High Frequency Trading (HFT) is trading that is designed to generate almost guaranteed profits (albeit very little) for minimal risk. The repetition of these trades quickly leads to substantial profit especially if the trading involves huge sums. HFT is reliant on the ability to obtain, analyse and execute trades quicker than other market participants. To do this, traders employ powerful computers laden with complex software.

To understand HFT, you will need to have a good grasp of the current framework along with the history of trading financial instruments. Securities are typically traded in 2 ways:

  • Parties trade securities directly with each other through dealer networks referred to as Over The Counter (OTC)
  • Parties trade securities via a centralised exchange such as the London Stock Exchange


Technological advancements have revolutionised the business of trading financial instruments. Previously, trades were conducted over the telephone. For example, Mr Smith calls his broker requesting 1000 shares in Barclays. The broker would then go to market on behalf of Mr Smith to fulfill the order. This whole process could take minutes, hours or even days to complete. The arrival of electronic trading has seen the platform for trading shift to computers. Now, at the click of a button, stocks, currency, bonds, e.t.c can be bought and sold within a matter of seconds.

One second is a very long time in the world of HFT. HFT is conducted in even smaller units of time – microseconds and milliseconds. Some of this speed advantage can be attributed to ‘Colocation’. This is the situation of a company’s IT infrastructure in close proximity to that of the Exchange via whom it is trading. Consequently, information is received quicker as the information has a smaller distance to travel. To most people, this speed advantage (which works out to fractions of seconds) is negligible but this translates to a considerable advantage for HFT. The search for this speed has seen people go to great lengths. At first, most participants wanted their machines closest to the Exchange’s main terminal then once the exchanges realised what was happening they decided to level the playing field by issuing everyone with the same length of cable connecting to their terminal. The race for speed then led to the real estate around the major exchanges swiftly being gobbled up with premiums sky rocketing. Michael Lewis, the author of the book Flash Boys, describes within it a situation where one firm has gone as far as blowing up a mountain in the US in the hope of creating their own shortened fibre optic network and bypassing the conventional network. This firm was then able to charge a premium for what was essentially a ‘fast lane’ for trading.

It is no wonder that computer science graduates are now more sought after than ever by finance companies. These Quantitative traders or ‘Quants’ as they are known as colloquially are employed by the investment banks, hedge funds e.t.c to build the algorithms for High Frequency Trading. Algorithms are sets of instructions programmed into software. Estimates put human generated trades at 16% of the overall trading activity with the rest being automated. The programmes tend to be completely independent and capable of processing numerous transactions simultaneously.

The speed and ability to execute trades a split second quicker than others is of no use without a strategy. The strategies that have become synonymous with HFT are arguably the most controversial strategies in the business. One of these strategies is called Spoofing. Spoofing is the placing and instantaneous cancelling of orders in an attempt to misrepresent the interest in a particular security and manipulate its value. The spoofer is then able to capitalise on the false activity as other algorithms are fooled into thinking there is genuine interest in a particular security. Another controversial HFT strategy is ‘Quote Stuffing’. Quote stuffing involves an algorithm generating numerous orders in an attempt to flood the market with information. This rush of information is designed to slow down other competing algorithms.

One of the most surreal moments was in 2014 when the New York Stock Exchange trading floor was almost brought to a halt due to the raging debate between people in support and against high frequency trading and its wider implication or indication of the market being rigged. Proponents argue that HFT is a valuable source of liquidity. A market is said to be liquid when any order placed can be fulfilled within a relatively short period of time i.e an ideal trading environment. The high frequency traders themselves often argue that they guarantee there is someone else on the other side of a trade.

Those against this form of trading point to the May 2010 ‘Flash Crash’ as an example of the side effects of HFT. HFT is also said to impose an implicit transaction tax because most trades are interposed with HFT trades. It is also worth remembering that the algorithms are designed by humans; consequently, they are not always error free. The problems arising from a malfunctioning algorithm are further complicated by the speed at which HFT transactions are carried out. Naturally, by the time a human spots an error the damage is already magnified by other algorithms reacting to the ‘bad’ algorithm.

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