Global High-frequency Trading Market Research Report 2023-Competitive Analysis, Status and Outlook by Type, Downstream Industry, and Geography, Forecast to 2029

Global High-frequency Trading Market Research Report 2023-Competitive Analysis, Status and Outlook by Type, Downstream Industry, and Geography, Forecast to 2029

High-frequency trading (HFT) is an automated trading platform used by large investment banks, hedge funds and institutional investors. The strategy engages powerful computers and servers and the fastest connectivity technology to trade large numbers of orders at extremely high speeds. High-frequency trading uses algorithms to analyze trading data and execute trades in fractions of a second.

Market Overview:

The latest research study on the global High-frequency Trading market finds that the global High-frequency Trading market reached a value of USD 8522.41 million in 2022. It’s expected that the market will achieve USD 8045.62 million by 2028, exhibiting a CAGR of -0.95% during the forecast period.

High-frequency trading strategies are more reliable than other quantitative strategies:

The theoretical basis of high-frequency trading strategies is completely consistent with other quantitative trading strategies, which is the law of large numbers in probability statistics. But the reliability of high-frequency trading strategies is theoretically higher. No matter what kind of quantitative investment strategy, in general, the formation process of its strategy needs to go through statistical analysis within the sample, post-event verification outside the sample, and then carry out the actual operation. There are two basic assumptions for daring to conduct real trading operations. One is that through a large number of in-sample analyses, the strategy can gain profits with a high probability; the second is that it is expected that the winning frequency of real trading operations will converge to this probability. The frequency is used here, not the probability, because the opportunity given to the real test is very limited, and it may be a small sample test. From a statistical point of view, the basic condition of the samples required by the law of large numbers is independent and identical distribution, that is to say, if the sample distribution is more homogenous in the experimental process, the greater the possibility that the law of large numbers can be realized. Therefore, in the process of constructing a quantitative strategy, the primary problem that needs to be solved is data cleaning. Through the cleaning and screening of samples, noise data is eliminated, and a relatively independent and identically distributed sample space is obtained for modeling. Compared with quantitative stock selection, high-frequency trading has relatively fewer noise data in the sample, so from the perspective of model reliability, the quantitative model of high-frequency trading is relatively more reliable.

Advances in technologies such as computers and algorithms:

High-frequency trading has two cores, one is the running speed of the computer and the transmission speed of the trading network; the other is the trading strategy, which is carried out based on the quantitative mathematical model composed of dynamic mathematical formula + prior probability judgment + statistical reasoning, which can be carried out through software Automatic optimization algorithm. High-performance computing systems, new trading technologies, low-latency information middleware, and feed handlers reduce the execution time of trading instructions. The development of information technology has greatly increased the speed of transactions. The information delay is reduced from 1 second to the order of milliseconds and microseconds. Therefore, technological advancements are expected to drive the development of high-frequency trading.

Region Overview:

In 2021, the share of the High-frequency Trading market in United States stood at 46.72%.

Company Overview:

Virtu Financial, Citadel Securities, Optiver were the top 3 players in the High-frequency Trading market in 2022, taking up a market share of 50.11% together.

Segmentation Overview:

Among different product types, Cloud-Based segment is anticipated to contribute the largest market share in 2027.

Application Overview:

By application, the Investment Banks segment occupied the biggest share from 2017 to 2022.

Key Companies in the global High-frequency Trading market covered in Chapter 3:

Hudson River Trading
Jump Trading
IMC
Tower Research Capital
DRW Trading
Flow Traders
Citadel Securities
Optiver
RSJ Algorithmic Trading
Tradebot Systems
Virtu Financial
Two Sigma Securities
Quantlab Financial

In Chapter 4 and Chapter 14.2, on the basis of types, the High-frequency Trading market from 2018 to 2029 is primarily split into:

On-Premise
Cloud-Based

In Chapter 5 and Chapter 14.3, on the basis of Downstream Industry, the High-frequency Trading market from 2018 to 2029 covers:

Investment Banks
Funds
Personal Investors
Others

Geographically, the detailed analysis of consumption, revenue, market share and growth rate, historic and forecast (2018-2029) of the following regions are covered in Chapter 8 to Chapter 14:

North America (United States, Canada)
Europe (Germany, UK, France, Italy, Spain, Russia, Netherlands, Turkey, Switzerland, Sweden)
Asia Pacific (China, Japan, South Korea, Australia, India, Indonesia, Philippines, Malaysia)
Latin America (Brazil, Mexico, Argentina)
Middle East & Africa (Saudi Arabia, UAE, Egypt, South Africa)