Algorithmic Trading Market Size (2024)

It is anticipated that the development of artificial intelligence, machine learning, and large amounts of data in the financial services sector will be major factors contributing to the expansion of the global algorithmic trading market.

Covid-19 Impact and Market Status

COVID-19 was a blessing to the algorithmic trading market. This is because of the greater move toward algorithmic trading, which enables decision-making to occur at an extremely rapid pace while simultaneously minimizing the number of human errors. For instance, the Reserve Bank of Australia indicated in a recent article that the Covid-19 outbreak may have merely furthered the transition toward computerized trading in the business. Additionally, High-Frequency Traders (HFT) are experiencing a boom in popularity during the epidemic, which is contributing to the expansion of the market.

Solution Segment Will Dominate The Algorithmic Trading Market

In 2020, the solution category saw the highest growth in terms of market share for algorithmic trading, and it is anticipated that this segment will continue to maintain its dominant position in the years to come. The benefits of algorithmic trading, such as lower transaction costs due to the absence of human participation and immediate trade order placement that is both accurate and precise, are the primary factor driving the demand for algorithmic trading solutions. In addition, market participants are developing sophisticated algorithmic trading systems to cater to the many different requirements of their consumers.

North America Will Dominate The Algorithmic Trading Market

The market for algorithmic trading is dominated by North America for a variety of reasons, the most important of which are the massive investments made in trading technologies and the increase in government backing for international trade. The widespread presence of algorithmic trading vendor companies in the region is another factor that is driving the expansion of the market.

The public and private sectors are making significant investments to improve their trading technologies, which is driving demand for algorithmic trading solutions to automate trading processes. As a result of these investments, it is anticipated that experience a steady growth rate over the course of the forecast period.

Furthermore, advancements in technology, regulators are also beginning to pay attention to the different ways in which individuals interact with the market. Some of the most important financial institutions in the world have recently begun to implement such technology in order to advance algorithmic trading.

The expansion of the worldwide algorithmic trading business is primarily being driven by causes such as an increase in demand for trustworthy, quick, and efficient order execution; the advent of favourable government rules; and the requirement for market surveillance. The need for algorithmic trading is also fuelled by the growing interest in minimizing the expenses associated with conducting trades.

Nevertheless, inadequate risk valuation capabilities have the potential to impede the expansion of the market to some degree. On the other hand, throughout the forecast period, the advent of AI and algorithmics in the financial services sector is anticipated to present the market with a number of attractive chances for expansion.

In addition, throughout the time of forecast, there is predicted to be an increase in demand for cloud-based solutions, which is anticipated to be advantageous for the growth of the algorithmic trading market.

The global algorithmic trading market is expected to increase to $31,500 million by 2029, showing a compound annual growth rate (CAGR) of 12.8% from 2022 to 2029.

Automated or algorithmic trading is a type of trading in which a computer program follows a prearranged set of rules to make trades on the market. These instructions or rules may include the buying or selling of an asset in relation to the fluctuating market data. Timing, quantity, pricing, or any other type of mathematical model may serve as the foundation for the established sets of instructions or rules.

The vast majority of companies that sell algorithmic trading software also provide cloud-based trading solutions, which allow users to maximize their earnings while also efficiently automating the trading process. This is mostly due to the numerous advantages offered by these solutions, including simple trade data maintenance, cost-efficiency, scalability, and efficient management.

Technical indicators, including moving average crossovers, channel breakouts, and price level variations, are the primary emphasis of most algorithmic trading strategies. These are the techniques that may be applied using algorithmic trading in the simplest and most direct way possible because they do not require making any predictions or price forecasts. Profitable trends are used to trigger trades, and these algorithmics are easy to implement without delving into the complexity of predictive research.

Computer software and the financial markets are brought together in the process of algorithmic trading, which enables trades to be opened and closed based on predetermined lines of code. They also have the ability to engage in high-frequency trading by utilizing processing power. The widespread use of algorithmic trading in today's financial markets can be attributed to the numerous trading methods that can be implemented. To get started, you should equip yourself with computer hardware, programming knowledge, and previous experience in the financial market.

There has been a discernible rise in the percentage of tasks that are now carried out electronically and automatically. The number of people working at buy-side and sell-side desks, as well as commissions and fees, declined during the epidemic. Because of the rise in volatility, there has been a corresponding rise in demand for algorithmic trading solutions and services that can manage the surge.

The leading companies in the global algorithmic trading market are Tata Consulting Services, uTrade, Tethys, Automated Trading SoftTech, QuantCore Capital Management, Argo SE, Meta Quotes Software, Kuberre Systems, Thomson Reuters, InfoReach, Software AG, Vela, 63 moons, iRage Capital, Trading Technologies, Virtu Financial, Symphony Fintech, and Algo Trader among others.

Recent Developments in Global Algorithmic Trading Market: A Snapshot

• It was announced in April 2021 by the management of the prominent investment bank JP Morgan that the growth in the algorithmic trading of fixed income futures accelerated rapidly in 2020. This was due to the fact that buy-side traders increasingly turned to the company's machine-learning-equipped algorithmic in order to deal with the intense volatility of the market.
• For example, in September of 2019, BNP Paribas released an improved foreign exchange trading platform that featured real-time analytics as well as interactive algorithmics. On the other hand, it is anticipated that the services sector will experience the highest growth. This is due to the widespread acceptance of professional services among end users, which is important since it assures the efficient operation of algorithmic trading solutions throughout the process.

Algorithmic Trading Market Scope

Key Segments in ‘Global Algorithmic Trading Market’

Type Overview (USD Million)

• Solutions type
• Services type

End-User Overview (USD Million)

• SMEs
• Large Enterprises

Application Overview (USD Million)

• Bonds
• FOREX
• Cryptos
• ETF
• Others

Regional Overview (USD Million)

North America

• U.S
• Canada

Europe

• Germany
• France
• UK
• Rest of Europe

Asia Pacific

• China
• India
• Japan
• Rest of Asia Pacific

South America

• Mexico
• Brazil
• Rest of South America

Middle East and South Africa