Algorithmic Trading Market

Algorithmic Trading Market

Algorithmic Trading Market Forecasts to 2030 - Global Analysis By Type (Bonds, Cryptocurrencies, Exchange-Traded Fund (ETF) and Other Types), Deployment (Cloud and On-premise), Component (Solution and Services), Organization Size, End User and By Geography

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Published: 2023 ID: SMRC23882

This report covers the impact of COVID-19 on this global market

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.

Market Dynamics:


Growing need for efficiency and cost reduction

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.


High cost of setup

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.


Technology advancements

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.


Lack of risk assessment capabilities

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.

Covid-19 Impact

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 expected to be the largest during the forecast period

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.

The cloud segment is expected to have the highest CAGR during the forecast period

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.

Region with largest share:

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.

Region with highest CAGR:

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.

Key players in the market

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.

Key Developments:

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.

Types Covered:
• Bonds
• Cryptocurrencies
• Exchange-Traded Fund (ETF)
• Foreign Exchange (FOREX)
• Stock Markets
• Other Types

Deployments Covered:
• Cloud
• On-premise

Components Covered:
• Solution
• Services

Organization Sizes Covered:
• Small and Medium Enterprises
• Large Enterprises

End Users Covered:
• Short-term Traders
• Long-term Traders
• Retail Investors
• Institutional Investors
• Other End Users

Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o Qatar
o South Africa
o Rest of Middle East & Africa

What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements

Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
o Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface
2.1 Abstract
2.2 Stake Holders
2.3 Research Scope
2.4 Research Methodology
2.4.1 Data Mining
2.4.2 Data Analysis
2.4.3 Data Validation
2.4.4 Research Approach
2.5 Research Sources
2.5.1 Primary Research Sources
2.5.2 Secondary Research Sources
2.5.3 Assumptions

3 Market Trend Analysis
3.1 Introduction
3.2 Drivers
3.3 Restraints
3.4 Opportunities
3.5 Threats
3.6 End User Analysis
3.7 Impact of Covid-19

4 Porters Five Force Analysis
4.1 Bargaining power of suppliers
4.2 Bargaining power of buyers
4.3 Threat of substitutes
4.4 Threat of new entrants
4.5 Competitive rivalry

5 Global Algorithmic Trading Market, By Type
5.1 Introduction
5.2 Bonds
5.3 Cryptocurrencies
5.4 Exchange-Traded Fund (ETF)
5.5 Foreign Exchange (FOREX)
5.6 Stock Markets
5.7 Other Types

6 Global Algorithmic Trading Market, By Deployment
6.1 Introduction
6.2 Cloud
6.3 On-premise

7 Global Algorithmic Trading Market, By Component
7.1 Introduction
7.2 Solution
7.2.1 Platforms
7.2.2 Software Tools
7.3 Services
7.3.1 Professional Services
7.3.2 Managed Services

8 Global Algorithmic Trading Market, By Organization Size
8.1 Introduction
8.2 Small and Medium Enterprises
8.3 Large Enterprises

9 Global Algorithmic Trading Market, By End User
9.1 Introduction
9.2 Short-term Traders
9.3 Long-term Traders
9.4 Retail Investors
9.5 Institutional Investors
9.6 Other End Users

10 Global Algorithmic Trading Market, By Geography
10.1 Introduction
10.2 North America
10.2.1 US
10.2.2 Canada
10.2.3 Mexico
10.3 Europe
10.3.1 Germany
10.3.2 UK
10.3.3 Italy
10.3.4 France
10.3.5 Spain
10.3.6 Rest of Europe
10.4 Asia Pacific
10.4.1 Japan
10.4.2 China
10.4.3 India
10.4.4 Australia
10.4.5 New Zealand
10.4.6 South Korea
10.4.7 Rest of Asia Pacific
10.5 South America
10.5.1 Argentina
10.5.2 Brazil
10.5.3 Chile
10.5.4 Rest of South America
10.6 Middle East & Africa
10.6.1 Saudi Arabia
10.6.2 UAE
10.6.3 Qatar
10.6.4 South Africa
10.6.5 Rest of Middle East & Africa

11 Key Developments
11.1 Agreements, Partnerships, Collaborations and Joint Ventures
11.2 Acquisitions & Mergers
11.3 New Product Launch
11.4 Expansions
11.5 Other Key Strategies

12 Company Profiling
12.1 Algo Trader AG
12.2 Argo Software Engineering
12.3 InfoReach, Inc.
12.4 Kuberre Systems, Inc.
12.5 MetaQuotes Ltd.
12.6 Refinitiv Ltd
12.7 Symphony
12.8 Tata Consultancy Services Limited
12.9 Thomson Reuters
12.10 Tradetron
12.11 VIRTU Finance Inc.
12.12 Wyden
12.13 63 Moons Technologies Limited

List of Tables
1 Global Algorithmic Trading Market Outlook, By Region (2021-2030) ($MN)
2 Global Algorithmic Trading Market Outlook, By Type (2021-2030) ($MN)
3 Global Algorithmic Trading Market Outlook, By Bonds (2021-2030) ($MN)
4 Global Algorithmic Trading Market Outlook, By Cryptocurrencies (2021-2030) ($MN)
5 Global Algorithmic Trading Market Outlook, By Exchange-Traded Fund (ETF) (2021-2030) ($MN)
6 Global Algorithmic Trading Market Outlook, By Foreign Exchange (FOREX) (2021-2030) ($MN)
7 Global Algorithmic Trading Market Outlook, By Stock Markets (2021-2030) ($MN)
8 Global Algorithmic Trading Market Outlook, By Other Types (2021-2030) ($MN)
9 Global Algorithmic Trading Market Outlook, By Deployment (2021-2030) ($MN)
10 Global Algorithmic Trading Market Outlook, By Cloud (2021-2030) ($MN)
11 Global Algorithmic Trading Market Outlook, By On-premise (2021-2030) ($MN)
12 Global Algorithmic Trading Market Outlook, By Component (2021-2030) ($MN)
13 Global Algorithmic Trading Market Outlook, By Solution (2021-2030) ($MN)
14 Global Algorithmic Trading Market Outlook, By Platforms (2021-2030) ($MN)
15 Global Algorithmic Trading Market Outlook, By Software Tools (2021-2030) ($MN)
16 Global Algorithmic Trading Market Outlook, By Services (2021-2030) ($MN)
17 Global Algorithmic Trading Market Outlook, By Professional Services (2021-2030) ($MN)
18 Global Algorithmic Trading Market Outlook, By Managed Services (2021-2030) ($MN)
19 Global Algorithmic Trading Market Outlook, By Organization Size (2021-2030) ($MN)
20 Global Algorithmic Trading Market Outlook, By Small and Medium Enterprises (2021-2030) ($MN)
21 Global Algorithmic Trading Market Outlook, By Large Enterprises (2021-2030) ($MN)
22 Global Algorithmic Trading Market Outlook, By End User (2021-2030) ($MN)
23 Global Algorithmic Trading Market Outlook, By Short-term Traders (2021-2030) ($MN)
24 Global Algorithmic Trading Market Outlook, By Long-term Traders (2021-2030) ($MN)
25 Global Algorithmic Trading Market Outlook, By Retail Investors (2021-2030) ($MN)
26 Global Algorithmic Trading Market Outlook, By Institutional Investors (2021-2030) ($MN)
27 Global Algorithmic Trading Market Outlook, By Other End Users (2021-2030) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.

List of Figures


Research Methodology

We at Stratistics opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.

Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.

Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.

Data Mining

The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.

Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.

Data Analysis

From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:

  • Product Lifecycle Analysis
  • Competitor analysis
  • Risk analysis
  • Porters Analysis
  • PESTEL Analysis
  • SWOT Analysis

The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.

Data Validation

The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.

We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.

The data validation involves the primary research from the industry experts belonging to:

  • Leading Companies
  • Suppliers & Distributors
  • Manufacturers
  • Consumers
  • Industry/Strategic Consultants

Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.

For more details about research methodology, kindly write to us at

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