Everything you must know about high-frequency trading

High-frequency trading (HFT) is a method of stock market trading in which the computerized system used by the trader places a large number of orders at extremely high speeds.

What exactly is high-frequency trading?

HFT describes any automated trading strategy and operates on algorithmic or pre-programmed rules in very basic terms. These trading strategies utilize sophisticated technology and powerful computers to complete transactions at rates never before possible in the financial markets we see today.

It would have been impossible for a machine to do this so quickly a few decades ago. Still, with the advent of ultra-fast internet speeds, fiber optic networks, immense computing power, advanced software applications, low-cost stock data feeds, and other advancements, HFT has become commonplace.

Pattern detection software and algorithmic AI

The fractional advantages and automated nature of HFT mean that. Many traders using pattern detection software and algorithmic AI can spot trade patterns and automatically place their orders. Colloquially, these trades are often referred to as “bots” or “fake people.”

This form of trading is controversial, with some parties claiming it is equivalent to insider dealing because it is near-instantaneous. At the same time, proponents argue that it provides liquidity for markets that would otherwise be lethargic.

Retail and institutional investors can use HFT, but it’s most commonly associated with the latter. Institutional traders often deal with numbers too big for human dealers or market makers to handle. It is estimated that currently, between 40% and 50% of all US equity trades are made by HFT firms.

What do you need to know about high-frequency trading?

The main goal of high-frequency trading is to gain an advantage over other participants in the financial markets through faster trade execution. It involves placing the mechanical trades directly into exchanges rather than routing them through traditional, slower-moving humans.

There are two primary types of high-frequency trading:

Market making, which tries to make money by placing bids and offers in the market for securities; and statistical arbitrage, which uses computer algorithms to detect pricing anomalies within securities across different markets. Market makers are also known as liquidity providers.

Optimal Execution is not possible with HFT

Because of the limited amount of information available to the trader, there will always be a time lag between when an order is placed and when it is filled. It means that sometimes you cannot get the best price for your trade.

HFT has Advantages vs. Other Traders

The way that most people trade stock means that they are subject to latency problems just like everyone else. Still, with HFT’s ability to cancel and modify orders exceptionally quickly, HFT traders can dance around these other players who can’t keep up with them, thus leveraging their superior technological advantage over traditional market participants.

HFT is subject to the Law of large numbers

As more and more people begin to use this method, it becomes harder for any individual trader to improve their average returns as the market will now be expecting those trades and thus move against them

The technology behind HFT has the power to disrupt the traditional face of finance

Researchers have claimed that high-frequency trading can predict how stocks will behave with 70% accuracy.

High-frequency trading benefits everyone

These factors create a fairer stock market by ensuring that big players don’t have unfair advantages over regular traders.

There are Downsides too

Some would argue that HFT creates volatility in the market by trading on order book imbalances. If these orders are large, this can distort prices and create whipsaws for regular traders.

Additionally

Some academics and institutional investors have criticized high-frequency trading in general for hurting market quality and creating an uneven playing field between large and small investors.

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