search will show you that monthly single digit returns are the norm, and actually most of the months these returns are in the low single digit area, with negative months being casual. A very pertinent question would be why being involved in the HFT industry after all if the returns are so small? The right answer to this question is that while percentages are small, the amounts they are referring to are significant. This is being called scalability. It is one thing to make a twenty percent rate of return on a one hundred thousand accounts and another one to keep the same performance on a two billion account. Scalability refers to the ability to reach the same percentage wise performances on different account sizes.
Types of Robots in the HFT Industry
There are many types of robots in this industry, or computers programmed algorithms, starting with quants and ending with very basic buying and selling and in order to understand the size of this industry, imagine that these robots actually take thousands of trades per second. Yes, that is correct. Thousands of trades are being traded each and every second and this is what makes the Forex market to be so unpredictable and full of fake moves. The normal retail trader is calculating the pips performance based on a five digits’ quotation, but the HFT industry is trading on the 7th and 8th digit of a currency pairs quotation. Can you imagine the access to the interbank liquidity, the resources and the costs to sustain such execution, not to mention computer hosting and maintaining costs? These are tremendous amounts that are being paid but it seems they are worth the trouble.
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News Based Trading Robots
These robots are being programmed to buy or sell on the outcome of an economic new. As every trader knows by now, the economic calendar is offering us the possibility to know in advance the important economic news to be released in the week ahead and a forecast is known in advance as well. This forecast represents the average of a survey of economists and if the actual economic release/number is better than the forecast, then it is being considered as positive for a currency, so it should be bought. The opposite is true as well, with a disappointing release being met will selling orders. When it comes to the trading algorithms mentioned above, they are programmed to buy or to sell based on that outcome. This is why the economic news is being released exactly at the top of the hour or by the second on that due date, so these algorithms should not start buying or selling earlier. Therefore, price stability, the long-lasting dream central banks have, has more time to come true. On important economic events, we’re talking about extremely violent moves as all these robots are trading in the same direction. Remember the scalability concept mentioned at the start of this article? Because of it, the actual amounts of money these algorithms are moving are tremendous.
Consider that such moves are being made in a market that trades more than five trillion dollars each and every trading day and you’ll see why it is really difficult to have such spikes. For the HFT industry, though, this is the norm.
If you think that what was described above is not spooky enough, consider this. There are trading robots that are instructed to buy or sell based on different words that appear or not in documents or statements that are released. Let me give you an example. Every six months the Federal Reserve of the United States is holding its regular Federal Open Market Committee (FOMC) meeting and at the end of it, the FOMC Statement is being released to the press. Traders (or actually programmers that work for the HFT industry) are setting these robots to buy or sell based on the text differences between the actual FOMC Statement and the previous one. The emphasis is being placed on words that may mean something for the overall future monetary policy and the outcome is a terrible move in the Forex markets. Moreover, the same algorithms are being “glued” on newswires, instructed to read financial “snippets” transmitted from different press conferences, economic events, etc., and order to buy or sell a specific currency are being transmitted with the speed of light. Trading is not like it used to be as the IT industry changed the face of it forever. We cannot even imagine what it would be in the period ahead of us, but one thing is sure: if the last decade’s robots were following humans, in trading, this is not the case anymore. Human traders, and especially retail traders need to adapt and follow the footsteps of these robots or this HFT industry as it is the only way to survive in such a competitive environment. This industry is changing so fast that it is virtually impossible to stay as it is. What retail traders should do is to properly understand what moves markets, what are the drivers in the Forex market and how can profits still be made against all these adverse conditions. After all, robots are still programmed by humans and human nature dominates trading as much as it does to any other industry.
Other educational materials
- What is Forex Trading?
- What is a Currency Pair?
- Majors and Crosses – How to Trade Them?
- Leverage and Margin Requirements
- Forex Trading Platforms – Metatrader 4 and 5
- Trading Sessions and Their Importance
Recommended further readings
- “High frequency trading.” Biais, Bruno, and Paul Woolley. Manuscript, Toulouse University, IDEI (2011).
- “High-frequency trading.” Deutsche Bank Research 7 (2011) Chlistalla, Michael, Bernhard Speyer, Sabine Kaiser, and Thomas Mayer. .