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2021
Algorithmic Trading Market

Algorithmic Trading Market by Component (Solution and Services), Type (Stock Markets, FOREX, ETF, Bonds, Cryptocurrencies, and Others), Deployment Mode (Cloud and On-Premise), and Type of Traders (Institutional Investors, Long-Term Traders, Short-Term Traders, and Retail Investors): Global Opportunity Analysis and Industry Forecast, 2021–2028

A08567
Pages: 242
May 2021 | 2322 Views
   
Author(s) : Vikas Gaikwad , Rachita Rake
Tables: 120
Charts: 66
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COVID-19

Pandemic disrupted the entire world and affected many industries.

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Algorithmic Trading Market Statistics: 2028

The global algorithmic trading market size was valued at $12,143 million in 2020, and is projected to reach $31,494 million by 2028, registering a CAGR of 12.7% from 2021 to 2028. Algorithmic trading or automated trading is a form of automation, in which computer program is used to execute a defined set of instructions or rules that includes the buying or selling of an asset in regards to the varying market data. The defined sets of instructions or rules are based on timing, quantity, price, or any mathematical model. It offers several benefits to market participants such as it executes trades at the best possible prices; simultaneous automated checks on multiple market conditions; trades timed correctly and instantly; and reduced transaction costs due to lack of human intervention.

COVID-19 pandemic has impacted positively on the growth rate of the algorithmic trading market owing to the increased shift towards algorithmic trading for taking the decisions at a very rapid pace by reducing human errors. For instance, Reserve Bank of Australia, in its recent publication stated that the Covid-19 pandemic may have only furthered the industry's shift toward electronic trading. Also, there is upsurge in popularity of High-Frequency Traders (HFT) during the pandemic; thus, fueling the market growth. For instance, Virtu Financial, one of the leading high-speed traders reported $784.5 million in net trading income for the first quarter of 2020.

On the basis of component, the solution segment exhibited the highest growth in the algorithmic trading market share in 2020, and is expected to maintain its dominance in the upcoming years. The demand for algorithmic trading solutions is mainly driven by its benefits such as reduced transaction costs due to lack of human intervention and instant and accurate trade order placement. In addition, the market players are introducing advanced algorithmic trading solutions to serve various needs of their customers. For instance, in September 2019, BNP Paribas introduced an upgraded FX trading platform with real-time analytics and interactive algorithms. However, the services segment is expected to witness the highest growth, due to an extensive adoption of professional services among end users, as it ensures effective functioning of algorithmic trading solution throughout the process.

Algorithmic-Trading-Market

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By deployment mode, the global algorithmic trading market share was dominated by the cloud segment in 2020, and is expected to maintain its dominance in the upcoming years, due to increase in adoption of cloud-based applications by financial institutions to enhance their productivity and efficiency. In addition, the cloud-based algorithmic trading solutions are gaining popularity among the traders as it ensures the effective automation of processes and data maintenance along with cost-friendly management. This factor further propels the growth of the segment during the forecast period. 

North America dominates the algorithmic trading market, owing to a number of factors including huge investments in trading technologies and increase in government support for global trading. In addition, extensive presence of algorithmic trading vendors in the region propels the growth of the market. However, Asia-Pacific is expected to witness highest growth rate during the forecast period, due to heavy investments by public and private sectors to enhance their trading technologies, driving the demand for algorithmic trading solutions to automate trading processes.

Algorithmic Trading Market
By Deployment Mode

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Cloud segment is projected as one of the most lucrative segments.

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The report focuses on the growth prospects, restraints, and algorithmic trading market analysis. The study provides Porter’s five forces analysis of the algorithmic trading industry to understand the impact of various factors such as bargaining power of suppliers, competitive intensity of competitors, threat of new entrants, threat of substitutes, and bargaining power of buyers on the algorithmic trading market trends.

Algorithmic Trading Market
By Type

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Cryptocurrencies segment is projected as one of the most lucrative segments.

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Segment review

The algorithmic trading market is segmented on the basis of component, type, deployment mode, type of traders, and region. On the component, it is categorized into solution and services. On the basis of type, it is classified into stock markets, FOREX, ETF, bonds, cryptocurrencies, and others. As per the deployment mode, it is classified into cloud and on-premise. Depending on type of traders, it is divided into institutional investors, long-term traders, short-term traders, and retail investors. Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.

Algorithmic Trading Market
By Region

2028
North America 
Europe
Asia-pacific
Lamea

Asia-Pacific is projected as one of the most significant region.

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COVID Impact Analysis

The current estimation of 2028 is projected to be higher than pre-COVID-19 estimates. The COVID-19 outbreak has low impact on the growth of the algorithmic trading market, as the adoption of algorithmic trading solutions have increased in the face of unprecedented circumstances. COVID-19 pandemic has significantly fueled the growth rate of the algorithmic trading market, owing to the increased shift toward algo trading for taking the decisions at a very rapid pace by reducing human errors. For instance, Reserve Bank of Australia, in its recent publication stated that the COVID-19 pandemic may have only furthered the industry's shift toward electronic trading. 

In addition, the market players have introduced innovative algorithmic trading products during the pandemic to ensure better serving the increased volumes of   trading. This factor drives the market growth. For instance, in March 2021, Cowen, an American multinational independent investment bank and financial services company launched an algorithmic trading solution to help institutional clients navigate market dynamics caused by increased volumes of retail trading.

Top impacting factors    

The growth of the global algorithmic trading industry is mainly driven by factors such as rise in demand for reliable, fast, and effective order execution; emergence of favorable government regulations; and the need for market surveillance primarily. In addition, rise in demand for reducing the transaction costs fuels the demand for algorithmic trading. However, insufficient risk valuation capabilities may hamper the market growth to some extent. On the other hand, emergence of AI and algorithms in the financial services is expected to provide lucrative opportunities for the market growth during the forecast period. In addition, rise in demand for cloud-based solutions is anticipated to be opportunistic for the algorithmic trading market growth during the forecast period.

Rise in demand for reliable, fast, and effective order execution 

Algorithmic trading is rapidly being used by big brokerage houses as well as institutional investors to cut down on costs associated with trading. This is attributed to the fact that the algorithmic trading enables easier and faster execution of orders, making it attractive for exchanges. In addition, it enables the investors and traders to quickly book profits off small changes in price. Therefore, rise in demand for effective trade drives the growth of the algorithmic trading market, as it enables the user to quickly execute trades.     

Emergence of AI and algorithms in the financial services 

Maximum number of financial services companies are increasing their AI and machine learning adoption to capitalize on the data from digitally driven channels. It is being used by several companies that operate in areas as banking, insurance, and asset management. This has led to the emerging trend of data-driven investments during the last decade. This in turn fueled the demand for high-frequency trading or algorithmic trading. Such AI-driven trading systems analyze massive amounts of data much quicker than people would do it. Thus, AI and algorithms in the financial services are opportunistic for the market growth during the algorithmic trading market forecast period, as it enables innovation in the market.

Key Benefits For Stakeholders

  • This study includes the analysis, algorithmic trading market trends, and future estimations to determine the imminent investment pockets.
  • The report presents information related to key drivers, restraints, and algorithmic trading market opportunity.
  • The algorithmic trading market size is quantitatively analyzed from 2020 to 2028 to highlight the financial competency of the industry.
  • Porter’s five forces analysis illustrates the potency of buyers & suppliers in algorithmic trading market.

Key Market Segments

By Component    

  • Solution
  • Services

By Type

  • Stock Markets
  • FOREX
  • ETF
  • Bonds
  • Cryptocurrencies
  • Others

By Deployment Mode

  • Cloud 
  • On-Premise 

By Type Of Traders 

  • Institutional Investors
  • Long-Term Traders
  • Short-Term Traders
  • Retail Investors

By Region

  • North America
    • U.S.
    • Canada
  • Europe 
    • UK
    • Germany
    • France
    • Spain
    • Rest of Europe
  • Asia-Pacific 
    • China
    • India
    • Japan
    • Australia
    • South Korea
    • Rest of Asia-Pacific
  • LAMEA
    • Latin America 
    • Middle East
    • Africa

Key Market Players

  • 63MOONS
  • Virtu Financial
  • Software AG
  • Refinitiv Ltd.
  • MetaQuotes Software Corp.
  • Symphony Fintech Solutions Pvt Ltd.
  • Argo SE,
  • Tata Consultancy Services
  • Algo Trader AG
  • Tethys

 

CHAPTER 1:INTRODUCTION

1.1.REPORT DESCRIPTION
1.2.KEY BENEFITS FOR STAKEHOLDERS
1.3.KEY MARKET SEGMENTS

1.3.1.Key market players

1.4.RESEARCH METHODOLOGY

1.4.1.Secondary research
1.4.2.Primary research
1.4.3.Analyst tools & models

CHAPTER 2:EXECUTIVE SUMMARY

2.1.KEY FINDINGS

2.1.1.Top impacting factors
2.1.2.Top investment pockets

2.2.CXO PERSPECTIVE

CHAPTER 3:MARKET OVERVIEW

3.1.MARKET DEFINITION AND SCOPE
3.2.KEY FORCES SHAPING THE ALGORITHMIC TRADING MARKET
3.3.MARKET DYNAMICS

3.3.1.Drivers

3.3.1.1.Rise in demand for reliable, fast, and effective order execution
3.3.1.2.Emergence of favorable government regulations
3.3.1.3.The need for market surveillance
3.3.1.4.Rise in demand for reducing the transaction costs

3.3.2.Restraints

3.3.2.1.Insufficient Risk Valuation Capabilities

3.3.3.Opportunities

3.3.3.1.Emergence of AI and algorithms in the financial services
3.3.3.2.Rise in demand for cloud based solutions

3.4.PATENT ANALYSIS

3.4.1.By region (2000-2020)
3.4.2.By applicant

3.5.COVID-19 IMPACT ANALYSIS ON THE ALGORITHMIC TRADING MARKET

3.5.1.Impact on market size
3.5.2.Consumer trends, preferences, and budget impact
3.5.3.Economic impact
3.5.4.Key player strategies to tackle negative impact
3.5.5.Opportunity window

CHAPTER 4:ALGORITHMIC TRADING MARKET, BY COMPONENT

4.1.OVERVIEW
4.2.SOLUTION

4.2.1.Key market trends, growth factors, and opportunities
4.2.2.Market size and forecast, by region
4.2.3.Market analysis, by country

4.3.SERVICES

4.3.1.Key market trends, growth factors, and opportunities
4.3.2.Market size and forecast, by region
4.3.3.Market analysis, by country

CHAPTER 5:ALGORITHMIC TRADING MARKET, BY TYPE

5.1.OVERVIEW
5.2.STOCK MARKETS

5.2.1.Key market trends, growth factors, and opportunities
5.2.2.Market size and forecast, by region
5.2.3.Market analysis, by country

5.3.FOREX

5.3.1.Key market trends, growth factors, and opportunities
5.3.2.Market size and forecast, by region
5.3.3.Market analysis, by country

5.4.ETF

5.4.1.Key market trends, growth factors, and opportunities
5.4.2.Market size and forecast, by region
5.4.3.Market analysis, by country

5.5.BONDS

5.5.1.Key market trends, growth factors, and opportunities
5.5.2.Market size and forecast, by region
5.5.3.Market analysis, by country

5.6.CRYPTOCURRENCIES

5.6.1.Key market trends, growth factors, and opportunities
5.6.2.Market size and forecast, by region
5.6.3.Market analysis, by country

5.7.OTHERS

5.7.1.Key market trends, growth factors, and opportunities
5.7.2.Market size and forecast, by region
5.7.3.Market analysis, by country

CHAPTER 6:ALGORITHMIC TRADING MARKET, BY DEPLOYMENT MODE

6.1.OVERVIEW
6.2.ON-PREMISE

6.2.1.Key market trends, growth factors, and opportunities
6.2.2.Market size and forecast, by region
6.2.3.Market analysis, by country

6.3.CLOUD

6.3.1.Key market trends, growth factors, and opportunities
6.3.2.Market size and forecast, by region
6.3.3.Market analysis, by country

CHAPTER 7:ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS

7.1.OVERVIEW
7.2.INSTITUTIONAL INVESTORS

7.2.1.Key market trends, growth factors, and opportunities
7.2.2.Market size and forecast, by region
7.2.3.Market analysis, by country

7.3.LONG-TERM TRADERS

7.3.1.Key market trends, growth factors, and opportunities
7.3.2.Market size and forecast, by region
7.3.3.Market analysis, by country

7.4.SHORT-TERM TRADERS

7.4.1.Key market trends, growth factors, and opportunities
7.4.2.Market size and forecast, by region
7.4.3.Market analysis, by country

7.5.RETAIL INVESTORS

7.5.1.Key market trends, growth factors, and opportunities
7.5.2.Market size and forecast, by region
7.5.3.Market analysis, by country

CHAPTER 8:ALGORITHMIC TRADING MARKET, BY REGION

8.1.OVERVIEW
8.2.NORTH AMERICA

8.2.1.Key market trends, growth factors, and opportunities
8.2.2.Market size and forecast, by component
8.2.3.Market size and forecast, by type
8.2.4.Market size and forecast, by Type of traders
8.2.5.Market analysis, by country

8.2.5.1.U.S.

8.2.5.1.1.Market size and forecast, by component
8.2.5.1.2.Market size and forecast, by type
8.2.5.1.3.Market size and forecast, by type of traders

8.2.5.2.Canada

8.2.5.2.1.Market size and forecast, by component
8.2.5.2.2.Market size and forecast, by type
8.2.5.2.3.Market size and forecast, by type of traders

8.3.EUROPE

8.3.1.Key market trends, growth factors, and opportunities
8.3.2.Market size and forecast, by component
8.3.3.Market size and forecast, by type
8.3.4.Market size and forecast, by Type of traders
8.3.5.Market analysis, by country

8.3.5.1.Germany

8.3.5.1.1.Market size and forecast, by component
8.3.5.1.2.Market size and forecast, by type
8.3.5.1.3.Market size and forecast, by type of traders

8.3.5.2.UK

8.3.5.2.1.Market size and forecast, by component
8.3.5.2.2.Market size and forecast, by type
8.3.5.2.3.Market size and forecast, by type of traders

8.3.5.3.France

8.3.5.3.1.Market size and forecast, by component
8.3.5.3.2.Market size and forecast, by type
8.3.5.3.3.Market size and forecast, by type of traders

8.3.5.4.Spain

8.3.5.4.1.Market size and forecast, by component
8.3.5.4.2.Market size and forecast, by type
8.3.5.4.3.Market size and forecast, by type of traders

8.3.5.5.Rest of Europe

8.3.5.5.1.Market size and forecast, by component
8.3.5.5.2.Market size and forecast, by type
8.3.5.5.3.Market size and forecast, by type of traders

8.4.ASIA-PACIFIC

8.4.1.Key market trends, growth factors, and opportunities
8.4.2.Market size and forecast, by component
8.4.3.Market size and forecast, by type
8.4.4.Market size and forecast, by Type of traders
8.4.5.Market analysis, by country

8.4.5.1.China

8.4.5.1.1.Market size and forecast, by component
8.4.5.1.2.Market size and forecast, by type
8.4.5.1.3.Market size and forecast, by type of traders

8.4.5.2.India

8.4.5.2.1.Market size and forecast, by component
8.4.5.2.2.Market size and forecast, by type
8.4.5.2.3.Market size and forecast, by type of traders

8.4.5.3.Japan

8.4.5.3.1.Market size and forecast, by component
8.4.5.3.2.Market size and forecast, by type
8.4.5.3.3.Market size and forecast, by type of traders

8.4.5.4.Australia

8.4.5.4.1.Market size and forecast, by component
8.4.5.4.2.Market size and forecast, by type
8.4.5.4.3.Market size and forecast, by type of traders

8.4.5.5.South Korea

8.4.5.5.1.Market size and forecast, by component
8.4.5.5.2.Market size and forecast, by type
8.4.5.5.3.Market size and forecast, by type of traders

8.4.5.6.Rest of Asia-Pacific

8.4.5.6.1.Market size and forecast, by component
8.4.5.6.2.Market size and forecast, by type
8.4.5.6.3.Market size and forecast, by type of traders

8.5.EUROPE

8.5.1.Key market trends, growth factors, and opportunities
8.5.2.Market size and forecast, by component
8.5.3.Market size and forecast, by type
8.5.4.Market size and forecast, by Type of traders
8.5.5.Market analysis, by country

8.5.5.1.Latin America

8.5.5.1.1.Market size and forecast, by component
8.5.5.1.2.Market size and forecast, by type
8.5.5.1.3.Market size and forecast, by type of traders

8.5.5.2.Middle East

8.5.5.2.1.Market size and forecast, by component
8.5.5.2.2.Market size and forecast, by type
8.5.5.2.3.Market size and forecast, by type of traders

8.5.5.3.Africa

8.5.5.3.1.Market size and forecast, by component
8.5.5.3.2.Market size and forecast, by type
8.5.5.3.3.Market size and forecast, by type of traders

CHAPTER 9:COMPETITIVE LANDSCAPE

9.1.KEY PLAYER POSITIONING ANALYSIS, 2020
9.2.TOP WINNING STRATEGIES
9.3.COMPETITIVE DASHBOARD
9.4.KEY DEVELOPMENTS

9.4.1.New product launches
9.4.2.Collaboration
9.4.3.Acquisition
9.4.4.Partnership

CHAPTER 10:COMPANY PROFILE

10.1.63MOONS

10.1.1.Company overview
10.1.2.Key executives
10.1.3.Company snapshot
10.1.4.Product portfolio
10.1.5.Business performance
10.1.6.Key strategic moves and developments

10.2.VIRTU FINANCIAL

10.2.1.Company overview
10.2.2.Key executives
10.2.3.Company snapshot
10.2.4.Product portfolio
10.2.5.Business performance
10.2.6.Key strategic moves and developments

10.3.SOFTWARE AG

10.3.1.Company overview
10.3.2.Key executive
10.3.3.Company snapshot
10.3.4.Product portfolio
10.3.5.R&D expenditure
10.3.6.Business performance
10.3.7.Key strategic moves and developments

10.4.REFINITIV LTD.

10.4.1.Company overview
10.4.2.Key executive
10.4.3.Company snapshot
10.4.4.Operating business segments
10.4.5.Product portfolio
10.4.6.Business performance
10.4.7.Key strategic moves and developments

10.5.METAQUOTES SOFTWARE CORP.

10.5.1.Company overview
10.5.2.Key executive
10.5.3.Company snapshot
10.5.4.Product portfolio
10.5.5.Key strategic moves and developments

10.6.SYMPHONY FINTECH SOLUTIONS PVT LTD.

10.6.1.Company overview
10.6.2.Key executive
10.6.3.Company snapshot
10.6.4.Product portfolio
10.6.5.Key strategic moves and developments

10.7.ARGO SE

10.7.1.Company overview
10.7.2.Key executives
10.7.3.Company snapshot
10.7.4.Product portfolio
10.7.5.Key strategic moves and developments

10.8.TATA CONSULTANCY SERVICES

10.8.1.Company overview
10.8.2.Key executive
10.8.3.Company snapshot
10.8.4.Product portfolio
10.8.5.R&D expenditure
10.8.6.Business performance
10.8.7.Key strategic moves and developments

10.9.ALGO TRADER AG

10.9.1.Company overview
10.9.2.Key executive
10.9.3.Company snapshot
10.9.4.Product portfolio
10.9.5.Key strategic moves and developments

10.10.TETHYS

10.10.1.Company overview
10.10.2.Key Executives
10.10.3.Company snapshot
10.10.4.Product portfolio
10.10.5.Key strategic moves and developments

LIST OF TABLES

TABLE 01.ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 02.ALGORITHMIC TRADING MARKET, BY REGION, 2020–2028 ($MILLION)
TABLE 03.ALGORITHMIC TRADING MARKET FOR SERVICES, BY REGION, 2020–2028 ($MILLION)
TABLE 04.ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 05.ALGORITHMIC TRADING MARKET FOR STOCK MARKETS, BY REGION, 2020–2028 ($MILLION)
TABLE 06.FOREX-BASED ALGORITHMIC TRADING MARKET, BY REGION, 2020–2028 ($MILLION)
TABLE 07.ETF-BASED ALGORITHMIC TRADING MARKET, BY REGION, 2020–2028 ($MILLION)
TABLE 08.BONDS-BASED ALGORITHMIC TRADING MARKET, BY REGION, 2020–2028 ($MILLION)
TABLE 09.BONDS-BASED ALGORITHMIC TRADING MARKET, BY REGION, 2020–2028 ($MILLION)
TABLE 10.OTHERS-BASED ALGORITHMIC TRADING MARKET, BY REGION, 2020–2028 ($MILLION)
TABLE 11.ALGORITHMIC TRADING MARKET, BY DEPLOYMENT MODE, 2020–2028 ($MILLION)
TABLE 12.ALGORITHMIC TRADING MARKET FOR ON-PREMISE, BY REGION, 2020–2028 ($MILLION)
TABLE 13.ALGORITHMIC TRADING MARKET FOR CLOUD, BY REGION, 2020–2028 ($MILLION)
TABLE 14.ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 15.ALGORITHMIC TRADING MARKET FOR INSTITUTIONAL INVESTORS, BY REGION, 2020–2028 ($MILLION)
TABLE 16.ALGORITHMIC TRADING MARKET FOR LONG-TERM TRADERS, BY REGION, 2020–2028 ($MILLION)
TABLE 17.ALGORITHMIC TRADING MARKET FOR SHORT-TERM TRADERS, BY REGION, 2020–2028 ($MILLION)
TABLE 18.ALGORITHMIC TRADING MARKET FOR GOVERNMENT AND EDUACTION, BY REGION, 2020–2028 ($MILLION)
TABLE 19.ALGORITHMIC TRADING MARKET FOR IT AND TELECOM, BY REGION, 2020–2028 ($MILLION)
TABLE 20.ALGORITHMIC TRADING MARKET, BY REGION, 2020–2028 ($MILLION)
TABLE 21.NORTH AMERICA ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 22.NORTH AMERICA ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 23.NORTH AMERICA ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 24.NORTH AMERICA ALGORITHMIC TRADING MARKET, BY COUNTRY, 2020–2028 ($MILLION)
TABLE 25.U.S. ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 26.U.S. ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 27.U.S. ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 28.CANADA ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 29.CANADA ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 30.CANADA ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 31.EUROPE ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 32.EUROPE ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 33.EUROPE ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 34.EUROPE ALGORITHMIC TRADING MARKET, BY COUNTRY, 2020–2028 ($MILLION)
TABLE 35.GERMANY ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 36.GERMANY ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 37.GERMANY ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 38.UK ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 39.UK ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 40.UK ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 41.FRANCE ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 42.FRANCE ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 43.FRANCE ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 44.SPAIN ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 45.SPAIN ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 46.SPAIN ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 47.REST OF EUROPE ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 48.REST OF EUROPE ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 49.REST OF EUROPE ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 50.ASIA-PACIFIC ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 51.ASIA-PACIFIC ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 52.ASIA-PACIFIC ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 53.ASIA-PACIFIC ALGORITHMIC TRADING MARKET, BY COUNTRY, 2020–2028 ($MILLION)
TABLE 54.CHINA ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 55.CHINA ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 56.CHINA ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 57.INDIA ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 58.INDIA ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 59.INDIA ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 60.JAPAN ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 61.JAPAN ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 62.JAPAN ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 63.AUSTRALIA ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 64.AUSTRALIA ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 65.AUSTRALIA ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 66.SOUTH KOREA ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 67.SOUTH KOREA ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 68.SOUTH KOREA ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 69.REST OF ASIA-PACIFIC ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 70.REST OF ASIA-PACIFIC ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 71.REST OF ASIA-PACIFIC ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 72.EUROPE ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 73.EUROPE ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 74.EUROPE ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 75.EUROPE ALGORITHMIC TRADING MARKET, BY COUNTRY, 2020–2028 ($MILLION)
TABLE 76.LATIN AMERICA ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 77.LATIN AMERICA ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 78.LATIN AMERICA ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 79.MIDDLE EAST ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 80.MIDDLE EAST ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 81.MIDDLE EAST ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 82.AFRICA ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
TABLE 83.AFRICA ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
TABLE 84.AFRICA ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
TABLE 85.KEY NEW PRODUCT LAUNCHES (2017-2020)
TABLE 86.COLLABORATION (2017-2020)
TABLE 87.ACQUISTION (2017-2020)
TABLE 88.PARTNERSHIP (2017-2020)
TABLE 89.63 MOONS: KEY EXECUTIVES
TABLE 90.63 MOONS: COMPANY SNAPSHOT
TABLE 91.63 MOONS: PRODUCT PORTFOLIO
TABLE 92.VIRTU FINANCIAL.: KEY EXECUTIVES
TABLE 93.VIRTU FINANCIAL: COMPANY SNAPSHOT
TABLE 94.VIRTU FINANCIAL: PRODUCT PORTFOLIO
TABLE 95.SOFTWARE AG: KEY EXECUTIVE
TABLE 96.SOFTWARE AG: COMPANY SNAPSHOT
TABLE 97.SOFTWARE AG: PRODUCT PORTFOLIO
TABLE 98.REFINITIV LTD.: KEY EXECUTIVE
TABLE 99.REFINITIV LTD.: COMPANY SNAPSHOT
TABLE 100.LONDON STOCK EXCHANGE GROUP: OPERATING SEGMENTS
TABLE 101.REFINITIV LTD.: PRODUCT PORTFOLIO
TABLE 102.METAQUOTES SOFTWARE CORPORATION: KEY EXECUTIVE
TABLE 103.METAQUOTES SOFTWARE CORPORATION: COMPANY SNAPSHOT
TABLE 104.METAQUOTES SOFTWARE CORPORATION: PRODUCT PORTFOLIO
TABLE 105.SYMPHONY FINTECH SOLUTIONS PVT LTD.: KEY EXECUTIVE
TABLE 106.SYMPHONY FINTECH SOLUTIONS PVT LTD.: COMPANY SNAPSHOT
TABLE 107.SYMPHONY FINTECH SOLUTIONS PVT LTD.: PRODUCT PORTFOLIO
TABLE 108.SYMPHONY FINTECH SOLUTIONS PVT LTD.: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 109.ARGO SE: KEY EXECUTIVES
TABLE 110.ARGO SE: COMPANY SNAPSHOT
TABLE 111.ARGO SE: PRODUCT PORTFOLIO
TABLE 112.TATA CONSULTANCY SERVICES: KEY EXECUTIVE
TABLE 113.TATA CONSULTANCY SERVICES: COMPANY SNAPSHOT
TABLE 114.TATA CONSULTANCY SERVICES: PRODUCT PORTFOLIO
TABLE 115.ALGO TRADER: KEY EXECUTIVE
TABLE 116.ALGO TRADER AG: COMPANY SNAPSHOT
TABLE 117.ALGO TRADER AG: PRODUCT PORTFOLIO
TABLE 118.TETHYS TECHNOLOGY, INC: KEY EXECUTIVES
TABLE 119.TETHYS TECHNOLOGY, INC. COMPANY SNAPSHOT
TABLE 120.TETHYS TECHNOLOGY, INC.: PRODUCT PORTFOLIO

LIST OF FIGURES

FIGURE 01.KEY MARKET SEGMENTS
FIGURE 02.ALGORITHMIC TRADING MARKET SNAPSHOT, BY SEGMENT, 2020–2028
FIGURE 03.ALGORITHMIC TRADING MARKET SNAPSHOT, BY COUNTRY, 2020–2028
FIGURE 04.TOP IMPACTING FACTORS
FIGURE 05.TOP INVESTMENT POCKETS
FIGURE 06.MODERATE-TO-HIGH BARGAINING POWER OF SUPPLIERS
FIGURE 07.MODERATE-TO-HIGH BARGAINING POWER OF BUYERS
FIGURE 08.MODERATE THREAT OF SUBSTITUTES
FIGURE 09.MODERATE-TO-HIGH THREAT OF NEW ENTRANTS
FIGURE 10.HIGH COMPETITIVE RIVALRY
FIGURE 11.MARKET DYNAMICS: GLOBAL ALGORITHMIC TRADING MARKET
FIGURE 12.PATENT ANALYSIS, BY REGION
FIGURE 13.PATENT ANALYSIS, BY APPLICANT
FIGURE 14.ALGORITHMIC TRADING MARKET, BY COMPONENT, 2020–2028 ($MILLION)
FIGURE 15.COMPARATIVE SHARE ANALYSIS OF ALGORITHMIC TRADING MARKET, BY COUNTRY,  2020 & 2028 (%)
FIGURE 16.COMPARATIVE SHARE ANALYSIS OF ALGORITHMIC TRADING MARKET FOR SERVICES, BY COUNTRY,  2020 & 2028 (%)
FIGURE 17.ALGORITHMIC TRADING MARKET, BY TYPE, 2020–2028 ($MILLION)
FIGURE 18.COMPARATIVE SHARE ANALYSIS OF STOCK MARKETS ALGORITHMIC TRADING MARKET, BY COUNTRY,  2020 & 2028 (%)
FIGURE 19.COMPARATIVE SHARE ANALYSIS OF FOREX-BASED ALGORITHMIC TRADING MARKET, BY COUNTRY,  2020 & 2028 (%)
FIGURE 20.COMPARATIVE SHARE ANALYSIS OF ETF-BASED ALGORITHMIC TRADING MARKET, BY COUNTRY,  2020 & 2028 (%)
FIGURE 21.COMPARATIVE SHARE ANALYSIS OF BONDS-BASED ALGORITHMIC TRADING MARKET, BY COUNTRY,  2020 & 2028 (%)
FIGURE 22.COMPARATIVE SHARE ANALYSIS OF BONDS-BASED ALGORITHMIC TRADING MARKET, BY COUNTRY,  2020 & 2028 (%)
FIGURE 23.COMPARATIVE SHARE ANALYSIS OF OTHERS-BASED ALGORITHMIC TRADING MARKET, BY COUNTRY,  2020 & 2028 (%)
FIGURE 24.ALGORITHMIC TRADING MARKET, BY DEPLOYMENT MODE, 2020–2028 ($MILLION)
FIGURE 25.COMPARATIVE SHARE ANALYSIS OF STOCK MARKETS ALGORITHMIC TRADING MARKET FOR ON-PREMISE, BY COUNTRY,  2020 & 2028 (%)
FIGURE 26.COMPARATIVE SHARE ANALYSIS OF ALGORITHMIC TRADING MARKET FOR CLOUD, BY COUNTRY,  2020 & 2028 (%)
FIGURE 27.ALGORITHMIC TRADING MARKET, BY TYPE OF TRADERS, 2020–2028 ($MILLION)
FIGURE 28.COMPARATIVE SHARE ANALYSIS OF ALGORITHMIC TRADING MARKET FOR INSTITUTIONAL INVESTORS, BY COUNTRY,  2020 & 2028 (%)
FIGURE 29.COMPARATIVE SHARE ANALYSIS OF ALGORITHMIC TRADING MARKET FOR LONG-TERM TRADERS, BY COUNTRY,  2020 & 2028 (%)
FIGURE 30.COMPARATIVE SHARE ANALYSIS OF ALGORITHMIC TRADING MARKET FOR SHORT-TERM TRADERS,  BY COUNTRY, 2020 & 2028 (%)
FIGURE 31.COMPARATIVE SHARE ANALYSIS OF ALGORITHMIC TRADING MARKET FOR GOVERNMENT AND EDUACTION, BY COUNTRY, 2020 & 2028 (%)
FIGURE 32.COMPARATIVE SHARE ANALYSIS OF ALGORITHMIC TRADING MARKET FOR TRANSPORT & LOGISTIC, BY COUNTRY,  2020 & 2028 (%)
FIGURE 33.U.S. ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 34.CANADA ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 35.GERMANY ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 36.UK ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 37.FRANCE ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 38.SPAIN ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 39.REST OF EUROPE ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 40.CHINA ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 41.INDIA ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 42.JAPAN ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 43.AUSTRALIA ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 44.SOUTH KOREA ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 45.REST OF ASIA-PACIFIC ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 46.LATIN AMERICA ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 47.MIDDLE EAST ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 48.AFRICA ALGORITHMIC TRADING MARKET, 2020–2028 ($MILLION)
FIGURE 49.KEY PLAYER POSITIONING ANALYSIS: GLOBAL ALGORITHMIC TRADING MARKET
FIGURE 50.TOP WINNING STRATEGIES, BY YEAR, 2017-2021
FIGURE 51.TOP WINNING STRATEGIES, BY DEVELOPMENT, 2017-2021
FIGURE 52.TOP WINNING STRATEGIES, BY COMPANY, 2017-2021
FIGURE 53.COMPETITIVE DASHBOARD
FIGURE 54.COMPETITIVE DASHBOARD
FIGURE 55.COMPETITIVE HEATMAP OF KEY PLAYERS
FIGURE 56.63 MOONS: REVENUE, 2018–2020 ($MILLION)
FIGURE 57.63 MOONS: REVENUE SHARE BY REGION, 2020 (%)
FIGURE 58.VIRTU FINANCIAL: REVENUE, 2018–2020 ($MILLION)
FIGURE 59.VIRTU FINANCIAL: REVENUE SHARE BY REGION, 2019 (%)
FIGURE 60.R&D EXPENDITURE, 2018-2020 ($MILLION)
FIGURE 61.SOFTWARE AG: REVENUE, 2018–2020 ($MILLION)
FIGURE 62.LONDON STOCK EXCHANGE GROUP: REVENUE, 2018–2020 ($MILLION)
FIGURE 63.LONDON STOCK EXCHANGE GROUP: REVENUE SHARE BY SEGMENT, 2020 (%)
FIGURE 64.R&D EXPENDITURE, 2018–2020 ($MILLION)
FIGURE 65.TATA CONSULTANCY SERVICES: REVENUE, 2018–2020 ($MILLION)
FIGURE 66.TATA CONSULTANCY SERVICES: REVENUE SHARE BY REGION, 2020 (%)

 
 

The algorithmic trading market is going through enormous transformation and growth. Algorithmic trading has become the emerging technology for financial institutions to gain an edge over other market participants. There is very less possibility that the traders are profitable; however, algorithmic trading has improved such odds through better strategy testing, design, and execution; thus, increasing the profitability. More number of investors are adopting algorithmic trading technology to bring superior efficiency to financial markets.

Moreover, most of the investors and regulators are inclining toward algorithmic as well as high-frequency trading (HFT). Over the past few years, HFT has become the most pervasive use of the algorithmic trading technology, especially among large financial institutions. HFT enables the large volumes of shares to be bought and sold automatically at very high speeds. HFT is anticipated to continuously grow and become the dominant form of algorithmic trading in the upcoming years. This is attributed to its huge popularity among big insurers, banks, and hedge funds, owing to its ability to place large volumes of orders at high speed across different markets based on a number of algorithmic trading strategies.

COVID-19 pandemic has significantly fueled the growth rate of the algorithmic trading market, owing to increase in shift toward algorithmic trading. For instance, the Reserve Bank of Australia, in its recent publication stated that the COVID-19 pandemic may have only furthered the industry's shift toward electronic trading.

Furthermore, the algorithmic trading market is competitive and comprises number of regional and global vendors competing based on factors such as cost of solutions, reliability, and support services. The growth of the market is impacted by rapid advances in the electronic trading offerings, whereas the vendor performance is impacted by COVID-19 conditions and industry development. Moreover, vendors operating in the market are offering advanced algorithmic trading products and services to improve the experience of traders using an algorithmic trading platform. 
 

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