Fairfield Market Research Algorithmic Trading Market Share, Type, Outlook, Size 2023-2030

Algorithmic Trading Market

Global Industry Analysis, Size, Share, Growth, Trends, and Forecast 2023-2030 - By Product, Technology, Grade, Application, End-user, Region: (North America, Europe, Asia Pacific, Latin America and Middle East and Africa)

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Global algorithmic trading market is likely to exhibit a promising growth curve as far as the short-term outlook is considered. The report will uncover the insights into how the market growth will unfold in the next few years.

Algorithmic Trading Market Flourishes as Financial Services Sector Embraces Next-generation Technologies

It is projected that supportive governmental regulations, expanding demand for prompt, dependable, and effective order execution, rising demand for the algorithmic trading market surveillance, and reducing transaction costs would all contribute to the need for the algorithmic trading business. Algorithmic trading lowers the costs of bulk trading for large brokerage firms, and institutional investors. In addition, promising market expansion potential is projected due to the development of AI, and financial service algorithms. The market is expected to expand in response to increased demand for cloud-based solutions. The financial services sector has been embracing AI, ML, and big data technologies, which holds a significant influence on the market growth. Regulations now take into account how customers engage with the market as a result of technological advancements.

Over the past two years, there has been a trend toward more widespread deployment of algorithms across-asset classes, notably cross-asset automation. According to TRADE's January 2022 Algorithmic Trading Survey, hedge funds rapidly use algorithms to trade most of their portfolios. Hedge funds rely on a larger number of providers for a multi-asset portfolio. In order to meet the demand from hedge funds, algorithm providers are emphasizing multi-asset solutions. Some of the main factors influencing the employment of algos are improved trader productivity (10.32%), less market effect (10.45%), consistent execution performance (10.19%), the convenience of use (12.04%), and cheap commission rates (8.69%). Additionally, there has been a discernible increase in the general level of automation and electronification. In addition, the rise in the volatility of algorithmic trading market has increased demand for algorithmic trading services and products.

Algorithmic Trading Market: COVID-19 Impact

The COVID-19 pandemic is anticipated to benefit the market. Due to a greater trend toward algorithmic trading, which allows for quick decision-making while minimizing human mistakes, the pandemic has significantly accelerated growth. During the pandemic, several algorithmic trading market participants introduced cutting-edge algorithmic trading solutions to cater to the increasing trading volumes. For instance, Cowen Inc., an investment bank and provider of financial services, released an algorithmic trading solution in March 2022 to help institutional clients navigate the market dynamics brought on by a growth in retail trading volume.

Increased Adoption by Institutional Investors Fuels Algorithmic Trading Market Expansion

Institutional investors oversee a group or institution's accounts and act as their agents when buying and selling equities. Institutional investors include insurance firms, exchange-traded funds, pension funds, and mutual fund families. Large brokerage firms and institutional investors largely use algorithmic trading to reduce trading expenses. Algorithmic trading particularly benefits large order sizes. Additionally, in the algorithmic trading markets that drive the stock market, institutional investors regularly use a variety of computer-driven algorithmic strategies. Investors can minimize trading costs and raise their profitability by using these tactics. High-frequency trading is required by these investors, which is not always possible. Due to algorithmic trading, institutional investors can divide a large sum of money into smaller amounts while still carrying out their trading according to predefined time frames or methods. Instead of depositing 100,000 shares all at once, an algorithmic trading technique might push 1,000 shares out every 15 seconds and gradually place modest amounts into the market under study throughout the session or the full day. These methods reduce the likelihood of human error. It reacts to marketing conditions instantly, making it a sought-after investment choice. Thus, the market expansion may be attributable to all of these causes.

Government Regulations Complement Algorithmic Trading Market Growth

Government agencies worldwide are researching ways to manage algorithms and putting rules in place to protect algorithmic trading. To prevent the algorithmic trading market manipulation, the Financial Industry Regulatory Authority (FINRA) proposed a rule calling algorithmic trading developers to register as securities traders. The U.S. Securities and Exchange Commission (SEC) has accepted the rule. The Securities and Exchange Board of India (Sebi) unveiled a new order-to-trade ratio (OTR) framework in June 2020. Such legislative rules are anticipated to be advantageous for the algorithmic trading sector.

Stringent Restrictions, and Limited Acceptance Across Several Nations Challenge Algorithmic Trading Market

Regulatory bodies worldwide have been strengthening their control over algorithmic trading in the financial sector to ensure that their markets are safe and advantageous for customers. There is a greater need for regulators to intervene and look for potential systemic flaws as automated trading systems become more widely used. An advanced algorithmic trading market will also require more sophisticated risk management solutions, which is essential for the market to expand.

Stocks Market Category Dominates Algorithmic Trading Market as it Helps Financial and Brokerage Organizations

The stock market category held the largest algorithmic trading market share, and it is anticipated that it will continue to rule the market during the forecast period. The stock market is regarded as one of the top asset classes for trading a wide variety of assets in a safe, monitored, and controlled setting. Additionally, stock markets aid financial and brokerage organizations by maximizing profits and managing risks. The advantages of stock markets are encouraging investors and traders to use algorithmic trading solutions. Furthermore, it is anticipated that the cryptocurrency segment will increase significantly throughout the projected period. The increase in trading experts' interest in bitcoin trading contributes to category growth. Market data from any supported cryptocurrency exchanges can be processed in real time by traders using algorithmic trading systems. These solutions also support margin and exchange trading. The segment's expansion is anticipated to be fueled by the above causes.

Cloud Category Leads Algorithmic Trading Market due to its Cost Effectiveness

The cloud category dominated the algorithmic trading market in 2021. To generate the greatest returns and effectively automate the trading process, many worldwide vendors are concentrating on providing cloud-based algorithmic trading solutions. Additionally, it is projected that more people will use cloud-based solutions due to their advantages, including cost-effectiveness, scalability, simple trade data upkeep, and efficient management. Traditional traders can use cloud-based solutions to back-test trades, run-time analyze series, and test new trading strategies. Furthermore, compared to their conventional on-premise counterpart, cloud-based solutions require the least infrastructure and offer faster processing. However, financial institutions' growing use of cloud-based solutions to boost productivity and efficiency is anticipated to fuel the cloud category growth.

North America Spearheads Algorithmic Trading Market with Higher Investments in Trading Technologies

Over the forecast period, the North American market will account for the largest revenue share. The increasing investments in trading technologies (such as blockchain), the expanding presence of algorithmic trading suppliers, and the expanding government support for international trade will be the primary drivers of the algorithmic trading market expansion throughout the projection period. Wall Street data indicate that algorithmic trading makes up between 60% and 73% of all US equity trading. According to Select USA, the US financial markets are the biggest and most liquid in the world. Sentient Technologies, a US-based AI company that runs a hedge fund, has created an algorithm that examines millions of data points to spot trade patterns and forecast trends. Modern technology is fast changing the formats of traditional investment models by automating all related trade processes, enabling the creation of a safe and efficient environment that will be available to all prospective investors. The Dex Finance ecosystem was created in February 2022 by a group of programmers. By automating advanced trading strategies and encouraging investors to leave their deposits within the protocol, Dex Finance built a low-risk algorithmic trading model that virtually anybody can use.

The Asia Pacific algorithmic trading market is anticipated to experience stable revenue growth throughout the forecast period. The area is currently regarded as one of the most dynamic and developing in the world. Many nations are experiencing a massive influx of foreign investment into industries like real estate and technology, especially technology. Given the high caliber of available investments, it is not surprising that algorithmic trading will flourish and advance in these countries. The significant investments made by the public and private sectors to improve their trading technologies are to blame for the regional expansion, 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.

Global Algorithmic Trading Market: Competitive Landscape

In October 2022, to maintain a seamless trading experience, Multi Commodity Exchange of India Limited (MCX) teamed up with 63 Moons Technologies for software technology services for three months. Similarly, in June 2022, Fernhill Corp. announced that MainBloq, a cutting-edge digital asset trading platform used by banks and hedge funds, had signed a multi-year contract to provide smart order routing, automated algorithmic trading, and customized trading solutions to improve the overall trading performance for India-based CryptoWire.

A few of the players in the algorithmic trading market include 63 moons, Virtu Financial, Software AG, Refinitiv Ltd., Metaquotes Software Corp., Symphony Fintech Solutions Pvt Ltd, Argo SE, Tata Consultancy Services, and Algo Trader AG, Tethys.

Regional Classification of the Global Algorithmic Trading Market is Described Below:

North America

  • U.S.
  • Canada

Europe

  • Germany
  • France
  • Spain
  • U.K.
  • Italy
  • Russia
  • Rest of Europe

Asia Pacific

  • China
  • Japan
  • India
  • Southeast Asia
  • Rest of Asia Pacific

Latin America

  • Brazil
  • Mexico
  • Rest of Latin America

Middle East and Africa

  • GCC
  • South Africa
  • Rest of Middle East and Africa

1. Executive Summary
     1.1. Global Algorithmic Trading Market Snapshot
     1.2. Key Market Trends
     1.3. Future Projections
     1.4. Analyst Recommendations

2. Market Overview
     2.1. Market Definitions and Segmentations
     2.2. Market Dynamics
            2.2.1. Drivers
                    2.2.1.1. Driver A
                    2.2.1.2. Driver B
                    2.2.1.3. Driver C
            2.2.2. Restraints
                    2.2.2.1. Restraint 1
                    2.2.2.2. Restraint 2
            2.2.3. Market Opportunities Matrix
     2.3. Value Chain Analysis
     2.4. Porter’s Five Forces Analysis
     2.5. Covid-19 Impact Analysis
            2.5.1. Pre-Covid and Post-Covid Scenario
            2.5.2. Supply Impact
            2.5.3. Demand Impact
     2.6. Government Regulations
     2.7. Technology Landscape
     2.8. Economic Analysis
     2.9. PESTLE

3. Global Algorithmic Trading Market Outlook, 2018 - 2030
     3.1. Global Algorithmic Trading Market Outlook, by Trading Type, Value (US$ Mn), 2018 - 2030
            3.1.1. Key Highlights
                    3.1.1.1. Stock Market
                    3.1.1.2. FOREX
                    3.1.1.3. Bonds
                    3.1.1.4. Cryptocurrency
                    3.1.1.5. ETF
                    3.1.1.6. Misc.
     3.2. Global Algorithmic Trading Market Outlook, by Deployment, Value (US$ Mn), 2018 - 2030
            3.2.1. Key Highlights
                    3.2.1.1. Cloud
                    3.2.1.2. On-premises
     3.3. Global Algorithmic Trading Market Outlook, by End-users Type, Value (US$ Mn), 2018 - 2030
            3.3.1. Key Highlights
                    3.3.1.1. Retail Investors
                    3.3.1.2. Institutional Investors
                    3.3.1.3. Long-term Traders
                    3.3.1.4. Short-term Traders
            3.3.2. BPS/Market Attractiveness Analysis
     3.4. Global Algorithmic Trading Market Outlook, by Region, Value (US$ Mn), 2018 - 2030
            3.4.1. Key Highlights
                    3.4.1.1. North America
                    3.4.1.2. Europe
                    3.4.1.3. Asia Pacific
                    3.4.1.4. Latin America
                    3.4.1.5. Middle East & Africa
            3.4.2. BPS/Market Attractiveness Analysis

4. North America Algorithmic Trading Market Outlook, 2018 - 2030
     4.1. North America Algorithmic Trading Market Outlook, by Trading Type, Value (US$ Mn), 2018 - 2030
            4.1.1. Key Highlights
                    4.1.1.1. Stock Market
                    4.1.1.2. FOREX
                    4.1.1.3. Bonds
                    4.1.1.4. Cryptocurrency
                    4.1.1.5. ETF
                    4.1.1.6. Misc.
     4.2. North America Algorithmic Trading Market Outlook, by Deployment, Value (US$ Mn), 2018 - 2030
            4.2.1. Key Highlights
                    4.2.1.1. Cloud
                    4.2.1.2. On-premises
     4.3. North America Algorithmic Trading Market Outlook, by End-users Type, Value (US$ Mn), 2018 - 2030
            4.3.1. Key Highlights
                    4.3.1.1. Retail Investors
                    4.3.1.2. Institutional Investors
                    4.3.1.3. Long-term Traders
                    4.3.1.4. Short-term Traders
     4.4. North America Algorithmic Trading Market Outlook, by Country, Value (US$ Mn), 2018 - 2030
            4.4.1. Key Highlights
                    4.4.1.1. U.S.
                    4.4.1.2. Canada
            4.4.2. BPS/Market Attractiveness Analysis

5. Europe Algorithmic Trading Market Outlook, 2018 - 2030
     5.1. Europe Algorithmic Trading Market Outlook, by Trading Type, Value (US$ Mn), 2018 - 2030
            5.1.1. Key Highlights
                    5.1.1.1. Stock Market
                    5.1.1.2. FOREX
                    5.1.1.3. Bonds
                    5.1.1.4. Cryptocurrency
                    5.1.1.5. ETF
                    5.1.1.6. Misc.
     5.2. Europe Algorithmic Trading Market Outlook, by Deployment, Value (US$ Mn), 2018 - 2030
            5.2.1. Key Highlights
                    5.2.1.1. Cloud
                    5.2.1.2. On-premises
     5.3. Europe Algorithmic Trading Market Outlook, by End-users Type, Value (US$ Mn), 2018 - 2030
            5.3.1. Key Highlights
                    5.3.1.1. Retail Investors
                    5.3.1.2. Institutional Investors
                    5.3.1.3. Long-term Traders
                    5.3.1.4. Short-term Traders
     5.4. Europe Algorithmic Trading Market Outlook, by Country, Value (US$ Mn), 2018 - 2030
            5.4.1. Key Highlights
                    5.4.1.1. Germany
                    5.4.1.2. France
                    5.4.1.3. U.K.
                    5.4.1.4. Italy
                    5.4.1.5. Spain
                    5.4.1.6. Russia
                    5.4.1.7. Rest of Europe
            5.4.2. BPS/Market Attractiveness Analysis

6. Asia Pacific Algorithmic Trading Market Outlook, 2018 - 2030
     6.1. Asia Pacific Algorithmic Trading Market Outlook, by Trading Type, Value (US$ Mn), 2018 - 2030
            6.1.1. Key Highlights
                    6.1.1.1. Stock Market
                    6.1.1.2. FOREX
                    6.1.1.3. Bonds
                    6.1.1.4. Cryptocurrency
                    6.1.1.5. ETF
                    6.1.1.6. Misc.
     6.2. Asia Pacific Algorithmic Trading Market Outlook, by Deployment, Value (US$ Mn), 2018 - 2030
            6.2.1. Key Highlights
                    6.2.1.1. Cloud
                    6.2.1.2. On-premises
     6.3. Asia Pacific Algorithmic Trading Market Outlook, by End-users Type, Value (US$ Mn), 2018 - 2030
            6.3.1. Key Highlights
                    6.3.1.1. Retail Investors
                    6.3.1.2. Institutional Investors
                    6.3.1.3. Long-term Traders
                    6.3.1.4. Short-term Traders
     6.4. Asia Pacific Algorithmic Trading Market Outlook, by Country, Value (US$ Mn), 2018 - 2030
            6.4.1. Key Highlights
                    6.4.1.1. China
                    6.4.1.2. Japan
                    6.4.1.3. South Korea
                    6.4.1.4. India
                    6.4.1.5. Southeast Asia
                    6.4.1.6. Rest of Asia Pacific
            6.4.2. BPS/Market Attractiveness Analysis

7. Latin America Algorithmic Trading Market Outlook, 2018 - 2030
     7.1. Latin America Algorithmic Trading Market Outlook, by Trading Type, Value (US$ Mn), 2018 - 2030
            7.1.1. Key Highlights
                    7.1.1.1. Stock Market
                    7.1.1.2. FOREX
                    7.1.1.3. Bonds
                    7.1.1.4. Cryptocurrency
                    7.1.1.5. ETF
                    7.1.1.6. Misc.
     7.2. Latin America Algorithmic Trading Market Outlook, by Deployment, Value (US$ Mn), 2018 - 2030
            7.2.1. Key Highlights
                    7.2.1.1. Cloud
                    7.2.1.2. On-premises
     7.3. Latin America Algorithmic Trading Market Outlook, by End-users Type, Value (US$ Mn), 2018 - 2030
            7.3.1. Key Highlights
                    7.3.1.1. Retail Investors
                    7.3.1.2. Institutional Investors
                    7.3.1.3. Long-term Traders
                    7.3.1.4. Short-term Traders
     7.4. Latin America Algorithmic Trading Market Outlook, by Country, Value (US$ Mn), 2018 - 2030
            7.4.1. Key Highlights
                    7.4.1.1. Brazil
                    7.4.1.2. Mexico
                    7.4.1.3. Rest of Latin America
            7.4.2. BPS/Market Attractiveness Analysis

8. Middle East & Africa Algorithmic Trading Market Outlook, 2018 - 2030
     8.1. Middle East & Africa Algorithmic Trading Market Outlook, by Trading Type, Value (US$ Mn), 2018 - 2030
            8.1.1. Key Highlights
                    8.1.1.1. Stock Market
                    8.1.1.2. FOREX
                    8.1.1.3. Bonds
                    8.1.1.4. Cryptocurrency
                    8.1.1.5. ETF
                    8.1.1.6. Misc.
     8.2. Middle East & Africa Algorithmic Trading Market Outlook, by Deployment, Value (US$ Mn), 2018 - 2030
            8.2.1. Key Highlights
                    8.2.1.1. Cloud
                    8.2.1.2. On-premises
     8.3. Middle East & Africa Algorithmic Trading Market Outlook, by End-users Type, Value (US$ Mn), 2018 - 2030
            8.3.1. Key Highlights
                    8.3.1.1. Retail Investors
                    8.3.1.2. Institutional Investors
                    8.3.1.3. Long-term Traders
                    8.3.1.4. Short-term Traders
     8.4. Middle East & Africa Algorithmic Trading Market Outlook, by Country, Value (US$ Mn), 2018 - 2030
            8.4.1. Key Highlights
                    8.4.1.1. GCC
                    8.4.1.2. South Africa
                    8.4.1.3. Rest of Middle East & Africa
            8.4.2. BPS/Market Attractiveness Analysis

9. Competitive Landscape
     9.1. Company Market Share Analysis, 2021
     9.2. Competitive Dashboard
     9.3. Company Profiles
            9.3.1. Tradetron
                    9.3.1.1. Company Overview
                    9.3.1.2. Product Portfolio
                    9.3.1.3. Financial Overview
                    9.3.1.4. Business Strategies and Development
(*Note: Above details would be available for below list of companies based on availability)
            9.3.2. TradeStation
            9.3.3. 63 Moons Technologies
            9.3.4. Tickblaze LLC
            9.3.5. Argo Software Engineering
            9.3.6. Wyden
            9.3.7. Symphony
            9.3.8. Algotraders
            9.3.9. Inforeach Inc.
            9.3.10. Refinitiv Ltd.
            9.3.11. FXCM Group
            9.3.12. TCS
            9.3.13. Tethys

10. Appendix
     10.1. Research Methodology
     10.2. Report Assumptions
     10.3. Acronyms and Abbreviations

Our Research Methodology

Considering the volatility of business today, traditional approaches to strategizing a game plan can be unfruitful if not detrimental. True ambiguity is no way to determine a forecast. A myriad of predetermined factors must be accounted for such as the degree of risk involved, the magnitude of circumstances, as well as conditions or consequences that are not known or unpredictable. To circumvent binary views that cast uncertainty, the application of market research intelligence to strategically posture, move, and enable actionable outcomes is necessary.

View Methodology
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