[250 Pages Report] The global automated algo trading market is anticipated to grow at a stupendous CAGR of around 10.6% during the forecast period from 2022 to 2032. Growth is attributable to the rising popularity of automated algo trading among end users like personal investors and credit unions.
| Report Attribute | Details |
|---|---|
| Automated Algo Trading Market Projected Growth Rate (2022 to 2032) | 10.6% CAGR |
| Estimated Base Year Value (2021) | US$ 13,260.4 Million |
| Expected Market Value (2022) | US$ 14,520.1 Million |
| Expected Market Value (2032) | US$ 39,715.3 Million |
The penetration of modern technologies is rapidly changing the way of traditional investment models or trading methods by automating all trading related processes. Latest trading platforms like automated algo trading have reduced the transitional costs and human errors, and significantly made the whole trading process cheaper and less cumbersome.
Automated algo trading uses a computer program that follows a defined set of instructions to place a trade (buying or selling of an asset). The defined set of instructions are based on quantity, price, timing or any other mathematical model. It initiates profit opportunities at great frequency and speed, by programming the computers to follow a specific set of calculations, guidelines, and instructions.
Rapid shift towards automated algo trading for taking the decisions at a very fast pace by reducing human errors is emerging as a key factor accelerating the growth of automated algo trading market.
Automated algo trading makes trading more systematic by eliminating human trader’s emotional impact on it. These platforms execute trading at the best prices and allow continuous monitoring of the trade market throughout the day and night. Adoption of automated algo trading therefore diversifies trading and allows businesses to make sure that there are no missed opportunities. In automated algo trading, the algorithms stick to an unwavering trading plan involving the trade’s price, timing, quantity and other mathematical parameters.
With growing penetration of advanced trading technologies across developed and developing economies and increasing participation of international markets, the global automated algo trading market is forecast to grow at prolific pace during the forecast period.
The liquidity in equity market due to integration of financial markets is a major factor that would drive the automated algo trading market during the forecast period.
Various end users including personal investors, credit unions, insurance firms, prime brokers, and multi-national investment banks are vigorously investing in adopting and upgrading the automated algo trading platforms. This will continue to boost market growth in the forthcoming years.
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The robust expansion of automated algo trading market is attributable to the growing demand for fast, effective, and reliable order execution, favorable government regulations, reducing transactional costs, and rising demand for market surveillance.
During the last few years, demand for automated algo trading has risen at an incredible pace and the trend is likely to continue during the forecast period. It offers various advantages by executing trades at best possible prices and reducing transaction costs as well as manual errors.
Automated algo trading is being increasingly used by leading brokerage houses, personal investors, credit unions, insurance firms etc. to cut down costs associated with trading. Adoption of automated algo trading enables faster and easier execution of orders, which makes it ideal for exchanges. It is especially ideal for situations where a human trader is not able to handle enormous numbers of trading.
Similarly, rising penetration of artificial intelligence (AI) and machine learning across financial services companies and other trading businesses is expected to generate lucrative growth opportunities within the global automated algo trading market during the assessment period.
Additionally, introduction of advanced automated algo trading platforms by market players to serve various needs of end users is anticipated to further expand the size of automated algo trading market in future.
Despite the growing popularity of automated algo trading, there are various factors that are likely to challenge market growth during the forecast period. Some of these factors are the increase in the amount of data to be processed and certain risks such as sudden system failure, erroneous network connectivity, imperfect algorithms, and time lags in order and executions, associated with automated algo trading solutions.
Moreover, lack of availability of modern facilities and poor awareness about automated algo trading across various emerging nations is also limiting the market growth.
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As per FMI, North America was the largest market for automated algo trading in 2022 and is expected to retain its dominant position during the forecast period, owing to the owing to the increasing investments in trading technologies, heavy presence of leading market vendors, favorable government support, and significant penetration of automated algo trading solutions in the financial markets.
Countries like the United States are becoming the ideal destinations for automated algo trading vendors due to growing adoption of modern trading technologies and increase in the number of end users.
According to Future Market Insights, the Asia Pacific automated algo trading market is expected to grow at a healthy CAGR during the forecast period from 2022 to 2032, owing to the rapid economic boom in countries like China and India, growing consumer awareness about the benefits of automated algo trading, and increasing investments by public and private sectors for enhancing their trading technologies.
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Some of the key participants present in the global automated algo trading market include Vela, AlgoTerminal LLC, AlgoTrader GmbH, Cloud9Trader, Quantopian, InfoReach, Inc., Trading Technologies International, Inc., QuantConnect, Tethys Technology, and Citadel, among others.
These leading market players are constantly introducing innovative automated algo trading solutions to help end users in smoothly running their businesses. Besides this, they have adopted growth strategies such as mergers, acquisitions, and partnerships to expand their global footprint.
| Report Attribute | Details |
|---|---|
| Growth Rate | CAGR of 10.6% from 2022 to 2032 |
| Base Year for Estimation | 2021 |
| Historical Data | 2015 to 2020 |
| Forecast Period | 2022 to 2032 |
| Quantitative Units | Revenue in USD Million and CAGR from 2022 to 2032 |
| Report Coverage | Revenue Forecast, Volume Forecast, Company Ranking, Competitive Landscape, Growth Factors, Trends and Pricing Analysis |
| Segments Covered |
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| Regions Covered |
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| Key Countries Profiled |
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| Key Companies Profiled |
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| Customization | Available Upon Request |
FMI projects the global automated algo trading market to expand at around 10.5% to 11.0% CAGR between 2022 and 2032.
North America will continue to remain the most lucrative market for automated algo trading during the forecast period.
Vela, AlgoTerminal LLC, AlgoTrader GmbH, Cloud9Trader, and Quantopian, InfoReach, Inc. are some prominent market players operating in the automated algo trading market.
1. Executive Summary
1.1. Global Market Outlook
1.2. Demand-side Trends
1.3. Supply-side Trends
1.4. Technology Roadmap Analysis
1.5. Analysis and Recommendations
2. Market Overview
2.1. Market Coverage / Taxonomy
2.2. Market Definition / Scope / Limitations
3. Market Background
3.1. Market Dynamics
3.1.1. Drivers
3.1.2. Restraints
3.1.3. Opportunity
3.1.4. Trends
3.2. Scenario Forecast
3.2.1. Demand in Optimistic Scenario
3.2.2. Demand in Likely Scenario
3.2.3. Demand in Conservative Scenario
3.3. Opportunity Map Analysis
3.4. Investment Feasibility Matrix
3.5. Value Chain Analysis
3.5.1. Profit Margin Analysis
3.5.2. Service Providers
3.6. PESTLE and Porter’s Analysis
3.7. Regulatory Landscape
3.7.1. By Key Regions
3.7.2. By Key Countries
3.8. Regional Parent Market Outlook
4. Global Market Analysis 2017-2021 and Forecast, 2022-2032
4.1. Historical Market Size Value (US$ Mn) Analysis, 2017-2021
4.2. Current and Future Market Size Value (US$ Mn) Projections, 2022-2032
4.2.1. Y-o-Y Growth Trend Analysis
4.2.2. Absolute $ Opportunity Analysis
5. Global Market Analysis 2017-2021 and Forecast 2022-2032, By Solution
5.1. Introduction / Key Findings
5.2. Historical Market Size Value (US$ Mn) Analysis By Solution, 2017-2021
5.3. Current and Future Market Size Value (US$ Mn) Analysis and Forecast By Solution, 2022-2032
5.3.1. Automated Trading Platforms
5.3.2. Algorithmic Trading Bots (API)
5.3.3. Services
5.4. Y-o-Y Growth Trend Analysis By Solution, 2017-2021
5.5. Absolute $ Opportunity Analysis By Solution, 2022-2032
Deep-dive segmentation will be available in the sample on request
6. Global Market Analysis 2017-2021 and Forecast 2022-2032, By Trading Application
6.1. Introduction / Key Findings
6.2. Historical Market Size Value (US$ Mn) Analysis By Trading Application, 2017-2021
6.3. Current and Future Market Size Value (US$ Mn) Analysis and Forecast By Trading Application, 2022-2032
6.3.1. Forex
6.3.2. Stocks
6.3.3. Commodities
6.3.4. Bonds
6.3.5. Cryptocurrencies
6.4. Y-o-Y Growth Trend Analysis By Trading Application, 2017-2021
6.5. Absolute $ Opportunity Analysis By Trading Application, 2022-2032
Deep-dive segmentation will be available in the sample on request
7. Global Market Analysis 2017-2021 and Forecast 2022-2032, By End User
7.1. Introduction / Key Findings
7.2. Historical Market Size Value (US$ Mn) Analysis By End User, 2017-2021
7.3. Current and Future Market Size Value (US$ Mn) Analysis and Forecast By End User, 2022-2032
7.3.1. Retail Traders
7.3.2. Institutional Traders
7.3.3. Asset Management Company (AMC)
7.3.4. Others
7.4. Y-o-Y Growth Trend Analysis By End User, 2017-2021
7.5. Absolute $ Opportunity Analysis By End User, 2022-2032
Deep-dive segmentation will be available in the sample on request
8. Global Market Analysis 2017-2021 and Forecast 2022-2032, By Region
8.1. Introduction
8.2. Historical Market Size Value (US$ Mn) Analysis By Region, 2017-2021
8.3. Current Market Size Value (US$ Mn) Analysis and Forecast By Region, 2022-2032
8.3.1. North America
8.3.2. Latin America
8.3.3. Europe
8.3.4. East Asia
8.3.5. South Asia & Pacific
8.3.6. MEA
8.4. Market Attractiveness Analysis By Region
9. North America Market Analysis 2017-2021 and Forecast 2022-2032, By Country
9.1. Historical Market Size Value (US$ Mn) Trend Analysis By Market Taxonomy, 2017-2021
9.2. Market Size Value (US$ Mn) Forecast By Market Taxonomy, 2022-2032
9.2.1. By Country
9.2.1.1. U.S.
9.2.1.2. Canada
9.2.2. By Solution
9.2.3. By Trading Application
9.2.4. By End User
9.3. Market Attractiveness Analysis
9.3.1. By Country
9.3.2. By Solution
9.3.3. By Trading Application
9.3.4. By End User
9.4. Key Takeaways
10. Latin America Market Analysis 2017-2021 and Forecast 2022-2032, By Country
10.1. Historical Market Size Value (US$ Mn) Trend Analysis By Market Taxonomy, 2017-2021
10.2. Market Size Value (US$ Mn) Forecast By Market Taxonomy, 2022-2032
10.2.1. By Country
10.2.1.1. Mexico
10.2.1.2. Brazil
10.2.1.3. Rest of Latin America
10.2.2. By Solution
10.2.3. By Trading Application
10.2.4. By End User
10.3. Market Attractiveness Analysis
10.3.1. By Country
10.3.2. By Solution
10.3.3. By Trading Application
10.3.4. By End User
10.4. Key Takeaways
11. Europe Market Analysis 2017-2021 and Forecast 2022-2032, By Country
11.1. Historical Market Size Value (US$ Mn) Trend Analysis By Market Taxonomy, 2017-2021
11.2. Market Size Value (US$ Mn) Forecast By Market Taxonomy, 2022-2032
11.2.1. By Country
11.2.1.1. Germany
11.2.1.2. Italy
11.2.1.3. France
11.2.1.4. U.K.
11.2.1.5. Spain
11.2.1.6. BENELUX
11.2.1.7. Russia
11.2.1.8. Rest of Europe
11.2.2. By Solution
11.2.3. By Trading Application
11.2.4. By End User
11.3. Market Attractiveness Analysis
11.3.1. By Country
11.3.2. By Solution
11.3.3. By Trading Application
11.3.4. By End User
11.4. Key Takeaways
12. East Asia Market Analysis 2017-2021 and Forecast 2022-2032, By Country
12.1. Historical Market Size Value (US$ Mn) Trend Analysis By Market Taxonomy, 2017-2021
12.2. Market Size Value (US$ Mn) Forecast By Market Taxonomy, 2022-2032
12.2.1. By Country
12.2.1.1. China
12.2.1.2. Japan
12.2.1.3. South Korea
12.2.2. By Solution
12.2.3. By Trading Application
12.2.4. By End User
12.3. Market Attractiveness Analysis
12.3.1. By Country
12.3.2. By Solution
12.3.3. By Trading Application
12.3.4. By End User
12.4. Key Takeaways
13. South Asia & Pacific Market Analysis 2017-2021 and Forecast 2022-2032, By Country
13.1. Historical Market Size Value (US$ Mn) Trend Analysis By Market Taxonomy, 2017-2021
13.2. Market Size Value (US$ Mn) Forecast By Market Taxonomy, 2022-2032
13.2.1. By Country
13.2.1.1. India
13.2.1.2. ASEAN
13.2.1.3. Australia and New Zealand
13.2.1.4. Rest of South Asia & Pacific
13.2.2. By Solution
13.2.3. By Trading Application
13.2.4. By End User
13.3. Market Attractiveness Analysis
13.3.1. By Country
13.3.2. By Solution
13.3.3. By Trading Application
13.3.4. By End User
13.4. Key Takeaways
14. MEA Market Analysis 2017-2021 and Forecast 2022-2032, By Country
14.1. Historical Market Size Value (US$ Mn) Trend Analysis By Market Taxonomy, 2017-2021
14.2. Market Size Value (US$ Mn) Forecast By Market Taxonomy, 2022-2032
14.2.1. By Country
14.2.1.1. GCC Countries
14.2.1.2. Turkey
14.2.1.3. South Africa
14.2.1.4. Rest of MEA
14.2.2. By Solution
14.2.3. By Trading Application
14.2.4. By End User
14.3. Market Attractiveness Analysis
14.3.1. By Country
14.3.2. By Solution
14.3.3. By Trading Application
14.3.4. By End User
14.4. Key Takeaways
15. Key Countries Market Analysis
15.1. U.S.
15.1.1. Pricing Analysis
15.1.2. Market Share Analysis, 2021
15.1.2.1. By Solution
15.1.2.2. By Trading Application
15.1.2.3. By End User
15.2. Canada
15.2.1. Pricing Analysis
15.2.2. Market Share Analysis, 2021
15.2.2.1. By Solution
15.2.2.2. By Trading Application
15.2.2.3. By End User
15.3. Mexico
15.3.1. Pricing Analysis
15.3.2. Market Share Analysis, 2021
15.3.2.1. By Solution
15.3.2.2. By Trading Application
15.3.2.3. By End User
15.4. Brazil
15.4.1. Pricing Analysis
15.4.2. Market Share Analysis, 2021
15.4.2.1. By Solution
15.4.2.2. By Trading Application
15.4.2.3. By End User
15.5. Germany
15.5.1. Pricing Analysis
15.5.2. Market Share Analysis, 2021
15.5.2.1. By Solution
15.5.2.2. By Trading Application
15.5.2.3. By End User
15.6. Italy
15.6.1. Pricing Analysis
15.6.2. Market Share Analysis, 2021
15.6.2.1. By Solution
15.6.2.2. By Trading Application
15.6.2.3. By End User
15.7. France
15.7.1. Pricing Analysis
15.7.2. Market Share Analysis, 2021
15.7.2.1. By Solution
15.7.2.2. By Trading Application
15.7.2.3. By End User
15.8. U.K.
15.8.1. Pricing Analysis
15.8.2. Market Share Analysis, 2021
15.8.2.1. By Solution
15.8.2.2. By Trading Application
15.8.2.3. By End User
15.9. Spain
15.9.1. Pricing Analysis
15.9.2. Market Share Analysis, 2021
15.9.2.1. By Solution
15.9.2.2. By Trading Application
15.9.2.3. By End User
15.10. BENELUX
15.10.1. Pricing Analysis
15.10.2. Market Share Analysis, 2021
15.10.2.1. By Solution
15.10.2.2. By Trading Application
15.10.2.3. By End User
15.11. Russia
15.11.1. Pricing Analysis
15.11.2. Market Share Analysis, 2021
15.11.2.1. By Solution
15.11.2.2. By Trading Application
15.11.2.3. By End User
15.12. China
15.12.1. Pricing Analysis
15.12.2. Market Share Analysis, 2021
15.12.2.1. By Solution
15.12.2.2. By Trading Application
15.12.2.3. By End User
15.13. Japan
15.13.1. Pricing Analysis
15.13.2. Market Share Analysis, 2021
15.13.2.1. By Solution
15.13.2.2. By Trading Application
15.13.2.3. By End User
15.14. South Korea
15.14.1. Pricing Analysis
15.14.2. Market Share Analysis, 2021
15.14.2.1. By Solution
15.14.2.2. By Trading Application
15.14.2.3. By End User
15.15. India
15.15.1. Pricing Analysis
15.15.2. Market Share Analysis, 2021
15.15.2.1. By Solution
15.15.2.2. By Trading Application
15.15.2.3. By End User
15.16. ASEAN
15.16.1. Pricing Analysis
15.16.2. Market Share Analysis, 2021
15.16.2.1. By Solution
15.16.2.2. By Trading Application
15.16.2.3. By End User
15.17. Australia and New Zealand
15.17.1. Pricing Analysis
15.17.2. Market Share Analysis, 2021
15.17.2.1. By Solution
15.17.2.2. By Trading Application
15.17.2.3. By End User
15.18. GCC Countries
15.18.1. Pricing Analysis
15.18.2. Market Share Analysis, 2021
15.18.2.1. By Solution
15.18.2.2. By Trading Application
15.18.2.3. By End User
15.19. Turkey
15.19.1. Pricing Analysis
15.19.2. Market Share Analysis, 2021
15.19.2.1. By Solution
15.19.2.2. By Trading Application
15.19.2.3. By End User
15.20. South Africa
15.20.1. Pricing Analysis
15.20.2. Market Share Analysis, 2021
15.20.2.1. By Solution
15.20.2.2. By Trading Application
15.20.2.3. By End User
16. Market Structure Analysis
16.1. Competition Dashboard
16.2. Competition Benchmarking
16.3. Market Share Analysis of Top Players
16.3.1. By Regional
16.3.2. By Solution
16.3.3. By Trading Application
16.3.4. By End User
17. Competition Analysis
17.1. Competition Deep Dive
17.1.1. Alpha Novae Ltd
17.1.1.1. Overview
17.1.1.2. Product Portfolio
17.1.1.3. Profitability by Market Segments
17.1.1.4. Sales Footprint
17.1.1.5. Strategy Overview
17.1.1.5.1. Marketing Strategy
17.1.1.5.2. Product Strategy
17.1.1.5.3. Channel Strategy
17.1.2. AlgoTrader
17.1.2.1. Overview
17.1.2.2. Product Portfolio
17.1.2.3. Profitability by Market Segments
17.1.2.4. Sales Footprint
17.1.2.5. Strategy Overview
17.1.2.5.1. Marketing Strategy
17.1.2.5.2. Product Strategy
17.1.2.5.3. Channel Strategy
17.1.3. Inteligex LLC
17.1.3.1. Overview
17.1.3.2. Product Portfolio
17.1.3.3. Profitability by Market Segments
17.1.3.4. Sales Footprint
17.1.3.5. Strategy Overview
17.1.3.5.1. Marketing Strategy
17.1.3.5.2. Product Strategy
17.1.3.5.3. Channel Strategy
17.1.4. Trading Technologies International, Inc.
17.1.4.1. Overview
17.1.4.2. Product Portfolio
17.1.4.3. Profitability by Market Segments
17.1.4.4. Sales Footprint
17.1.4.5. Strategy Overview
17.1.4.5.1. Marketing Strategy
17.1.4.5.2. Product Strategy
17.1.4.5.3. Channel Strategy
17.1.5. SquareOff
17.1.5.1. Overview
17.1.5.2. Product Portfolio
17.1.5.3. Profitability by Market Segments
17.1.5.4. Sales Footprint
17.1.5.5. Strategy Overview
17.1.5.5.1. Marketing Strategy
17.1.5.5.2. Product Strategy
17.1.5.5.3. Channel Strategy
17.1.6. Greeksoft Technology
17.1.6.1. Overview
17.1.6.2. Product Portfolio
17.1.6.3. Profitability by Market Segments
17.1.6.4. Sales Footprint
17.1.6.5. Strategy Overview
17.1.6.5.1. Marketing Strategy
17.1.6.5.2. Product Strategy
17.1.6.5.3. Channel Strategy
17.1.7. NinjaTrader, LLC
17.1.7.1. Overview
17.1.7.2. Product Portfolio
17.1.7.3. Profitability by Market Segments
17.1.7.4. Sales Footprint
17.1.7.5. Strategy Overview
17.1.7.5.1. Marketing Strategy
17.1.7.5.2. Product Strategy
17.1.7.5.3. Channel Strategy
17.1.8. AvaTrade
17.1.8.1. Overview
17.1.8.2. Product Portfolio
17.1.8.3. Profitability by Market Segments
17.1.8.4. Sales Footprint
17.1.8.5. Strategy Overview
17.1.8.5.1. Marketing Strategy
17.1.8.5.2. Product Strategy
17.1.8.5.3. Channel Strategy
17.1.9. Kx Systems, Inc.
17.1.9.1. Overview
17.1.9.2. Product Portfolio
17.1.9.3. Profitability by Market Segments
17.1.9.4. Sales Footprint
17.1.9.5. Strategy Overview
17.1.9.5.1. Marketing Strategy
17.1.9.5.2. Product Strategy
17.1.9.5.3. Channel Strategy
17.1.10. Flip Investor, Inc.
17.1.10.1. Overview
17.1.10.2. Product Portfolio
17.1.10.3. Profitability by Market Segments
17.1.10.4. Sales Footprint
17.1.10.5. Strategy Overview
17.1.10.5.1. Marketing Strategy
17.1.10.5.2. Product Strategy
17.1.10.5.3. Channel Strategy
17.1.11. Kuberre Systems
17.1.11.1. Overview
17.1.11.2. Product Portfolio
17.1.11.3. Profitability by Market Segments
17.1.11.4. Sales Footprint
17.1.11.5. Strategy Overview
17.1.11.5.1. Marketing Strategy
17.1.11.5.2. Product Strategy
17.1.11.5.3. Channel Strategy
17.1.12. Horizon Software
17.1.12.1. Overview
17.1.12.2. Product Portfolio
17.1.12.3. Profitability by Market Segments
17.1.12.4. Sales Footprint
17.1.12.5. Strategy Overview
17.1.12.5.1. Marketing Strategy
17.1.12.5.2. Product Strategy
17.1.12.5.3. Channel Strategy
17.1.13. Finvasia
17.1.13.1. Overview
17.1.13.2. Product Portfolio
17.1.13.3. Profitability by Market Segments
17.1.13.4. Sales Footprint
17.1.13.5. Strategy Overview
17.1.13.5.1. Marketing Strategy
17.1.13.5.2. Product Strategy
17.1.13.5.3. Channel Strategy
17.1.14. InfoReach, Inc.
17.1.14.1. Overview
17.1.14.2. Product Portfolio
17.1.14.3. Profitability by Market Segments
17.1.14.4. Sales Footprint
17.1.14.5. Strategy Overview
17.1.14.5.1. Marketing Strategy
17.1.14.5.2. Product Strategy
17.1.14.5.3. Channel Strategy
18. Assumptions & Acronyms Used
19. Research Methodology
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