Report ID:
SQMIG45J2244 |
Region:
Global |
Published Date: November, 2024
Pages:
186
|Tables:
0
|Figures:
0
Global Algorithmic Trading Market size was valued at USD 2.19 Billion in 2022 and is poised to grow from USD 2.36 Billion in 2023 to USD 3.76 Billion by 2031, growing at a CAGR of 7% in the forecast period (2024-2031).
The growth of the algorithmic trading market share has been driven by the use of artificial intelligence and machine learning technology in algorithmic trading systems. Through their use, the algorithmic trader may produce complex algorithms able to evaluate abundantly and instantly a vast volume of data find trends and make predictions more rapidly than he possibly could with conventional techniques. Not only do AI and ML accelerate trading techniques by providing adaptive learning—algorithms that improve over time based on past performance and changes in the market condition, but also high-frequency trading, or HFT, is another significant growth driver for the industry. HFT firms process thousands of orders at lightning speed, often in milliseconds, using complex algorithms. To this approach, small, fleeting price differences are added advantages because they enable traders to capitalize on miniscule price ripples. Ordinary traders are empowered to successfully apply algorithmic techniques due to access to easy-to-use platforms and teaching materials. This is so because individual investors can today utilize algorithms in the management of their portfolios and execution of transactions based on predetermined criteria. In this regard, this development leads to a rise in financial market involvement as there will be greater accessibility to these technologies that would spur market innovation and competitiveness. Businesses would invest much more in compliance algorithmic solutions as the laws are sure to change to keep up with these improvements in technology which in turn would boost the algorithmic trading market growth.
Global Market Size
Largest Segment
Fastest Growth
Growth Rate
CAGR
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The global algorithmic trading market is segmented into component, type, deployment mode, type of traders, and region. By component, the market is bifurcated into solution and services. Depending on type, it is classified into stock markets, FOREX, ETF, and Bonds. According to deployment mode, the market is divided into cloud and on-premises. As per the type of traders, it is categorized into institutional investors, long-term traders, short-term traders, and retail investors. Regionally, the market is analyzed across North America, Europe, Asia-Pacific, Middle East and Africa, and Latin America.
Analysis by Component
The solution segment had the highest share in 2023, standing at 85.83%. The market further specializes in two more categories, such as software tools and platforms. The algorithmic trading platform provides an effective manner for back-testing and research of trading techniques alongside a vast repository of free futures and equity data. The segment is anticipated to be led by the increasing demand for supplement trading techniques globally over the forecast period. In addition, the ever-increasing need for efficient portfolio management would open new potential prospects for the market. However, it is expected that the increasing use of algorithmic trading software tools to enable efficient trading executions to make money and identify better opportunities would drive the growth of the segment.
However, the services segment is anticipated to exhibit moderate growth during the forecast period. Two other segments of the services industry are professional services and managed services. The growth can be attributed to increased usage by end-users of professional services to ensure that trading solutions work correctly. Moreover, trading companies can automate or pass on a systematic trading method through professional services. Professional services specified through a set of rules enable traders to adapt any trading plan. Managed services, however, offer infrastructure management, maintenance, and support to investors and traders in order to help them develop trading strategies well. Most traders also employ managed services to both implement and monitor algorithmic trading systems effectively. In addition, managed services report real-time order execution infrastructure and trade data feed.
Analysis By Deployment Mode
The largest market segment in 2023 was the cloud. Global vendors are focusing on cloud-based algorithmic trading solutions, which will enhance revenues and execute a seamless and automated trade process for several traders. Along with these, the ensuing years will surely adopt cloud-based solutions more due to its benefits such as affordability, scalability, easy maintenance of trade data, and efficient administration. Besides, conventional traders, while trading, can do back-testing, time-series analysis, and test innovative methods using cloud-based tools. Compared to on-premises solutions, cloud-based solutions require less infrastructure and process data faster. In addition, it is also expected that with an increasing number of financial institutions adopting the use of cloud-based solutions to improve productivity and efficiency, this factor will also propel the growth of the cloud segment.
On the other hand, during the projection period, the on-premises segment is expected to grow moderately at 12.3%. A software application on the company's PCs is used for installation and operation on a customer's premises in an algorithmic trading solution. However, most financial institutions would like to have solutions installed on their premises because they have greater control over their trading environments and data protection, which enhances category growth. Apart from this, the architecture allows businesses to fine-tune their infrastructure and algorithms for specific trading tactics and legal restrictions to attain compliance and reduce the chance of data breaches.
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North America led the highest market share in the global algorithmic trading industry. Many players are competing within North American market, and it's also where the market will lead in the development and adoption of algorithmic trading solutions. The above factors have further boosted governmental support toward international trade and led to strong investments in trading technology. Availability of banks, larger technological advancements, and extensive usage of algorithm trading inside the financial houses will all contribute to the rise of the regional sector. One is the strong presence of institutional investors and hedge funds looking to up their trading efficiency that has, so far, ensured the US algorithmic trading industry led the market in 2023. The increasing dependence of approaches to trading on data analytics and machine learning also propels market growth.
Asia-Pacific is expected to grow significantly over the projection period following significant investments by both the public and commercial sectors to enhance their trading technology. This will increase demand for trading process automation solutions. In addition, growing usage of algorithmic trading technology by trading firms is opening profitable prospects for the major market participants. For instance, in May 2022, India-based online brokerage firm TradeSmart has collaborated with algo-trading platform KEEV which will help the traders to trade more accurately and effectively for increasing their return. This sector also has growing usage of cloud-based technology to drive the growth of regional markets.
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Drivers
Rise in Market Volatility
Technological Advancements Related to Data Analytics & ML
Restraints
Government Restrictions for Stable Market
Lack of Efficient Risk Evaluation Skills
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The algorithmic trading market leaders are focusing on providing industry-specific solutions in an attempt to expand their footprint geographically. For a strong regional grasp, such players are partnering with and acquiring local players. They will enjoy increased revenue margins if they can attract a large base of consumers through innovations and new product launches. To sustain and expand their market share, these companies are banking on the production of innovative solutions and efficient marketing strategies. International trade is also expected to increase the prospects of the market players due to their more profanity chances. Furthermore, driven by competition, the companies are focusing on different strategic moves such as alliances, and acquisitions with mergers.
Top Player’s Company Profile
Recent Developments
SkyQuest’s ABIRAW (Advanced Business Intelligence, Research & Analysis Wing) is our Business Information Services team that Collects, Collates, Correlates, and Analyses the Data collected by means of Primary Exploratory Research backed by robust Secondary Desk research.
As per SkyQuest analysis, AI and increasing market volatility along with technological innovation in the algorithmic trading market are driving rapid growth. Retail algorithmic trading, cloud computing, and innovations based on the same principles are democratizing access into sophisticated trading tactics, hence opening this market for a wider spectrum of participants; however, issues related to technical hazards and regulatory compliance continue to exist. Trading methods are changing due to developments as it adapts, among other developments, by using alternative data sources and giving prominence to ESG issues. To begin with, the future of the algorithmic trading market looks brighter than promising as this future generation will continue innovating that will increase efficiency in financial markets and decision-making.
Report Metric | Details |
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Market size value in 2022 | USD 2.19 Billion |
Market size value in 2031 | USD 3.76 Billion |
Growth Rate | 7% |
Base year | 2023 |
Forecast period | (2024-2031) |
Forecast Unit (Value) | USD Billion |
Segments covered |
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Regions covered | North America (US, Canada), Europe (Germany, France, United Kingdom, Italy, Spain, Rest of Europe), Asia Pacific (China, India, Japan, Rest of Asia-Pacific), Latin America (Brazil, Rest of Latin America), Middle East & Africa (South Africa, GCC Countries, Rest of MEA) |
Companies covered |
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Customization scope | Free report customization with purchase. Customization includes:-
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Executive Summary
Market overview
Parent Market Analysis
Market overview
Market size
KEY MARKET INSIGHTS
COVID IMPACT
MARKET DYNAMICS & OUTLOOK
Market Size by Region
KEY COMPANY PROFILES
For the Algorithmic Trading Market, our research methodology involved a mixture of primary and secondary data sources. Key steps involved in the research process are listed below:
1. Information Procurement: This stage involved the procurement of Market data or related information via primary and secondary sources. The various secondary sources used included various company websites, annual reports, trade databases, and paid databases such as Hoover's, Bloomberg Business, Factiva, and Avention. Our team did 45 primary interactions Globally which included several stakeholders such as manufacturers, customers, key opinion leaders, etc. Overall, information procurement was one of the most extensive stages in our research process.
2. Information Analysis: This step involved triangulation of data through bottom-up and top-down approaches to estimate and validate the total size and future estimate of the Algorithmic Trading Market.
3. Report Formulation: The final step entailed the placement of data points in appropriate Market spaces in an attempt to deduce viable conclusions.
4. Validation & Publishing: Validation is the most important step in the process. Validation & re-validation via an intricately designed process helped us finalize data points to be used for final calculations. The final Market estimates and forecasts were then aligned and sent to our panel of industry experts for validation of data. Once the validation was done the report was sent to our Quality Assurance team to ensure adherence to style guides, consistency & design.
Customization Options
With the given market data, our dedicated team of analysts can offer you the following customization options are available for the Algorithmic Trading Market:
Product Analysis: Product matrix, which offers a detailed comparison of the product portfolio of companies.
Regional Analysis: Further analysis of the Algorithmic Trading Market for additional countries.
Competitive Analysis: Detailed analysis and profiling of additional Market players & comparative analysis of competitive products.
Go to Market Strategy: Find the high-growth channels to invest your marketing efforts and increase your customer base.
Innovation Mapping: Identify racial solutions and innovation, connected to deep ecosystems of innovators, start-ups, academics, and strategic partners.
Category Intelligence: Customized intelligence that is relevant to their supply Markets will enable them to make smarter sourcing decisions and improve their category management.
Public Company Transcript Analysis: To improve the investment performance by generating new alpha and making better-informed decisions.
Social Media Listening: To analyze the conversations and trends happening not just around your brand, but around your industry as a whole, and use those insights to make better Marketing decisions.
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Report ID: SQMIG45J2244
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