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The global algorithm trading market is set to reach US$ 44.4 BN by 2032, at a 11.9% CAGR between years 2022-2032. Algorithm trading, also called algo trading or computer-based buying and selling of stocks has changed how financial markets work. It's opened a new time of fast efficiency in these areas. The way algorithm trading works in the market is complex and various. It's created by a mix of better tech, changes to rules, and always wanting more money. The core of robot trading is using difficult computer programs and algorithms to make trades fast and right. These systems study a lot of market information quickly, finding patterns and chances that regular traders might not notice.
This fast-breaking study helps traders use quick decisions from computer programs. They take advantage of small rough edges in the market and different values for things like stocks, bonds or real estate up to a second speedy split. A big reason for the growth of algorithm trading is that technology keeps changing. As computer skills have improved, thinking methods called algorithms are getting better. This lets traders make detailed and smart plans for trading stuff like stocks. High-frequency trading (HFT) is a big example where computer programs do many orders very fast. This has caused a major rise in the amount of buying and selling, along with cash flow, within financial markets.
Rules and laws also have a big impact on how the market for algorithm trading works. Governments and money groups around the world have made rules to fix problems with market control, fairness in trading, and big risks linked to computerized buying or selling stocks. Regulators always have the task of finding a good balance between supporting new ideas and keeping market honesty in check. The rules for managing trading are important because they affect how computer-driven strategies grow and become more used. People in the market must change to follow new laws or guides as time goes on.
The way that markets work is also affected by more and more use of machine learning and artificial intelligence in trading strategies. These tools let algorithms gain knowledge from past data and adjust to market changes. Machine learning can find small patterns and connections that might not be clear in normal study, making the guessing powers of trading system algorithms better.
Covered Aspects:
| Report Attribute/Metric | Details |
|---|---|
| Segment Outlook | Component, Deployment, Type, Type of Trader, and Organization SizeGeographies CoveredEurope, North America, Asia-Pacific, Middle East & Africa, and South AmericaCountries CoveredThomson Reuters (US) 63 moons (India) InfoReach (US) Argo SE (US) MetaQuotes Software (Cyprus) Automated Trading SoftTech (India) Tethys (US) Trading Technologies (US) trade (India) Tata Consulting Services (India) Vela (US) Virtu Financial (US) Symphony Fintech (India) Kuberre Systems (US) iRageCapital (India) Software AG (Germany) QuantCore Capital Management (China) ALGOTRADES - Automated Algorithmic Trading System (US).Key Market OpportunitiesRapid Adoption of AI in Financial Services.Key Market DriversIt is believed that the rise in the use of automated trading software. |
Algorithm Trading Market Highlights:
Algorithm Trading Market Overview
According to the latest research report, it was estimated that the Algorithm Trading Market size was worth USD 10.3 billion in the year 2019, and it is projected to grow at a compound annual growth rate of CAGR of 11.9% during the forecast timeframe, reaching USD 44.4 billion by the end of the year 2032. A form of trading known as algorithmic trading is a form of dealing that involves the use of software programs to create and perform a wide range of data set transactions in the financial sector. A variety of major banks, dealers, and large investors contribute to the development of the set of data orders. A significant role in the share market is played by the data set, wherein each and every statistic is evaluated and used to benefit all parties involved. This further enables the investors to discover liquidity possibilities, which in turn helps them to make more informed trading choices. Because of these choices, it is possible to reduce transaction costs while also improving control over trading processes, reducing market volatility, and increasing profit potential.
Cloud computing has become much more important in the financial industry, as digitalization is becoming heavily reliant on it. The majority of financial institutions are now using cloud-based trading, which is accessible from a variety of platforms, including desktop computers and mobile devices. software-as-a-service solutions, for example, enable end-users to keep data while also providing access to data via mobile devices. Flexibility and availability are two characteristics of cloud-based algorithmic trading that are anticipated to propel the development of an algorithm trading software market in the upcoming years. Aside from that, the incorporation of automation and artificial intelligence into algorithm trading platforms is expected to further fuel development in the algorithm trading market over the projected period.
This report contains all the information about Algorithms Market overview and highlights. The report also contains the culmination of dynamics, segmentation, key players, regional analysis, and other important factors. And a detailed analysis of the global Algorithm Trading Market forecast for 2024 is also included in the report.
Figure 1: Algorithm Trading Market Size, 2022-2030 (USD Billion)
Source: Secondary Research, Primary Research, and Analyst Review
Algorithm Trading Market Opportunity
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Growing adoption of Cloud
Cloud computing has become much more important in the financial industry, as digitalization is becoming heavily reliant on it. The majority of financial institutions are now using cloud-based trading, which is accessible from a variety of platforms, including desktop computers and mobile devices. software-as-a-service solutions, for example, enable end- users to keep data while also providing access to data via mobile devices. Flexibility and availability are two characteristics of cloud-based algorithmic trading that are anticipated to propel the development of an algorithm trading software market in the upcoming years. Aside from that, the incorporation of automation and artificial intelligence into algorithm trading platforms is expected to further fuel development in the algorithm trading market over the projected period.
Algorithm Trading Market COVID-19 Impact Analysis
The COVID-19 outbreak has had little impact on the growth of the algorithmic trading market. The adoption of algorithmic trading solutions has increased in the face of unprecedented circumstances. The COVID-19 pandemic has significantly fueled the growth rate of the algorithmic trading market, owing to the increased shift toward algo trading for taking decisions at a very rapid pace by reducing human errors. For example, the Reserve Bank of Australia, in its recent publication stated that they may have only furthered the industry's shift toward electronic trading.
Market Dynamics
Market growth for algorithmic trading is primarily driven by demand for reliable, fast, and effective order execution; the emergence of favorable regulatory policies; and requirements for market monitoring. However, shortcomings in risk valuation may slow down the industry growth to some extent. On the other hand, the emergence of Artificial Intelligence and algorithms in financial services provides an opportunity for development during the forecast period.
Market Drivers
- Increasing demand for efficient Algorithmic Trading
Algorithmic trading is rapidly being used by big brokerage houses as well as institutional investors to cut down on costs associated with trading. This rapid use is attributed to the fact that algorithmic trading makes it easier and faster to
execute orders, making it attractive for exchanges. In addition, it enables traders and investors to quickly book profits off small changes in price. Therefore, the rise in demand for effective trade drives the growth of the algorithmic trading market, as it enables users to quickly execute trades.
Restraint
- Strict regulations and low acceptance across many countries
Regulatory authorities across the world have been tightening their grip on the use of algorithmic trading in the financial sector to make sure that their market is secure and beneficial for the clients. With the increase in the adoption of automated systems to conduct trading activities, there is a greater need for regulators to step in and check for potential loopholes that could be exploited via the system. If a market will be technologically advanced, there will be a greater need for advanced risk management solutions as well, which is a necessity for the market to grow.
Challenges
Lack of knowledge, a high level of technical skill, a lack of transparency, and the absence of a common benchmark are all anticipated to create challenges for the major key players in the worldwide algorithm trading market.
Cumulative Growth Analysis
This solution segment is anticipated to retain its dominance in algorithms trading in the future years as the segment with the greatest increase in market share for solution providers continues to expand. The need for algorithmic trading technologies is primarily driven by the advantages they provide, such as lower fees owing to the absence of human involvement and the ability to issue trade orders in real-time and with pinpoint accuracy. In furthermore, market participants are developing sophisticated algorithmic trading solutions to meet the requirements of a diverse range of clients.
Value Chain Analysis
According to the reports, It has been determined that the global algorithm trading market is divided into four categories: component, trading type, deployment method, organization size, and area. The worldwide algorithm trading market has been segmented into two categories based on its component: solutions and services. The solution sector was further subdivided into two categories: platform and software tool. Among the services segments, business solutions and managed services have been identified as the most significant growth areas. According to the kind of trading, the market has been divided into the following categories: foreign exchange markets, stock markets, exchange-traded funds, bonds, and cryptocurrencies.
The worldwide algorithm trading market has been segmented into two categories based on the method of deployment: cloud and on-premise. The worldwide algorithm trading market has been divided into two categories based upon the size of the organization: big businesses and small and medium-sized enterprises.
Regional Analysis
By region, the global Algorithmic Trading market has been divided into North America, Europe, Asia-Pacific, and the Rest of the World. North America accounted for the largest market. Asia Pacific is projected to exhibit the highest CAGR during the review period.
Asia-Pacific Market
The Asia-Pacific region is expected to witness the most growth during the forecast period. The region is widely considered one of the most booming and upcoming regions in the world right now. There is a massive influx of foreign investment in many countries into sectors such as real estate and technology, but especially technology - and it is no surprise that algorithmic trading will see a boom and progress here due to this high standard of investments available.
North America Market
North America dominates the market on all fronts when it comes to trading and investing. The region has a lot of money to invest in new technologies and tools, which means a lot of people have money to use when they're gambling online or making asset purchases; and a government that backs them up with copious funds. In addition, there are many agencies based here, that have access to limited amounts of personal data making it easier for them to funnel funds into their own businesses and thus enabling them to grow at an even faster rate than usual.
Competitive Landscape
The market comprises tier-1, tier-2, and local players. The tier-1 and tier-2 players have presence across the globe with diverse product portfolios. Companies such as Thomson Reuters (US), 63 moons (India), Virtu Financial (US), and Software AG (Germany), dominate the global algorithmic trading market due to product differentiation, financial stability, and strategic developments, and diversified regional presence. The players are focused on investing in research and development. Furthermore, they adopt strategic growth initiatives, such as expansion, product launches, joint ventures, and partnerships, to strengthen their market position and capture a large customer base.
Key Companies in the Algorithm Trading Market include
- Thomson Reuters (US)
- 63 moons (India)
- Argo SE (US)
- MetaQuotes Software (Cyprus)
- Automated Trading SoftTech (India)
- Tethys (US)
- Trading Technologies (US)
- Tata Consulting Services (India)
- Vela (US)
- Virtu Financial (US)
- Symphony Fintech (India)
- iRageCapital (India)
- Software AG (Germany)
- QuantCore Capital Management (China)
- ALGOTRADES - Automated Algorithmic Trading System (US)
- Jump Trading LLC
- Refinitiv Ltd
- Others
Recent Developments
Avenix Fzco, a leader in financial trading technology, announced the release of its newest product, the Trendonex EA, in May 2024. This is a revolutionary forex trading solution that will improve trend identification and trade entry accuracy with its sophisticated algorithm. Forex market data analysis made possible by the Trendonex EA through advanced computational techniques helps traders to make better-informed decisions with more precision. This forex robot identifies promising trends earlier and more accurately than traditional methods, enabling users to capitalize on movements in the market.
According to John Spensieri, Stifel Head of U.S. Equity Trading, the Stifel Electronic Trading Team has developed a short-term momentum signal for intraday use that predicts price movements with high accuracy in March 2024. The signal is designed so that it can be used by all Stifel algorithms to reduce execution costs and enhance the spread capture regardless of their parent strategy. According to him, backtests and production showed consistently high levels of accuracy for this signal, while its duration is ticker-based and depends on quote stability.
MarketAxess Holdings Inc. (Nasdaq: MKTX), an operator of one of the leading electronic trading platforms for fixed-income securities, said it had entered into a definitive agreement to acquire Pragma as of August 2023; Pragma is a provider of quantitative trading technology specializing in algorithmic and analytical services across equities, FX amongst other fixed income instruments markets. These solutions have driven asset managers around the world, including hedge funds, broker-dealers, and bank exchanges, among others, using independent broker-neutral multi-asset trading from Pragma. Automated AI-driven multi-asset and mult-market execution solutions are offered by their algorithmic trading platform coupled with quantitative execution solutions for equities and FX clients. Last year alone, Pragma handled over $2 trillion worth of algorithmic order flow across more than 50 venues covering multiple asset classes.
In April 2023, FXALCHEMIST has launched an algorithm trading platform to transform retail investors' financial market approach. With the power of advanced machine learning algorithms and real-time data, the platform provides related trading technology previously used by institutional traders only.
In October 2022, Scotiabank in partnership with BestEx Research launched an algorithm trading platform in Canada. This platform is specifically developed for the Canadian Equities market. This collaboration fuels the market growth and offer growth opportunities for the market player.
In March 2022, Virtu Financial has entered a non-exclusive cooperation agreement with Arqaam Capital to deploy Virtu's global equity execution algorithms to clients in Middle-Eastern and North Africa (MENA) markets. Arqaam will provide market access and local expertise in MENA equity markets to Virtu clients, while Arqaam clients can leverage Virtu's trading algorithms to access global markets, including MENA.
Increased adoption of algo trading in Asia: Algorithmic trading revenues in Asia Pacific rose 34% in 2021 driven by rising demand in markets like South Korea, Taiwan, Singapore and India. Retail participation in algos is also increasing.
Launch of new crypto algos: With the growth in crypto markets, major quant funds like Two Sigma and WorldQuant have launched cryptocurrency trading algorithms. These algos leverage factors like social media sentiment, on-chain data etc.
Regulators mulling "kill switches": Financial regulators in US and Europe are exploring safeguards like kill switches to manage risks arising from algo trades executing all at once. These would allow stopping algos when markets become unstable.
Algos to adapt to rising rates: Quantitative hedge funds are tweaking their algorithms to trade effectively in a rising interest rates environment. This includes adjusting statistical arbitrage and high frequency strategies
Algorithm Trading Market Segments
By Solutions:
- Platforms
- Software Tools
By solutions segment, the algorithm trading market is segmented into platforms and software tools. Among this, the platform segment rules the market. The algorithm trading platform provides a wide range of equities and futures data for studying trading strategies or back-testing. With the growing retail investors and advanced technologies adoption of such solutions is multiplying. Thus, driving the segment growth.
Further, the demand for the software tools is expected to rise in coming years especially across investment banks and proprietary trading firms to execute multiple trades and identifying profitable opportunities in minimum time. Software tools include extensive trading systems supported by dedicated staff and advanced data centers, enhancing their trading capabilities significantly.
By Services:
- Professional Services
- Managed Services
By services, the market is bifurcated into professional services and managed services. The professional services segment is gaining traction. End-users are actively adopting professional services for ensuring seamless functioning of trading solutions throughout their operations. These services provide assistance and guidance to either automate end-users existing systematic trading strategies or migrate them. On the other hand, managed services are expected to project rapid growth rate during the forecast period. In managed services traders and investors get required support, maintenance, and infrastructure management to develop effective trading strategies with real time data.
By Deployment:
- Cloud
- On-premise
By deployment, the market is bifurcated into cloud and on-premises. The cloud-based platform is ruling the algorithm trading market, as financial firms are adopting cloud-based platforms for efficient trading automation and increased profit margins. Cloud-based solutions offers benefits such as scalability, cost-effectiveness, easy trade data maintenance, and efficient management, which further accelerates its demand across the globe. Also, clous-based platform enables traders to develop new strategies, back-testing and analysis, and conduct runtime series analysis. Hence, aforementioned factors drives the demand for the cloud-based platforms in coming years.
By Trading Type:
- Foreign Exchange (FOREX)
- Stock Markets
- Exchange-Traded Fund (ETF)
- Bonds
- Cryptocurrencies
- Others
By trading type, the algorithm trading market is divided into foreign exchange, stock markets, exchange-traded fund, bonds, cryptocurrencies, and others. The stock market is gaining traction, as with the growing awareness regarding the growth potential of stock market in terms of currency growth both for individuals as well as country. They offer financial and brokerage firms profit maximization and risk management advantages, encouraging widespread adoption of algorithmic trading solutions among traders and investors.
Cryptocurrencies are also gaining traction, however, due to fluctuations and volatility in rates, cryptocurrencies are witnessing comparatively less participation of individuals as compared to stock market specially across emerging economies. It is expected that in coming years the segment will witness growth.
By Enterprise Size:
- SMEs
- Large Enterprises
By trading type, the algorithm trading market is divided into SMEs and large enterprises. Large enterprises such as financial institutes, banks, credit unions, hedge funds, and others, utilize their currency either to invest in real state, securities, and other assets to increase the value of money over period of time. Algorithm trading supports in multiplying capital by providing strategy development support offering real time data analysis, back-testing, cut-down traders operational cost for the enterprises, and others services, which supports the individuals and institution to strategize efficiently. Owing to this the demand for the algorithm trading is multiplying from the large enterprises segment creating immense growth opportunities for the market.
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