Global Algorithmic Trading Market (2021-2026) by Trading Type, Types of Traders, Components, Deployment Type, Organization Size, and Geography, IGR Competitive Analysis, Impact of Covid-19, Ansoff Analysis
Introduction
The Global Algorithmic Trading Market is estimated to be USD 13.1 Bn in 2021 and is expected to reach USD 22.1 Bn by 2026, growing at a CAGR of 11%.
Market Dynamics
The major factor driving the growth of the algorithmic trading market is the rising trend of digitalization and the emergence of AI and algorithms in the financial services sector. Easier and faster execution of orders, reduced transaction costs, make Algorithmic Trading attractive for exchanges, which will thus boost the growth of the market during the forecast period. The emergence of favorable government regulations and the rising need for market surveillance are fuelling market growth. However, a lack of monitoring and inadequate risk valuation capabilities is expected to hinder the market growth.
The rising adoption of cloud-based algorithmic trading platforms and the growing popularity of high-frequency traders (HFT) are expected to generate untapped opportunities for the market.
Market Segmentation
The Global Algorithmic Trading Market is segmented further based on Trading Type, Types of Traders, Components, Deployment Type, Organization Size, and Geography.
By Trading Type, the market is classified into Foreign Exchange, Stock Markets, Exchange Traded Funds, Bonds, Cryptocurrencies, and Others. Amongst all, the Exchange Traded Funds segment is estimated to hold the highest market share during the forecast period.
By Type of Traders, the market is classified into Institutional Investors, Retail Investors, Long-term Traders, and Short-term Traders. Amongst all, the Institutional Investors segment is estimated to hold the highest market share during the forecast period.
By Component, the market is classified as Solutions and Services. Amongst the two, the Solutions segment is estimated to hold the highest market share during the forecast period.
By Deployment Mode, the market is classified as Cloud and On-Premises. Amongst two, the Cloud segment is estimated to hold the highest market share during the forecast period.
By Organization Size, the market is classified as Small and Medium-Sized Enterprises and Large Enterprises. Amongst the two, the Small and Medium-Sized Enterprises segment is estimated to hold the highest market share during the forecast period.
By Geography, North America is projected to lead the market.
Recent Developments
1. London Stock Exchange Group completes $27 bn acquisition of Refinitiv – 29th January 2021
2. The listed German Fintech firm called NAGA announced that it had enhanced its overall trading experience and the integration of the MetaTrader 5 platform. The brand has further completely expanded its multi-asset, by offering to provide its growing network of clients with direct market access mainly to stocks listed on nine global exchanges, including NASDAQ, HKE, NYSE, London Stock Exchange, Börse Frankfurt, and BME, among others. - 17th February 2020
Company Profiles
Some of the companies covered in this report are 63 Moons Technologies Limited, Automated Trading SoftTech Pvt. Ltd., InfoReach Inc., MetaQuotes Ltd., Symphony Fintech Solutions Pvt Ltd., Tata Consultancy Services Limited, etc.
IGR Competitive Quadrant
The report includes IGR Competitive Quadrant, a proprietary tool to analyze and evaluate the position of companies based on their Industry Position score and Market Performance score. The tool uses various factors for categorizing the players into four categories. Some of these factors considered for analysis are financial performance over the last 3 years, growth strategies, innovation score, new product launches, investments, growth in market share, etc.
Why buy this report?
The report offers a comprehensive evaluation of the Global Algorithmic Trading Market. The report includes in-depth qualitative analysis, verifiable data from authentic sources, and projections about market size. The projections are calculated using proven research methodologies.
The report has been compiled through extensive primary and secondary research. The primary research is done through interviews, surveys, and observation of renowned personnel in the industry.
The report includes an in-depth market analysis using Porter’s 5 forces model and the Ansoff Matrix. In addition, the impact of Covid-19 on the market is also featured in the report.
The report also includes the regulatory scenario in the industry, which will help you make a well-informed decision. The report discusses major regulatory bodies and major rules and regulations imposed on this sector across various geographies.
The report also contains the competitive analysis using IGR Positioning Quadrants, Infogence’s Proprietary competitive positioning tool.
Report Highlights:
A complete analysis of the market, including parent industry
Important market dynamics and trends
Market segmentation
Historical, current, and projected size of the market based on value and volume
Market shares and strategies of key players
Recommendations to companies for strengthening their foothold in the market
- 1 Report Description
- 1.1 Study Objectives
- 1.2 Market Definition
- 1.3 Currency
- 1.4 Years Considered
- 1.5 Language
- 1.6 Key Stakeholders
- 2 Research Methodology
- 2.1 Research Process
- 2.2 Data Collection and Validation
- 2.2.1 Secondary Research
- 2.2.2 Primary Research
- 2.2.3 IGR Models
- 2.3 Market Size Estimation
- 2.3.1 Bottom-Up Approach
- 2.3.2 Top-Down Approach
- 2.4 Assumptions of the Study
- 2.5 Limitations of the Study
- 3 Executive Summary
- 3.1 Introduction
- 3.2 Market Size and Segmentation
- 3.3 Market Outlook
- 4 Market Influencers
- 4.1 Drivers
- 4.1.1 Increasing Demand for Reliable, Fast, and Effective Order Execution
- 4.1.2 Reduced Transaction Costs
- 4.1.3 The Emergence of AI and Algorithms in the Financial Services
- 4.1.4 Favorable Government Regulations and Rising Demand for Market Surveillance
- 4.2 Restraints
- 4.2.1 Lack of Monitoring and Inadequate Risk Valuation Capabilities
- 4.3 Opportunities
- 4.3.1 Rising Adoption of Cloud-based Algorithmic Trading Platforms
- 4.3.2 Growing Popularity of High-Frequency Traders (HFT)
- 4.4 Challenges
- 4.4.1 Lack of Accuracy and Consistency in Algorithms
- 4.5 Trends
- 5 Market Analysis
- 5.1 Regulatory Scenario
- 5.2 Porter’s Five Forces Analysis
- 5.3 Impact of COVID-19
- 5.4 Ansoff Matrix Analysis
- 6 Global Algorithmic Trading Market, By Trading Type
- 6.1 Introduction
- 6.2 Foreign Exchange
- 6.3 Stock Markets
- 6.4 Exchange-Traded Funds
- 6.5 Bonds
- 6.6 Cryptocurrencies
- 6.7 Others
- 7 Global Algorithmic Trading Market, By Type of Traders
- 7.1 Introduction
- 7.2 Institutional Investors
- 7.3 Retail Investors
- 7.4 Long-term Traders
- 7.5 Short-term Traders
- 8 Global Algorithmic Trading Market, By Component
- 8.1 Introduction
- 8.2 Solutions
- 8.2.1 Platforms
- 8.2.2 Software Tools
- 8.3 Services
- 8.3.1 Professional Services
- 8.3.2 Managed Services
- 9 Global Algorithmic Trading Market, By Deployment Mode
- 9.1 Introduction
- 9.2 Cloud
- 9.3 On-Premise
- 10 Global Algorithmic Trading Market, By Organization Size
- 10.1 Introduction
- 10.2 Small and Medium-Sized Enterprises
- 10.3 Large Enterprises
- 11 Global Algorithmic Trading Market, By Geography
- 11.1 Introduction
- 11.2 North America
- 11.2.1 US
- 11.2.2 Canada
- 11.2.3 Mexico
- 11.3 South America
- 11.3.1 Brazil
- 11.3.2 Argentina
- 11.3.3 Chile
- 11.3.4 Colombia
- 11.4 Europe
- 11.4.1 UK
- 11.4.2 France
- 11.4.3 Germany
- 11.4.4 Italy
- 11.4.5 Spain
- 11.4.6 Netherlands
- 11.4.7 Sweden
- 11.4.8 Russia
- 11.4.9 Rest of Europe
- 11.5 Asia-Pacific
- 11.5.1 China
- 11.5.2 Japan
- 11.5.3 India
- 11.5.4 Indonesia
- 11.5.5 Malaysia
- 11.5.6 South Korea
- 11.5.7 Australia
- 11.5.8 Sri Lanka
- 11.5.9 Thailand
- 11.5.10 Rest of APAC
- 11.6 Middle-East and Africa
- 11.6.1 Qatar
- 11.6.2 Saudi Arabia
- 11.6.3 South Africa
- 11.6.4 United Arab Emirates
- 12 Competitive Landscape
- 12.1 IGR Competitive Quadrant
- 12.2 Market Share Analysis
- 12.3 Strategic Initiatives
- 12.3.1 M&A and Investments
- 12.3.2 Partnerships and Collaborations
- 12.3.3 Product Developments and Improvements
- 13 Company Profiles
- 13.1 Thomson Reuters Corporation
- 13.2 63 moons Technologies Limited
- 13.3 VIRTU Financial Inc.
- 13.4 London Stock Exchange Group Plc.
- 13.5 Software AG
- 13.6 MetaQuotes Ltd
- 13.7 Symphony Fintech Solutions Pvt Ltd.
- 13.8 InfoReach Inc.
- 13.9 Argo Software Engineering
- 13.10 Kuberre Systems, Inc.
- 13.11 Tata Consultancy Services Limited
- 13.12 QuantCore Capital Management, LLC
- 13.13 iRageCapital Advisory Pvt Ltd
- 13.14 Automated Trading SoftTech Pvt. Ltd.
- 13.15 Tethys Technology Inc.
- 13.16 Trading Technologies International, Inc.
- 13.17 uTrade Solutions Pvt. Ltd.
- 13.18 Exegy Incorporated
- 13.19 AlgoTrader AG
- 13.20 Trade Tool FX
- 13.21 Tower Research Capital LLC
- 13.22 MetaQuotess Ltd.
- 13.23 Optiver VOF
- 13.24 Citadel Enterprise Americas LLC
- Appendix
- 13.25 Questionnaire
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