Jan 2024 109

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According to our (Global Info Research) latest study, the global Algorithmic Trading market size was valued at USD 11750 million in 2023 and is forecast to a readjusted size of USD 14990 million by 2030 with a CAGR of 3.5% during review period.
Algorithmic trading is a method of executing a large order (too large to fill all at once) using automated pre-programmed trading instructions accounting for variables such as time, price, and volume to send small slices of the order (child orders) out to the market over time.
Global Algorithmic Trading key players include Virtu Financial, Optiver, IMC, DRW Trading, Flow Traders, etc. Global top five manufacturers hold a share about 50%.
United States is the largest market, with a share about 50%, followed by Europe, and Japan, both have a share over 40 percent.
In terms of application, the largest application is Investment Banks, followed by CFunds, Personal Investors, etc.
The Global Info Research report includes an overview of the development of the Algorithmic Trading industry chain, the market status of Investment Banks (On-Premise, Cloud-Based), Funds (On-Premise, Cloud-Based), and key enterprises in developed and developing market, and analysed the cutting-edge technology, patent, hot applications and market trends of Algorithmic Trading.
Regionally, the report analyzes the Algorithmic Trading markets in key regions. North America and Europe are experiencing steady growth, driven by government initiatives and increasing consumer awareness. Asia-Pacific, particularly China, leads the global Algorithmic Trading market, with robust domestic demand, supportive policies, and a strong manufacturing base.

Key Features:
The report presents comprehensive understanding of the Algorithmic Trading market. It provides a holistic view of the industry, as well as detailed insights into individual components and stakeholders. The report analysis market dynamics, trends, challenges, and opportunities within the Algorithmic Trading industry.
The report involves analyzing the market at a macro level:
Market Sizing and Segmentation: Report collect data on the overall market size, including the revenue generated, and market share of different by Type (e.g., On-Premise, Cloud-Based).
Industry Analysis: Report analyse the broader industry trends, such as government policies and regulations, technological advancements, consumer preferences, and market dynamics. This analysis helps in understanding the key drivers and challenges influencing the Algorithmic Trading market.
Regional Analysis: The report involves examining the Algorithmic Trading market at a regional or national level. Report analyses regional factors such as government incentives, infrastructure development, economic conditions, and consumer behaviour to identify variations and opportunities within different markets.
Market Projections: Report covers the gathered data and analysis to make future projections and forecasts for the Algorithmic Trading market. This may include estimating market growth rates, predicting market demand, and identifying emerging trends.

The report also involves a more granular approach to Algorithmic Trading:
Company Analysis: Report covers individual Algorithmic Trading players, suppliers, and other relevant industry players. This analysis includes studying their financial performance, market positioning, product portfolios, partnerships, and strategies.
Consumer Analysis: Report covers data on consumer behaviour, preferences, and attitudes towards Algorithmic Trading This may involve surveys, interviews, and analysis of consumer reviews and feedback from different by Application (Investment Banks, Funds).
Technology Analysis: Report covers specific technologies relevant to Algorithmic Trading. It assesses the current state, advancements, and potential future developments in Algorithmic Trading areas.
Competitive Landscape: By analyzing individual companies, suppliers, and consumers, the report present insights into the competitive landscape of the Algorithmic Trading market. This analysis helps understand market share, competitive advantages, and potential areas for differentiation among industry players.
Market Validation: The report involves validating findings and projections through primary research, such as surveys, interviews, and focus groups.

Market Segmentation
Algorithmic Trading market is split by Type and by Application. For the period 2019-2030, the growth among segments provides accurate calculations and forecasts for consumption value by Type, and by Application in terms of value.

Market segment by Type
- On-Premise
- Cloud-Based

Market segment by Application
- Investment Banks
- Funds
- Personal Investors
- Others

Market segment by players, this report covers
- Virtu Financial
- DRW Trading
- Optiver
- Tower Research Capital
- Flow Traders
- Hudson River Trading
- Jump Trading
- RSJ Algorithmic Trading
- Spot Trading
- Sun Trading
- Tradebot Systems
- Quantlab Financial
- Teza Technologies

Market segment by regions, regional analysis covers
- North America (United States, Canada, and Mexico)
- Europe (Germany, France, UK, Russia, Italy, and Rest of Europe)
- Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Australia and Rest of Asia-Pacific)
- South America (Brazil, Argentina and Rest of South America)
- Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)

The content of the study subjects, includes a total of 13 chapters:
Chapter 1, to describe Algorithmic Trading product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top players of Algorithmic Trading, with revenue, gross margin and global market share of Algorithmic Trading from 2019 to 2024.
Chapter 3, the Algorithmic Trading competitive situation, revenue and global market share of top players are analyzed emphatically by landscape contrast.
Chapter 4 and 5, to segment the market size by Type and application, with consumption value and growth rate by Type, application, from 2019 to 2030.
Chapter 6, 7, 8, 9, and 10, to break the market size data at the country level, with revenue and market share for key countries in the world, from 2019 to 2024.and Algorithmic Trading market forecast, by regions, type and application, with consumption value, from 2025 to 2030.
Chapter 11, market dynamics, drivers, restraints, trends and Porters Five Forces analysis.
Chapter 12, the key raw materials and key suppliers, and industry chain of Algorithmic Trading.
Chapter 13, to describe Algorithmic Trading research findings and conclusion.

Table of Contents

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