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Using high-frequency trading in the UK

In the UK, several different market participants use high-frequency trading (HFT), including brokers, asset managers, and traders.

The benefits of using HFT include:

  • Improved liquidity
  • Faster order execution
  • Increased transparency

Brokers use HFT to increase the liquidity of the markets they operate. By providing a more significant number of orders at lower prices, they can improve the market’s overall efficiency and ensure that investors can buy and sell assets quickly and at a reasonable cost.

For brokers specialized in HFT, visit Saxo capital markets.

Asset managers also use HFT to improve the liquidity of the markets in which they invest. By placing orders at a range of different prices, they can ensure that they can buy and sell assets quickly and at a reasonable price. This helps to minimize the costs associated with investing and ensures that they can take advantage of market opportunities when they arise.

Traders also use HFT to improve their trading performance. By using algorithms to trade at high speeds, they can maximize their profits by taking advantage of small price movements. This can be achieved by buying or selling assets very quickly in response to changes in the market.

Overall, HFT is a successful tool for market participants in the UK. It has helped to improve liquidity, increase transparency and improve the overall efficiency of the markets. As a result, it is likely to play an essential role in the UK economy for many years to come.

What is HFT?

High-frequency trading (HFT) uses very sophisticated computer programs to trade financial instruments, typically by exploiting minor price changes rapidly. These computers can buy and sell thousands of orders per second, thus “snapping up profit opportunities more quickly than human traders can.”

HFT in the financial market

In 2008, author Michael Lewis wrote about HFT in his book “Flash Boys”. It revealed that financial markets were rigged to benefit large banks and hedge funds through speed advantages given to high-frequency firms. This lets them see your buy or sell orders before they get filled. They exploit this weakness by ensuring a place in stock exchanges’ order queues ahead of anyone else, resulting in faster trades that are more likely to be profitable.

Since the 2008 financial crisis, increasing calls for action to protect ordinary investors and prevent market rigging. In 2010, US Senator Charles Schumer argued that HFT is “a bad thing” and is pushing for a ban on Algorithmic Trading, which includes: “programs whose purpose is entering orders onto an exchange, managing those orders and then removing them once they have been filled.”

In 2011, he also called for the SIP (Securities Information Processor) to delay trades by high-frequency traders until human oversight can determine whether or not it is appropriate. Since then, the EU has passed stricter regulations against such trading methods.

However, despite these efforts, a 2013 study from the University of Michigan entitled “High-Frequency Trading and Price Discovery” suggested that HFT positively impacts market quality. Its findings state that increased liquidity, lower spreads and better availability of capital caused by high-frequency trading benefit small and large-cap stocks.

However, the US Government Accountability Office is currently reviewing whether or not such activities are harming investors. Furthermore, they have announced their intention to introduce new rules for computerized traders to prevent instances of insider trading.

In conclusion

Algorithmic trading has become an essential tool in modern finance, allowing firms to make carefully calculated decisions when executing financial transactions. They have been designed to minimize the room for human error associated with manual efforts whilst simultaneously maximizing profits. However, it is essential to be aware of the algorithmic trading tools used by high-frequency traders before investing in financial markets. This knowledge will allow you to make more informed investment decisions.

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