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Global Algorithmic Trading Market to reach USD 3.30 billion by the end of 2029.

Global Algorithmic Trading Market Size study & Forecast, by Type (Stock Market, Foreign Exchange, Exchange-Traded Fund, Bonds, Cryptocurrencies, Others) by Deployment (Cloud, On-premise), by End-user (Short-term Traders, Long-term Traders, Retail Investors, Institutional Investors) and Regional Analysis, 2022-2029

Product Code: ICTNGT-61714055
Publish Date: 13-05-2023
Page: 200

Global Algorithmic Trading Market is valued at approximately USD 1.89 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 7.2% over the forecast period 2022-2029. Algorithmic trading is a process of executing orders using automated, pre-programmed trading instructions that take time, price, and volume into consideration. This type of trading aims to increase efficiency by using computers’ speed and computational power instead of human traders. The surging adoption of algorithmic trading in financial institutions, rising for fast, reliable, and effective order execution and reduced transaction costs, coupled with the growing investments in trading technologies are the primary factors that are fostering market growth across the globe.

In addition, the rise in government regulations is acting as a catalyzing factor for market growth.
For instance, MiFID II- a European Union framework to rule financial markets by the implementation of a comprehensive set of algorithmic and high-frequency trading regulations in 2021. Also, in September 2022, SEBI declared several guidelines for stock brokers to offer services relating to algorithmic trading to investors and prevent misspelling instances. Moreover, the rising emergence of AI and ML in financial services, as well as the surge in demand for cloud-based solutions are presenting various lucrative opportunities over the forecasting years. However, the lack of appropriate risk valuation capabilities and lack of accuracy and consistency in algorithms are challenging the market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Algorithmic Trading Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. North America dominated the market in terms of revenue, owing to the growing investments in trading technologies, as well as rising government support for global trade. Whereas, the Asia Pacific is also expected to grow with the highest CAGR during the forecast period, owing to factors such as the rising deployment of algo trading technology by trading companies, along with and increase in computerized trading in the market space.

Major market players included in this report are:
Tradetron (U.S.)
Tickblaze LLC (U.S.)
Wyden (U.S.)
TradeStation (U.S.)
InfoReach, Inc. (U.S.)
Symphony (U.S.)
ALGOTRADERS (U.S.)
Argo Software Engineering (U.S.)
FXCM Group (U.S.)
Tata Consultancy Services Limited (U.S.)

Recent Developments in the Market:
Ø In October 2022, Scotiabank introduced an algorithmic trading platform in collaboration with BestEx Research for the Canadian stock market. This new service offers top-tier trading performance for customers while significantly reducing costs thanks to research-based logic.
Ø In March 2022, Trading Technologies International, Inc.- a provider of trading software stated that it had acquired RCM-X, a provider of technology for algorithmic trading products. This acquisition of RCM-X provides best-in-class implementation tools.

Global Algorithmic Trading Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Type, Deployment, End-user, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
Customization Scope Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Type:
Stock Market
Foreign Exchange
Exchange-Traded Fund
Bonds
Cryptocurrencies
Others
By Deployment:
Cloud
On-premise
By End-user:
Short-term Traders
Long-term Traders
Retail Investors
Institutional Investors
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
RoLA
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Billion)
1.2.1. Algorithmic Trading Market, by Region, 2019-2029 (USD Billion)
1.2.2. Algorithmic Trading Market, by Type, 2019-2029 (USD Billion)
1.2.3. Algorithmic Trading Market, by Deployment, 2019-2029 (USD Billion)
1.2.4. Algorithmic Trading Market, by End-user, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Algorithmic Trading Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Algorithmic Trading Market Dynamics
3.1. Algorithmic Trading Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Surging adoption of algorithmic trading in financial institutions
3.1.1.2. Rise in government regulations
3.1.2. Market Challenges
3.1.2.1. Lack of appropriate risk valuation capabilities
3.1.2.2. Lack of accuracy and consistency in algorithms
3.1.3. Market Opportunities
3.1.3.1. Rising emergence of AI and ML in financial services
3.1.3.2. Surge in demand for cloud-based solutions
Chapter 4. Global Algorithmic Trading Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. Industry Experts Prospective
4.7. Analyst Recommendation & Conclusion
Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Algorithmic Trading Market, by Type
6.1. Market Snapshot
6.2. Global Algorithmic Trading Market by Type, Performance – Potential Analysis
6.3. Global Algorithmic Trading Market Estimates & Forecasts by Type 2019-2029 (USD Billion)
6.4. Algorithmic Trading Market, Sub Segment Analysis
6.4.1. Stock Market
6.4.2. Foreign Exchange
6.4.3. Exchange-Traded Fund
6.4.4. Bonds
6.4.5. Cryptocurrencies
6.4.6. Others
Chapter 7. Global Algorithmic Trading Market, by Deployment
7.1. Market Snapshot
7.2. Global Algorithmic Trading Market by Deployment, Performance – Potential Analysis
7.3. Global Algorithmic Trading Market Estimates & Forecasts by Deployment 2019-2029 (USD Billion)
7.4. Algorithmic Trading Market, Sub Segment Analysis
7.4.1. Cloud
7.4.2. On-premise
Chapter 8. Global Algorithmic Trading Market, by End-user
8.1. Market Snapshot
8.2. Global Algorithmic Trading Market by End-user, Performance – Potential Analysis
8.3. Global Algorithmic Trading Market Estimates & Forecasts by End-user 2019-2029 (USD Billion)
8.4. Algorithmic Trading Market, Sub Segment Analysis
8.4.1. Short-term Traders
8.4.2. Long-term Traders
8.4.3. Retail Investors
8.4.4. Institutional Investors
Chapter 9. Global Algorithmic Trading Market, Regional Analysis
9.1. Algorithmic Trading Market, Regional Market Snapshot
9.2. North America Algorithmic Trading Market
9.2.1. U.S. Algorithmic Trading Market
9.2.1.1. Type breakdown estimates & forecasts, 2019-2029
9.2.1.2. Deployment breakdown estimates & forecasts, 2019-2029
9.2.1.3. End-user breakdown estimates & forecasts, 2019-2029
9.2.2. Canada Algorithmic Trading Market
9.3. Europe Algorithmic Trading Market Snapshot
9.3.1. U.K. Algorithmic Trading Market
9.3.2. Germany Algorithmic Trading Market
9.3.3. France Algorithmic Trading Market
9.3.4. Spain Algorithmic Trading Market
9.3.5. Italy Algorithmic Trading Market
9.3.6. Rest of Europe Algorithmic Trading Market
9.4. Asia-Pacific Algorithmic Trading Market Snapshot
9.4.1. China Algorithmic Trading Market
9.4.2. India Algorithmic Trading Market
9.4.3. Japan Algorithmic Trading Market
9.4.4. Australia Algorithmic Trading Market
9.4.5. South Korea Algorithmic Trading Market
9.4.6. Rest of Asia Pacific Algorithmic Trading Market
9.5. Latin America Algorithmic Trading Market Snapshot
9.5.1. Brazil Algorithmic Trading Market
9.5.2. Mexico Algorithmic Trading Market
9.5.3. Rest of Latin America Algorithmic Trading Market
9.6. Rest of The World Algorithmic Trading Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. Tradetron (U.S.)
10.2.1.1. Key Information
10.2.1.2. Overview
10.2.1.3. Financial (Subject to Data Availability)
10.2.1.4. Product Summary
10.2.1.5. Recent Developments
10.2.2. Tickblaze LLC (U.S.)
10.2.3. Wyden (U.S.)
10.2.4. TradeStation (U.S.)
10.2.5. InfoReach, Inc. (U.S.)
10.2.6. Symphony (U.S.)
10.2.7. ALGOTRADERS (U.S.)
10.2.8. Argo Software Engineering (U.S.)
10.2.9. FXCM Group (U.S.)
10.2.10. Tata Consultancy Services Limited (U.S.)
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

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