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Report Scope & Overview:

The Algorithmic Trading Market size was valued at USD 16.9 billion in 2022 and is expected to grow to USD 42.74 billion by 2030 and grow at a CAGR of 22.3 % over the forecast period of 2023-2030.

Algorithmic Trading is a type of automation where a computer program is used to successfully carry out a given set of rules or instructions, including the purchasing or selling of an asset in consideration of changing market data. Additionally, the established sets of guidelines or directives are based on parameters like quantity, cost, scheduling, or any mathematical model. Algorithmic Trading solutions are becoming more popular among investors and traders since they enable them to execute trades at the most advantageous prices.

Using market surveillance equipment, traders keep tabs on their investment portfolio and Trading activities. Over the course of the forecast period, the market expansion is anticipated to be driven by rising demand for market surveillance technology that benefits from lower transaction costs. Additionally, algorithmic Trading solutions make it simpler and faster to execute orders, which appeals to exchanges. Numerous advantages provided by these solutions, such as concurrent automated checks on numerous market circumstances and trades timed immediately and accurately, are anticipated to open new market expansion prospects.

Market Dynamics

Drivers

  • Consistently increasing the adoption of AI (artificial intelligence), and (machine learning) ML in financial services that drives the market.

  • Financial Institutions Should Use Algorithmic Trading to Promote Market Growth

Since algorithms are the most cost-effective for low-maintenance trades, their use has led to headcount reductions and changes to sales desks. One important innovation that has helped to lower trading costs is the ability to automatically surrender orders to exchanges rather than brokers. Automation has also improved back-office tasks and post-trade services like clearing and settlement. Broker-dealers additionally employ algorithms to match buy and sell orders without divulging quotes. Broker algorithms enable increased liquidity and higher commissions for brokers by limiting information leakage and taking both the offer and bid sides of the trade.

Restrains

  • Lack of Capabilities for Appropriate Risk Valuation to Restrain Market Growth

  • The traders have no discretionary decision-making power. The trader lacks the power to halt the program and stop trading

Algorithm trading is vulnerable to risks and uncertainties, and without effective safeguards, losses can grow quickly. High-frequency trading is an algorithmic trading strategy that makes use of electronic trading instruments and quick-response financial data to conduct transactions at high turnover rates, quick speeds, and high order-to-trade ratios. Orders that violate risk management standards are withdrawn by investment businesses. High-frequency Trading (HFT) using algorithms also raises issues, such as rising systemic risk. Additionally, new market volatility undermines many investors' confidence in the fairness of the market. Therefore, the market's ability to grow is hampered by algorithmic trading systems' lack of risk valuation capabilities.

Opportunities

  • The popularity of cloud-based algorithmic trading solutions is growing among traders because they provide efficient process automation, data maintenance, and cost-effective management.

Challenges

  • Lack of Risk Assessment Capabilities

  • Market growth is anticipated to be hampered by algorithm’s lack of consistency and precision, Over the projection period

Impact Of covid-19

The forecast is expected to be greater than predictions made before COVID-19. Due to the rising acceptance of algorithmic Trading solutions in the face of unprecedented circumstances, the COVID-19 outbreak has had no effect on the expansion of the algorithmic Trading market. The COVID-19 epidemic has considerably accelerated the growth rate of the algorithmic Trading industry because there has been a growing trend towards algo Trading, which allows for a speedy decision-making process while minimizing human mistakes. The COVID-19 outbreak, for instance, may have merely accelerated the industry's shift towards electronic Trading, according to a recent paper by the Reserve Bank of Australia.

Additionally, during the pandemic, market participants launched cutting-edge algorithmic Trading tools to ensure better serving the increasing trade volumes. This element fuels market expansion. For instance, Cowen, a worldwide independent American investment bank and financial services corporation, introduced an algorithmic Trading solution in March 2021 to assist institutional clients in navigating market dynamics brought on by a rise in retail Trading volume.

Key Market Segmentation

The Algorithmic Trading Market is segmented into five types on the basis of by solution, by service, by Deployment, by Trading types, and by types of traders.

By Solution:

  • Platforms

  • Software Tools

By Service:

  • Professional Services

  • Managed Services

By Deployment:

  • Cloud

  • On-premise

By Trading Types:

  • Foreign Exchange (FOREX)

  • Stock Markets

  • Exchange-Traded Fund (ETF)

  • Bonds

  • Cryptocurrencies

  • Others

By Type of Traders:

  • Institutional Investors

  • Long-term Traders

  • Short-term Traders

  • Retail Investors

Regional Analysis

North America dominated the algorithmic Trading business with high revenue and market share. The existence of multiple market participants in the area is responsible for the regional expansion. To increase their position in the market, these vendors are also implementing a variety of growth techniques. Over the projected period, a number of variables, including rising investments in Trading technologies and rising government backing for international trade, are anticipated to contribute to regional growth.

Over the forecast period, the highest CAGR is anticipated in Asia Pacific. The regional expansion, which has increased demand for algorithmic Trading platforms, is attributable to the large expenditures made by the public and commercial sectors to enhance their Trading technologies. The region now features more computerized business activity. It is expected that algorithmic Trading solutions would be used more frequently as a result. In the regional analysis study of the regions of North America, Europe, Asia Pacific middle east, and Africa.

REGIONAL COVERAGE:

North America

  • USA

  • Canada

  • Mexico

Europe

  • Germany

  • UK

  • France

  • Italy

  • Spain

  • The Netherlands

  • Rest of Europe

Asia-Pacific

  • Japan

  • South Korea

  • China

  • India

  • Australia

  • Rest of Asia-Pacific

The Middle East & Africa

  • Israel

  • UAE

  • South Africa

  • Rest of the Middle East & Africa

Latin America

  • Brazil

  • Argentina

  • Rest of Latin America

Key Players:

The major players in market are 63 moons technologies limited, Tata Consultancy Services Limited, Algo Trader, Symphony, Argo Software Engineering, Refinitiv, InfoReach, Inc., Kuberre Systems, Inc., MetaQuotes Ltd., VIRTU Finance Inc and others in final report.

Algorithmic Trading Market Report Scope:
Report Attributes Details
Market Size in 2022  US$  16.9 Bn
Market Size by 2030  US$ 42.74 Bn
CAGR   CAGR of  22.3 % From 2023 to 2030
Base Year 2022
Forecast Period  2023-2030
Historical Data  2020-2021
Report Scope & Coverage Market Size, Segments Analysis, Competitive  Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segments • By Solution (Platforms, Software Tools), By Service (Professional Services, Managed Services)
• By Deployment (Cloud, On-premise)
• By Trading Types (Foreign Exchange (FOREX), Stock Markets, Exchange-Traded Fund (ETF), Bonds, Cryptocurrencies, Others)
• By Type of Traders (Institutional Investors, Long-term Traders, Short-term Traders, Retail Investors)
Regional Analysis/Coverage North America (USA, Canada, Mexico), Europe
(Germany, UK, France, Italy, Spain, Netherlands,
Rest of Europe), Asia-Pacific (Japan, South Korea,
China, India, Australia, Rest of Asia-Pacific), The
Middle East & Africa (Israel, UAE, South Africa,
Rest of Middle East & Africa), Latin America (Brazil, Argentina, Rest of Latin America)
Company Profiles 63 moons technologies limited, Tata Consultancy Services Limited, Algo Trader, Symphony, Argo Software Engineering, Refinitiv, InfoReach, Inc., Kuberre Systems, Inc., MetaQuotes Ltd., VIRTU Finance Inc
Key Drivers • Consistently increasing the adoption of AI (artificial intelligence), and (machine learning) ML in financial services that drives the market.
• Financial Institutions Should Use Algorithmic Trading to Promote Market Growth
Market Opportunities • The popularity of cloud-based algorithmic trading solutions is growing among traders because they provide efficient process automation, data maintenance, and cost-effective management.

 

Frequently Asked Questions

The growth rate of the Algorithmic Trading Market is CAGR 22.3 %.

USD 16.9 billion in 2022 is the market share of the Algorithmic Trading Market.

The major worldwide key players in the Algorithmic Trading Market are 63 moons technologies limited, AlgoTrader, Argo Software Engineering, InfoReach, Inc., Symphony, Tata Consultancy Services Limited, VIRTU Finance Inc and others in final report.

The forecast period for the Algorithmic Trading Market is 2022-2030.

North American region is dominating the global Algorithmic Trading Market.

Table of Contents

1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions

2. Research Methodology

3. Market Dynamics
3.1 Drivers
3.2 Restraints
3.3 Opportunities
3.4 Challenges

4. Impact Analysis
4.1 COVID-19 Impact Analysis

5. Value Chain Analysis

6. Porter’s 5 forces model

7. PEST Analysis

8. Algorithmic Trading Market Segmentation, by Solution
8.1 Platforms
8.2 Software Tools

9. Algorithmic Trading Market Segmentation, by Service
9.1 Professional Services
9.2 Managed Services

10. Algorithmic Trading Market Segmentation, by Deployment
10.1 Cloud
10.2 On-premise

11. Algorithmic Trading Market Segmentation, by Trading Types
11.1 Foreign Exchange (FOREX)
11.2 Stock Markets
11.3 Exchange-Traded Fund (ETF)
11.4 Bonds
11.5 Cryptocurrencies
11.6 Others

12. Algorithmic Trading Market Segmentation, by Type of Traders
12.1 Institutional Investors
12.2 Long-term Traders
12.3 Short-term Traders
12.4 Retail Investors

13. Regional Analysis
13.1 Introduction
13.2 North America
13.2.1 North America Algorithmic Trading Market by Country
13.2.2North America Algorithmic Trading Market by Solution
13.2.3 North America Algorithmic Trading Market by Service
13.2.4 North America Algorithmic Trading Market by Deployment
13.2.5 North America Algorithmic Trading Market by Trading Types
13.2.6 North America Algorithmic Trading Market by Type of Traders
13.2.7 USA
13.2.7.1 USA Algorithmic Trading Market by Solution
13.2.7.2 USA Algorithmic Trading Market by Service
13.2.7.3 USA Algorithmic Trading Market by Deployment
13.2.7.4 USA Algorithmic Trading Market by Trading Types
13.2.7.5 USA Algorithmic Trading Market by Type of Traders
13.2.8 Canada
13.2.8.1 Canada Algorithmic Trading Market by Solution
13.2.8.2 Canada Algorithmic Trading Market by Service
13.2.8.3 Canada Algorithmic Trading Market by Deployment
13.2.8.4 Canada Algorithmic Trading Market by Trading Types
13.2.8.5 Canada Algorithmic Trading Market by Type of Traders
13.2.9 Mexico
13.2.9.1 Mexico Algorithmic Trading Market by Solution
13.2.9.2 Mexico Algorithmic Trading Market by Service
13.2.9.3 Mexico Algorithmic Trading Market by Deployment
13.2.9.4 Mexico Algorithmic Trading Market by Trading Types
13.2.9.5 Mexico Algorithmic Trading Market by Type of Traders
13.3 Europe
13.3.1 Europe Algorithmic Trading Market by country
13.3.2 Europe Algorithmic Trading Market by Solution
13.3.3 Europe Algorithmic Trading Market by Service
13.3.4 Europe Algorithmic Trading Market by Deployment
13.3.5 Europe Algorithmic Trading Market by Trading Types
13.3.6 Europe Algorithmic Trading Market by Type of Traders
13.3.7 Germany
13.3.7.1 Germany Algorithmic Trading Market by Solution
13.3.7.2 Germany Algorithmic Trading Market by Service
13.3.7.3 Germany Algorithmic Trading Market by Deployment
13.3.7.4 Germany Algorithmic Trading Market by Trading Types
13.3.7.5 Germany Algorithmic Trading Market by Type of Traders
13.3.8 UK
13.3.8.1 UK Algorithmic Trading Market by Solution
13.3.8.2 UK Algorithmic Trading Market by Service
13.3.8.3 UK Algorithmic Trading Market by Deployment
13.3.8.4 UK Algorithmic Trading Market by Trading Types
13.3.8.5 UK Algorithmic Trading Market by Type of Traders
13.3.9 France
13.3.9.1 France Algorithmic Trading Market by Solution
13.3.9.2 France Algorithmic Trading Market by Service
13.3.9.3 France Algorithmic Trading Market by Deployment
13.3.9.4 France Algorithmic Trading Market by Trading Types
13.3.9.5 France Algorithmic Trading Market by Type of Traders
13.3.10 Italy
13.3.10.1 Italy Algorithmic Trading Market by Solution
13.3.10.2 Italy Algorithmic Trading Market by Service
13.3.10.3 Italy Algorithmic Trading Market by Deployment
13.3.10.4 Italy Algorithmic Trading Market by Trading Types
13.3.10.5 Italy Algorithmic Trading Market by Type of Traders
13.3.11 Spain
13.3.11.1 Spain Algorithmic Trading Market by Solution
13.3.11.2 Spain Algorithmic Trading Market by Service
13.3.11.3 Spain Algorithmic Trading Market by Deployment
13.3.11.4 Spain Algorithmic Trading Market by Trading Types
13.3.11.5 Spain Algorithmic Trading Market by Type of Traders
13.3.12 The Netherlands
13.3.12.1 Netherlands Algorithmic Trading Market by Solution
13.3.12.2 Netherlands Algorithmic Trading Market by Service
13.3.12.3 Netherlands Algorithmic Trading Market by Deployment
13.3.12.4 Netherlands Algorithmic Trading Market by Trading Types
13.3.12.5 Netherlands Algorithmic Trading Market by Type of Traders
13.3.13 Rest of Europe
13.3.13.1 Rest of Europe Algorithmic Trading Market by Solution
13.3.13.2 Rest of Europe Algorithmic Trading Market by Service
13.3.13.3 Rest of Europe Algorithmic Trading Market by Deployment
13.3.13.4 Rest of Europe Algorithmic Trading Market by Trading Types
13.3.13.5 Rest of Europe Algorithmic Trading Market by Type of Traders
13.4 Asia-Pacific
13.4.1 Asia Pacific Algorithmic Trading Market by Country
13.4.2 Asia Pacific Algorithmic Trading Market by Solution
13.4.3 Asia Pacific Algorithmic Trading Market by Service
13.4.4 Asia Pacific Algorithmic Trading Market by Deployment
13.4.5 Asia Pacific Algorithmic Trading Market by Trading Types
13.4.6 Asia Pacific Algorithmic Trading Market by Type of Traders
13.4.7 japan
13.4.7.1 Japan Algorithmic Trading Market by Solution
13.4.7.2 Japan Algorithmic Trading Market by Service
13.4.7.3 Japan Algorithmic Trading Market by Deployment
13.4.7.4 Japan Algorithmic Trading Market by Trading Types
13.4.7. 5 Japan Algorithmic Trading Market by Type of Traders
13.4.8 South Korea
13.4.8.1 South Korea Algorithmic Trading Market by Solution
13.4.8.2 South Korea Algorithmic Trading Market by Service
13.4.8.3 South Korea Algorithmic Trading Market by Deployment
13.4.8.4 South Korea Algorithmic Trading Market by Trading Types
13.4.8.5 South Korea Algorithmic Trading Market by Type of Traders
13.4.9 China
13.4.9.1 China Algorithmic Trading Market by Solution
13.4.9.2 China Algorithmic Trading Market by Service
13.4.9.3 China Algorithmic Trading Market by Deployment
13.4.9.4 China Algorithmic Trading Market by Trading Types
13.4.9.5 China Algorithmic Trading Market by Type of Traders
13.4.10 India
13.4.10.1 India Algorithmic Trading Market by Solution
13.4.10.2 India Algorithmic Trading Market by Service
13.4.10.3 India Algorithmic Trading Market by Deployment
13.4.10.4 India Algorithmic Trading Market by Trading Types
13.4.10.5 India Algorithmic Trading Market by Type of Traders
13.4.11 Australia
13.4.11.1 Australia Algorithmic Trading Market by Solution
13.4.11.2 Australia Algorithmic Trading Market by Service
13.4.11.3 Australia Algorithmic Trading Market by Deployment
13.4.11.4 Australia Algorithmic Trading Market by Trading Types
13.4.11.5 Australia Algorithmic Trading Market by Type of Traders
13.4.12 Rest of Asia-Pacific
13.4.12.1 APAC Algorithmic Trading Market by Solution
13.4.12.2 APAC Algorithmic Trading Market by Service
13.4.12.3 APAC Algorithmic Trading Market by Deployment
13.4.12.4 APAC Algorithmic Trading Market by Trading Types
13.4.12.5 APAC Algorithmic Trading Market by Type of Traders
13.5 The Middle East & Africa
13.5.1 The Middle East & Africa Algorithmic Trading Market by Country
13.5.2 The Middle East & Africa Algorithmic Trading Market by Solution
13.5.3 The Middle East & Africa Algorithmic Trading Market by Service
13.5.4 The Middle East & Africa Algorithmic Trading Market by Deployment
13.5.5 The Middle East & Africa Algorithmic Trading Market by Trading Types
13.5.6 The Middle East & Africa Algorithmic Trading Market by Type of Traders
13.5.7 Israel
13.5.7.1 Israel Algorithmic Trading Market by Solution
13.5.7.2 Israel Algorithmic Trading Market by Service
13.5.7.3 Israel Algorithmic Trading Market by Deployment
13.5.7.4 Israel Algorithmic Trading Market by Trading Types
13.5.7.5 Israel Algorithmic Trading Market by Type of Traders
13.5.8 UAE
13.5.8.1 UAE Algorithmic Trading Market by Solution
13.5.8.2 UAE Algorithmic Trading Market by Service
13.5.8.3 UAE Algorithmic Trading Market by Deployment
13.5.8.4 UAE Algorithmic Trading Market by Trading Types
13.5.8.5 UAE Algorithmic Trading Market by Type of Traders
13.5.9 South Africa
13.5.9.1 South Africa Algorithmic Trading Market by Solution
13.5.9.2 South Africa Algorithmic Trading Market by Service
13.5.9.3 South Africa Algorithmic Trading Market by Deployment
13.5.9.4 South Africa Algorithmic Trading Market by Trading Types
13.5.9.5 South Africa Algorithmic Trading Market by Type of Traders
13.5.10 Rest of Middle East & Africa
13.5.10.1 Rest of Middle East & Asia Algorithmic Trading Market by Solution
13.5.10.2 Rest of Middle East & Asia Algorithmic Trading Market by Service
13.5.10.3 Rest of Middle East & Asia Algorithmic Trading Market by Deployment
13.5.10.4 Rest of Middle East & Asia Algorithmic Trading Market by Trading Types
13.5.10.5 Rest of Middle East & Asia Algorithmic Trading Market by Type of Traders
13.6 Latin America
13.6.1 Latin America Algorithmic Trading Market by Country
13.6.2 Latin America Algorithmic Trading Market by Solution
13.6.3 Latin America Algorithmic Trading Market by Service
13.6.4 Latin America Algorithmic Trading Market by Deployment
13.6.5 Latin America Algorithmic Trading Market by Trading Types
13.6.6 Latin America Algorithmic Trading Market by Type of Traders
13.6.7 Brazil
13.6.7.1 Brazil Algorithmic Trading Market by Solution
13.6.7.2 Brazil Africa Algorithmic Trading Market by Service
13.6.7.3 Brazil Algorithmic Trading Market by Deployment
13.6.7.4 Brazil Algorithmic Trading Market by Trading Types
13.6.7.5 Brazil Algorithmic Trading Market by Type of Traders
13.6.8 Argentina
13.6.8.1 Argentina Algorithmic Trading Market by Solution
13.6.8.2 Argentina Algorithmic Trading Market by Service
13.6.8.3 Argentina Algorithmic Trading Market by Deployment
13.6.8.4 Argentina Algorithmic Trading Market by Trading Types
13.6.8.5 Argentina Algorithmic Trading Market by Type of Traders
13.6.9 Rest of Latin America
13.6.9.1 Rest of Latin America Algorithmic Trading Market by Solution
13.6.9.2 Rest of Latin America Algorithmic Trading Market by Service
13.6.9.3 Rest of Latin America Algorithmic Trading Market by Deployment
13.6.9.4 Rest of Latin America Algorithmic Trading Market by Trading Types
13.6.9.5 Rest of Latin America Algorithmic Trading Market by Type of Traders

14. Company Profile
14.1 AlgoTrader
14.1.1 Market Overview
14.1.2 Financials
14.1.3 Product/Services/Offerings
14.1.4 SWOT Analysis
14.1.5 The SNS View
14.2 63 moons technologies limited.
14.2.1 Market Overview
14.2.2 Financials
14.2.3 Product/Services/Offerings
14.2.4 SWOT Analysis
14.2.5 The SNS View
14.3 Argo Software Engineering.
14.3.1 Market Overview
14.3.2 Financials
14.3.3 Product/Services/Offerings
14.3.4 SWOT Analysis
14.3.5 The SNS View
14.4 InfoReach, Inc.
14.4.1 Market Overview
14.4.2 Financials
14.4.3 Product/Services/Offerings
14.4.4 SWOT Analysis
14.4.5 The SNS View
14.5 Kuberre Systems, Inc
14.5.1 Market Overview
14.5.2 Financials
14.5.3 Product/Services/Offerings
14.5.4 SWOT Analysis
14.5.5 The SNS View
14.6 MetaQuotes Ltd.
14.6.1 Market Overview
14.6.2 Financials
14.6.3 Product/Services/Offerings
14.6.4 SWOT Analysis
14.6.5 The SNS View
14.7 Refinitiv
14.7.1 Market Overview
14.7.2 Financials
14.7.3 Product/Services/Offerings
14.7.4 SWOT Analysis
14.7.5 The SNS View
14.8 Symphony
14.8.1 Market Overview
14.8.2 Financials
14.8.3 Product/Services/Offerings
14.8.4 SWOT Analysis
14.8.5 The SNS View
14.9 Tata Consultancy Services Limited
14.9.1 Market Overview
14.9.2 Financials
14.9.3 Product/Services/Offerings
14.9.4 SWOT Analysis
14.9.5 The SNS View
14.10 VIRTU Finance Inc.
14.10.1 Market Overview
14.10.2 Financials
14.10.3 Product/Services/Offerings
14.10.4 SWOT Analysis
14.10.5 The SNS View

15. Competitive Landscape
15.1 Competitive Benchmarking
15.2 Market Share Analysis
15.3 Recent Developments

16. USE Cases and Best Practices

17. Conclusion

An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.

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The 5 steps process:

Step 1: Secondary Research:

Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.

Secondary Research

Step 2: Primary Research

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This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.

Primary Research

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Data Bank Validation

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