In the era of machine learning, algorithms are tending to replace traders in the financial markets. Indeed, stock market players increasingly favor computer systems to place and execute orders. With high frequency trading, they have even removed the human factor from scalping. Transactions are thus carried out very quickly and automatically by dedicated software.
What is High Frequency Trading?
the high frequency trading is a practice of executing high-speed financial transactions through algorithms. It is therefore an automated and optimized form of scalping. The speed of transactions is of the order of ten milliseconds, or even a hundred microseconds (0.1 ms). This method is also called nano trading or high-frequency trading (HFT).
Like the scalper, the high-frequency trader multiplies transactions over a short period of time to obtain capital gains. It relies mainly on the tiny fluctuation of prices over the period considered. Thus, incomes are generally low. The operator nevertheless counts on the volume of operations carried out to earn more. Besides, its tools can handle a huge amount of orders.
The traders in THF can execute transactions on all marketplaces, whether over-the-counter or regulated. They dominated the US stock market as early as 2005 before expanding internationally. In 2011, they carried out 40% of transactions on European exchanges. According to brokers, THF now accounts for 80% of transactions on global stock exchanges.
Most often, high frequency traders are companies like online brokers. It is indeed necessary to invest in a powerful computer system to have a powerful trading robot on the international stock markets. In addition, many experts are needed to optimize the speed and efficiency of algorithmic trading (programmers, analysts, network engineers, etc.).
How it works ?
In THF, the basic idea is to rely on speed to outclass the competition and make profit. Speed is decisive in detecting and then exploiting opportunities appearing on global markets. However, the trader must use high-performance computers and robots to react very quickly to stock prices. It will thus be able to automatically launch the most profitable scenarios.
This system makes it possible, for example, to buy shares massively in a few milliseconds when faced with a slight uptrend. An equally rapid resale will then offer gains to the operator concerned. Widespread, this strategy relies on flash orders to get ahead of other market players. It is especially lucrative when the trader has information a little before his competitors.
However, THF is often criticized for exploiting the slight lag between the issuance and execution of orders by market makers. Indeed, the order books are private before being communicated on Euronext, Dow Jones, Nasdaq, etc. High-frequency traders therefore take advantage of the opportunity to make trades, sometimes ahead of the initial order issuers.
On the other hand, theTHF algorithm covers several missions, apart from the analysis and execution of orders. It can also perform global monitoring of stock market fluctuations in the background. This observation will ultimately make it possible to design a complex strategy to influence stock market prices. This controlled situation will therefore facilitate the execution of flash transactions by the THF robot.
How to do high frequency trading?
Given the funds and equipment required, high-frequency trading is mostly practiced by large companies. These entities are also able to install IT infrastructures as close as possible to financial centers such as Wall Street, Frankfurt, Hong Kong, Tokyo, etc.
With these facilities, transactions are less affected by latency due to computer networks. Today, many operators even have servers located within the main world stock exchanges. They thus improve their responsiveness and their access to information on the various global financial markets.
For make THF, traders on their own account can in particular contact players offering open systems. The independent operator may in this case use the servers present on site to deploy its own algorithms. In addition, the market now includes a wide variety of PaaS (platform as a service) and IaaS (infrastructure as a service).
Finally, individuals can also turn to a trading platform providing a wide range of technical tools. High frequency trading will this time be aligned with traditional financial techniques and products. Additionally, traders often have training and a demo account to master these complex systems.