Algorithmic Trading Market to Hit a Robust CAGR of 13.01% by 2032 | Rising Requirements for Market Surveillance to Fuel Market Growth, States Extrapolate

The Algorithmic Trading Market is anticipated to reach a market valuation of USD 49.32 billion during the forecast period. With North America dominating the market, factors attributable to the market growth are positive regulatory regulations, minimal transaction costs, and effective order execution.

Dubai, UAE, June 26, 2023 (GLOBE NEWSWIRE) — As per the latest report published by Extrapolate, the Global Algorithmic Trading Market size was worth around USD 14.69 billion in 2022 and is anticipated to reach USD 49.32 billion by 2032, exhibiting a robust compound annual growth rate of roughly 13.01% between 2023 and 2032. Positive regulatory regulations, expanding demand for swift, dependable, and effective order execution, rising requirements for market surveillance, and decreasing transaction costs are expected to drive growth for the algorithmic market. Large brokerage firms and institutional investors use algorithmic trading to cut down on bulk trading costs.

Algorithmic trading, or “algo-trading,” is the management of trading activity by computer programs that follow a pre-established set of instructions. The pricing, timing, quantity, and various other factors are based on a mathematical model for the instructions. Furthermore, it is projected that the advancement of financial service algorithms and artificial intelligence (AI) would offer lucrative market growth opportunities. Furthermore, a surge in demand for cloud-based solutions is anticipated to aid in the algorithmic trading market growth.

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Competitive Landscape

The most prominent companies are concentrating on extending their geographic reach by developing sector-specific solutions. These players strategically team up and acquire local competitors to establish a firm regional foothold. New product introductions and innovations draw a large customer base, increasing sales.

These businesses focus on producing innovative products and efficient marketing techniques to preserve and increase their market share. The expanding volume of international trade is anticipated to bring about profitable chances for market participants. As a result, to maintain their position as leaders in the industry, these companies concentrate on various strategic activities, including alliances and mergers & acquisitions.

Leading companies operating in the global algorithmic trading market include:

  • 63 moons technologies limited
  • AlgoTrader
  • Argo Software Engineering
  • Citadel LLC
  • FlexTrade Systems, Inc.
  • Hudson River Trading
  • InfoReach, Inc.
  • Lime Trading Corp.
  • MetaQuotes Ltd
  • Refinitiv Limited
  • Software AG
  • Symphony
  • Tata Consultancy Services Limited
  • Tethys Technology, Inc.
  • Tower Research Capital LLC
  • Trading Technologies International, Inc.
  • Virtu Financial
  • Others

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Market Segmentation

By Component

  • Solution
  • Services

Solution Component to Dominate the Market Share Owing to the Introduction of Sophisticated Systems by Key Players

The solution component led the market share for global algorithmic trading in 2020. The segmental growth is attributable to numerous factors such as the introduction of sophisticated algorithmic trading systems by key market participants to meet rising customer needs.

Government restrictions, market monitoring, and consumer demand for quick, dependable, and efficient order execution all promote the segment’s growth. Demand for algorithmic trading solutions is further fueled by lower transaction costs resulting from removing human involvement and issuing trade orders quickly and accurately.

By Deployment

  • On-premise
  • Cloud-based

Cloud-Based Deployment to Gain Immense Traction Due to the Rising Number of Financial Firms

The cloud-based segment has dominated the global algorithmic trading market share in 2020 and is anticipated to grow at the highest CAGR during the projection period. The growth of the segment is primarily attributable to the increasing prevalence of financial firms that uses cloud-based solutions to improve productivity and efficiency. Additionally, traders are increasingly using cloud-based algorithmic trading solutions as they ensure effective process automation, data preservation, and cost-effective management.

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Challenges Faced by Algorithmic Trading Market

At both the international and local levels, algorithmic trading is governed by strict laws. Although some countries regulatory bodies have already developed rules, a few countries still need to come to an agreement on whether to allow algorithmic trading. As a result, there is always a chance that the regulatory body would establish extra rules that are special to algorithmic trading or perhaps contemplate outright banning it. Market participants should be on the lookout for new regulatory developments in this area and remain alert.

Inadequate Risks Valuation Pose as a Restraint in Algorithmic Trading Market

Lack of observation and poor risk assessment abilities might prevent the market from growing as anticipated. Additionally, algorithms have a limited lifespan, which could impede industry growth. Furthermore, operating the platforms requires a skilled professional.

Introduction of Machine Learning, Artificial Intelligence, Among Others to Improve Efficiency, Propelling Market Growth

The market for algorithmic trading is likely to experience tremendous growth as cloud-based services, cloud computing, and trading solutions becoming increasingly used. Trading professionals use cloud services for back testing, run-time series analysis, and trading strategies when placing trades to increase productivity, security, data management, sustainability, and other factors.

The market growth for algorithmic trading is projected to be significantly influenced by the financial services industry’s embrace of AI, ML, and big data. Technology improvements have promoted authorities to start paying attention to how consumers interact with the market. These technologies are now being used by some of the biggest organizations in the world to develop algorithmic trading.

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Key Developments

  • In June 2022, AlgoTrader released the most recent version 6.4 of its Broker Desk service, allowing traders to offer consumers trading in cryptocurrencies and other digital assets.
  • In 2022, In order to increase its presence in both the domestic and international Foreign Exchange (FX) markets, Alexbank announced its implementation of the Electronic Trading solution (ET) offered by Refinitiv.

Significant Expenditure in North America to Support Regional Market Growth

North America accounted for the largest share of the algorithmic trading market. The regional growth is majorly attributable to a number of factors, including significant investments in trading technology and rising public support for international commerce.

The region further gains from a concentrated supply of companies that provide algorithmic trading solutions, which support regional market growth. North America has a significant presence in the algorithmic trading business, highlighting both its status as a leader and its potential for future growth.

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Key Points from TOC:

Chapter 1. Executive Summary

Chapter 2. Research Methodology

2.1. Research Approach
2.2. Scope, definition, and Assumptions
2.3. Data Component
2.3.1. Secondary Component Preliminary data others
2.3.2. Primary Component Statistical Model Data Triangulation Research Objective

Chapter 3. Market Outlook

3.1. Introduction
3.2. Key Trends
3.2.1. Increasing API-driven Trading in Developing Regions
3.3. Market Drivers
3.3.1. Increasing Implementation of Cloud-based Services
3.3.2. Introduction of ML, AI, and Other Technologies to Improve Efficiency
3.4. Market Restraints
3.4.1. Concerns Pertaining to Inadequate Risks Valuation
3.5. Market Opportunities
3.5.1. Increasing Overseas Trade Across the World
3.6. Market Challenges
3.6.1. Stringent Regulations Might Hamper the Market
3.7. Porter’s Five Forces Analysis
3.7.1. Bargaining Type of Suppliers
3.7.2. Bargaining Type of Buyers
3.7.3. Threat of New Entrant
3.7.4. Threat of Substitutes
3.7.5. High Competitive Rivalry
3.8. Value chain analysis

Chapter 4. COVID-19 Impact On Algorithmic Trading Market

Chapter 5. Global Algorithmic Trading Market Overview, By Component, 2017 – 2030 (USD Million)

Chapter 6. Global Algorithmic Trading Market Overview, By Deployment, 2017 – 2030 (USD Million)

Chapter 7. Global Algorithmic Trading Market Overview, By Type, 2017 – 2030 (USD Million)

Chapter 8. Global Algorithmic Trading Market Overview, By Geography, 2017 – 2030 (USD Million)

Chapter 14. Competitive Landscape

14.1. Competitive environment, 2021
14.2. Strategic Framework
14.2.1. Partnership/agreement
14.2.2. Expansion
14.2.3. Mergers & Acquisitions
14.2.4. New Size development

Chapter 15. Key Vendor Analysis

15.1. 63 moons technologies limited
15.1.1. Company Overview
15.1.2. Financial performance
15.1.3. Component Benchmarking
15.1.4. Recent initiatives
15.1.5. SWOT analysis
15.2. AlgoTrader
15.2.1. Company Overview
15.2.2. Financial performance
15.2.3. Component Benchmarking
15.2.4. Recent initiatives
15.2.5. SWOT analysis
15.3. Argo Software Engineering
15.3.1. Company Overview
15.3.2. Financial performance
15.3.3. Component Benchmarking
15.3.4. Recent initiatives
15.4. Citadel LLC
15.5. FlexTrade Systems, Inc.
15.6. Hudson River Trading
15.7. InfoReach, Inc.
15.8. Lime Trading Corp.
15.9. MetaQuotes Ltd
15.10. Refinitiv Limited
15.11. Software AG
15.12. Symphony
15.13. Tata Consultancy Services Limited
15.14. Tethys Technology, Inc.
15.15. Tower Research Capital LLC
15.16. Trading Technologies International, Inc.
15.17. Virtu Financial
15.18. Others

Chapter 16. Sourcing Strategy and Downstream Buyers
Chapter 17. Marketing Strategy Analysis, Distributors/Traders
Chapter 18. Market Effect Factors Analysis
…TOC Continued

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