到 2030 年的演算法交易市場預測：依類型、部署、組件、組織規模、最終用戶和地區進行的全球分析
Algorithmic Trading Market Forecasts to 2030 - Global Analysis By Type (Bonds, Cryptocurrencies, Exchange-Traded Fund and Other Types), Deployment, Component, Organization Size, End User and By Geography
根據 Stratistics MRC 的數據，2023 年全球演算法交易市場規模將達到 181.6 億美元，預計 2030 年將達到 429.9 億美元，預測期內年複合成長率為 13.1%。
根據華爾街資料顯示，演算法交易約占美國股票全部交易的 60-73%。根據 Select USA 的數據，美國金融市場是全球最大、流動性最強的市場。
COVID-19 的爆發為市場帶來了福音。這場流行病顯著加速了成長，因為人們已經轉向演算法交易，可以更快地做出決策，同時最大限度地減少人為錯誤。在 3 月向歐盟委員會提交的文件中，紐約證券交易所 (NYSE) 表示，由於新冠肺炎 (COVID-19) 在紐約大都會圈的傳播以及對員工安全的擔憂，將關閉其主要現貨交易場所。暫時關閉並轉向完全電子化交易。此外，在疫情期間，許多市場參與企業都實施了尖端的演算法交易解決方案，以應對不斷成長的交易量。
According to Stratistics MRC, the Global Algorithmic Trading Market is accounted for $18.16 billion in 2023 and is expected to reach $42.99 billion by 2030 growing at a CAGR of 13.1% during the forecast period. Algorithmic trading is the process of using computers created to follow a specific set of instructions for placing a trade in order to earn profits at a pace and frequency that are impractical for a human trader. Any algorithmic trading strategy needs to identify a profitable chance to boost profits or cut expenses. The algorithmic trading methods follow set rules and are based on price, timing, a mathematical model, and quantity. Algorithms are becoming more common in the world of online trading, and many large clients use these technologies. These mathematical formulas analyze each quote and trade executed on the stock market, search for potential liquidity sources, and use the information to execute profitable trades.
According to Wall Street data, algorithmic trading accounts for around 60-73% of the overall US equity trading. As per Select USA, the US financial markets are the largest and most liquid globally.
A significant market driver is the financial sector's growing focus on efficiency and cost-cutting. Traditional manual trading methods take a lot of time and are prone to error. On the other hand, algorithmic trading automates these procedures, resulting in faster execution and a lower risk of errors. Additionally, this automation makes it possible to handle large volumes of trade without correspondingly raising costs. Furthermore, the ability to process enormous amounts of data quickly and make trading decisions in nanoseconds improves market liquidity and reduces spreads. Algorithmic trading provides a competitive edge by minimizing transaction costs and maximizing profits through clever trading strategies, encouraging its adoption throughout the financial sector.
Algorithmic trading is more affordable in the long run if the customer intends to carry out several trade orders each day. However, the initial cost of building the infrastructure for algorithmic trading is high. For quick trade execution, algorithmic traders need the fastest computers possible. The high cost of these computers and the necessary hardware restricts the market's expansion.
Rapid technological advancements in computing power and data processing have had a significant impact on the industry's expansion. These developments have enabled the real-time execution of sophisticated mathematical models and algorithms. The availability of high-frequency trading platforms has significantly decreased latency, allowing traders to act quickly based on market conditions. The development of more sophisticated trading strategies that are adapted to particular market circumstances and personal investment goals has also been made possible by the widespread use of artificial intelligence and cloud computing. Additionally, the accessibility and ongoing development of these technologies have made algorithmic trading available to even smaller companies, thereby expanding the market and encouraging innovation.
Intraday algorithmic trading is risky, and without adequate controls, losses could grow quickly. Orders that violate risk management thresholds must be immediately rejected or canceled by investment companies. High-frequency trading (HFT) using algorithms raises issues, such as the potential to increase systemic risk. As a result, market growth during the forecast period may be hampered by algorithmic trading systems' insufficient risk valuation capabilities.
The COVID-19 pandemic benefited the market. Due to an increased shift toward algorithmic trading, which allows for quick decision-making while minimizing human error, the pandemic has significantly accelerated growth. The New York Stock Exchange (NYSE), in a filing with the Commission in March, stated that due to the spread of COVID-19 in the New York metropolitan area and its employee safety interests, it temporarily closed its main physical trading floor and switched to fully electronic trading. Additionally, during the pandemic, a number of market participants introduced cutting-edge algorithmic trading solutions to better cater to the increased trading volumes.
The stock markets segment is anticipated to register the largest market share. One of the most popular asset classes for trading a wide variety of securities in a safe, managed, and controlled environment is the stock market. Additionally, stock markets provide financial and brokerage firms with advantages like profit maximization and risk management. The advantages that stock markets provide are encouraging traders and investors to use algorithmic trading tools, which is growing the market.
Due to financial organizations' adoption of cloud-based applications to boost productivity and efficiency, the cloud segment is anticipated to grow at the highest CAGR during the forecast period. Additionally, cloud-based solutions are becoming more and more popular among traders as they guarantee efficient process automation, data upkeep, and cost-effective management. These elements contribute to the forecasted growth of cloud-based algorithmic trading software.
North America's market share is anticipated to be the largest during the forecast period. The North American market is made up of the United States and Canada. North America is expected to take the lead in the adoption and development of algorithmic trading solutions due to its sizable market and competitive industry. This is the result of significant government support for international trade and huge investments in trading technologies. Additionally, the expansion of the industry is aided by significant technological advancements and the widespread use of algorithmic trading in banks and financial institutions.
Over the forecast period, the highest CAGR is anticipated in Asia-Pacific. The significant investments made by the public and private sectors to improve their trading technologies are to blame for the regional growth, which has led to a rise in demand for algorithmic trading platforms. The amount of computerized trading has increased in the area. As a result, it is anticipated that algorithmic trading solutions will be adopted more widely in the area.
Some of the key players profiled in the Algorithmic Trading Market include: Algo Trader AG, Argo Software Engineering, InfoReach, Inc., Kuberre Systems, Inc., MetaQuotes Ltd., Refinitiv Ltd, Symphony, Tata Consultancy Services Limited, Thomson Reuters, Tradetron, VIRTU Finance Inc., Wyden and 63 Moons Technologies Limited.
In April 2023, Argo SE announces a new release of Argo Exchange Solution. A new release adds significant latency and scalability improvements. We have implemented of parallel and distributed transactions, federated risk management. There are significant improvements in IOI/RFQ workflow improvements and new reports.
In March 2023, Trading Technologies International Inc. announced the purchase of London-based AxeTrading by the company. With a significant expansion into full coverage of corporate, government, municipal, and emerging market bonds as well as over-the-counter (OTC) interest rate swaps, the acquisition significantly broadens TT's multi-asset capabilities and reinforces TT's dominant position in fixed income derivatives and U.S. Treasury securities.
In September 2022, Refinitiv, an LSEG Business and one of the world's largest providers of financial markets data and infrastructure, today announced a long-term strategic agreement with HDFC Bank, India's largest private sector bank, to support digital transformation and innovation programmes across the whole business in India. Under the multi-year agreement, comprehensive access to Refinitiv's data and products will enable HDFC Bank to realize new customer opportunities and fast-track its innovation agenda while reducing total cost.
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.