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市场调查报告书
商品编码
1519800

2024-2032 年按交易类型（外汇、股票市场、交易所交易基金、债券、加密货币等）、组件、部署模型、组织规模和区域分類的演算法交易市场报告

Algorithmic Trading Market Report by Trading Type (Foreign Exchange, Stock Markets, Exchange-Traded Fund, Bonds, Cryptocurrencies, and Others), Components, Deployment Model, Organization Size, and Region 2024-2032
出版日期: | 出版商: IMARC | 英文 142 Pages | 商品交期: 2-3个工作天内

价格

2023年全球IMARC Group交易市场规模达156亿美元。金融市场的全球化、客製化交易规则的引入、迎合特定风险状况以及交易技术领域的不断进步是推动市场的一些主要因素。

演算法交易市场分析：

市场成长与规模：由于金融领域对自动交易系统的依赖程度增加以及该产业范围和规模的不断扩大，市场正在经历显着成长。

主要市场驱动因素：金融市场全球化、应对复杂且相互关联的市场的演算法需求、根据所选风险状况设计的客製化交易系统的需求以及永久技术进步和进步的趋势等主要因素主导着金融市场的成长。这些因素结合在对此类交易方案的快速获取和了解中。

主要市场趋势：云端运算在这里具有最高的吸引力，其次是可扩展性和成本效率。人工智慧和机器学习技术是嵌入的另一个方面，可以完成更复杂和高效的交易策略。

地理趋势：北美市场构成了主要的演算法交易市场份额，其原因在于其相关的数位基础设施、高效的金融市场以及强有力的监管方式。 Region以颠覆性技术为中心的交易系统和专门用于运算设备（尤其是人工智慧和云端）的巨额资金是其控制市场的主要原因。

竞争格局：市场竞争激烈，主要参与者不断涉足创新并提供更高阶的产品，最近出现了收购、新交易平台和扩张，以保护其竞争优势并适应交易者快速变化的趋势。

挑战与机会：市场面临着诸如需要不断的技术升级、遵守不断变化的法规以及网路安全威胁的风险等挑战。然而，这些挑战为市场参与者提供了创新的机会，特别是在开发更安全、高效和合规的演算法交易解决方案方面，从而推动市场的成长。

演算法交易市场趋势：

监管环境的存在

政府和监管机构也持续关注，并相应地修改法规，以适应快速变化的科技环境。据 Share India 的一篇文章称，SEBI（印度证券交易委员会）于 2008 年 4 月 3 日在印度引入了演算法交易。各种让金融市场更透明、公平、诚实的措施的实施也增加了交易的信任。国际规则确保不同国家的标准监管，从而增强全球商品和服务的出口，从而推动演算法交易市场洞察。在这方面，严格的合规法规的执行迫使企业建立熟练的风险管理模型，最终使该行业更加可靠。这些监管框架维护了投资者的利益，也对演算法交易产业的稳定和成长发挥了实质和累积的作用。例如，2022年6月10日，SEBI发布了一份关于某不受监管的提供演算法交易策略平台声称的业绩/回报的通知，因为SEBI注意到股票经纪人透过此类平台向投资者提供演算法交易设施，以防止任何错误- 出售并保护证券市场投资者的利益。这进一步提高了演算法交易市场的成长率。

对效率和降低成本的需求不断增长

该行业目前对资源利用优化和成本降低的需求很高。金融业对生产力的需求和预算削减是主要原因之一。涉及手动程序的传统交易实践非常耗时且充满人为错误。虽然演算法交易本质上考虑了执行速度并降低了错误风险，但手动交易在很大程度上依赖人为因素。这项基于自动化的决定也导致处理大量交易的成本降低，而费用却没有相应增加，从而影响演算法交易市场的收入。根据国际贸易政府统计，美国製造业的外国直接投资占美国全部外国直接投资的40.1%，自动化在吸引投资和创造就业方面发挥关键作用。除此之外，资料处理速度和快速交易使用量等于高市场流动性和小点差。透过采用明智的策略有效消除交易成本并增加利润有助于向更广泛的金融领域扩张。例如，2023 年 6 月 14 日，GAO 发布了第 13 份年度报告，强调了减少联邦计画分散、重迭和重复的机会，以及节省资金和增加收入的机会。预计这将提高未来几年演算法交易市场的预测。

科技不断进步

该行业的成长在很大程度上取决于处理资料和运算能力方面惊人的技术进步。这些复杂性使得在运行时能够逼真地执行基本和复杂的数学模型和演算法。那些具有强大运算能力的投机平台减少了延迟，因此交易者能够在不到一秒的时间内做出快速决策。此外，云端运算和人工智慧的爆炸性成长正在导致更精细的交易策略的设计，使交易者能够在不同的市场条件下实现目标，并投资于特定的方向，这进一步推动了演算法交易的市场价值。例如，2023 年 11 月，AMD 和微软重点介绍了 AMD 产品（包括即将推出的 AMD Instinct MI300X 加速器、AMD EPYC CPU 和带有 AI 引擎的 AMD Ryzen CPU）如何跨云和生成式 AI、机密运算、云计算和更智能的PC。此外，演算法变得更加有效和易于使用，无论是简单的分析还是复杂的交易操作，这也为小公司提供了支持，从而实现成长和发展。

目录

第一章：前言

第 2 章：范围与方法

  • 研究目的
  • 利害关係人
  • 资料来源
    • 主要资源
    • 二手资料
  • 市场预测
    • 自下而上的方法
    • 自上而下的方法
  • 预测方法

第 3 章：执行摘要

第 4 章：简介

  • 概述
  • 主要行业趋势

第 5 章：全球演算法交易市场

  • 市场概况
  • 市场业绩
  • COVID-19 的影响
  • 市场区隔：按交易类型
  • 市场区隔：按组成部分
  • 市场区隔：依部署模式
  • 市场区隔：依组织规模
  • 市场区隔：按地区
  • 市场预测

第 6 章：市场区隔：按交易类型

  • 外汇 (FOREX)
    • 市场走向
    • 市场预测
  • 股市
    • 市场走向
    • 市场预测
  • 交易所交易基金 (ETF)
    • 市场走向
    • 市场预测
  • 债券
    • 市场走向
    • 市场预测
  • 加密货币
    • 市场走向
    • 市场预测
  • 其他的
    • 市场走向
    • 市场预测

第 7 章：市场区隔：按组成部分

  • 解决方案
    • 市场走向
    • 主要类型
      • 平台
      • 软体工具
    • 市场预测
  • 服务
    • 市场走向
    • 主要类型
      • 专业的服务
      • 管理服务
    • 市场预测

第 8 章：市场区隔：依部署模型

  • 本地部署
    • 市场走向
    • 市场预测
  • 云
    • 市场走向
    • 市场预测

第 9 章：市场区隔：依组织规模

  • 中小企业
    • 市场走向
    • 市场预测
  • 大型企业
    • 市场走向
    • 市场预测

第 10 章：市场区隔：按地区

  • 北美洲
    • 市场走向
    • 市场预测
  • 欧洲
    • 市场走向
    • 市场预测
  • 亚太地区
    • 市场走向
    • 市场预测
  • 中东和非洲
    • 市场走向
    • 市场预测
  • 拉丁美洲
    • 市场走向
    • 市场预测

第 11 章：SWOT 分析

  • 概述
  • 优势
  • 弱点
  • 机会
  • 威胁

第 12 章：价值链分析

第 13 章：波特的五力分析

  • 概述
  • 买家的议价能力
  • 供应商的议价能力
  • 竞争程度
  • 新进入者的威胁
  • 替代品的威胁

第14章：竞争格局

  • 市场结构
  • 关键参与者
  • 关键参与者简介
    • Vela Trading Systems LLC
    • Meta-Quotes Limited
    • Trading Technologies International Inc.
    • Software AG
    • AlgoTrader
    • uTrade Solutions Private Limited
    • Automated Trading SoftTech Private Limited
    • Kuberre Systems Inc.
    • InfoReach Inc.
    • Virtu Financial Inc.
    • Tata Consultancy Services
    • Argo Group International Holdings Limited
    • Thomson Reuters Corporation
    • iRageCapital Advisory Private Limited
    • 63 Moons Technologies Ltd.
Product Code: SR112024A1641

The global algorithmic trading market size reached US$ 15.6 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 37.6 Billion by 2032, exhibiting a CAGR of 10% during 2024-2032. The globalization of financial markets, the introduction of customized trading rules, catering to specific risk profiles, and the continuous advancements in the field of trading technologies are some of the major factors propelling the market.

Algorithmic Trading Market Analysis:

Market Growth and Size: The market is experiencing significant growth, driven by the increased level of reliance on automated trading systems in the financial sector, along with the continual increase in the scope and scale of the sector.

Major Market Drivers: Main factors such as globalization of financial markets, the need for algorithms to cope with complex and interlinking markets, demand for customized trading systems designed according to chosen risk profiles, and the tendency for permanent technological advance and progress dominate the growth of algorithmic trading. These factors coalesce in the quick acquisition and knowledge of such trading schemes.

Key Market Trends: Cloud computing has its highest degree of attractiveness here followed by scalability and cost-efficiency. Artificial intelligence and machine learning technologies are another aspect that is being embedded which allow a much more complex and efficient trading strategy to be completed.

Geographical Trends: The North American market constitutes the main algorithmic trading market share with the cause lying in its pertinent digital infrastructure, efficient financial markets as well as strong regulatory approach. Region's disruptive technology-focused trading systems and huge funds dedicated to computing devices notably including AI and cloud are the main reasons behind its control of the market.

Competitive Landscape: The market is competitive, with key players continuously dabbling in innovating and providing offerings of a higher order that has of late seen acquisitions, new trading platforms and expansion to protect its competitive edge and accommodate the fast-moving trends of traders.

Challenges and Opportunities: The market faces challenges such as the need for constant technological upgrades, compliance with evolving regulations, and the risk of cybersecurity threats. However, these challenges present opportunities for market players to innovate, particularly in developing more secure, efficient, and compliant algorithmic trading solutions, thereby driving the market's growth.

Algorithmic Trading Market Trends:

The presence of a regulatory environment

Governments and regulators are also on a constant watch, and they amend the regulations accordingly to stay on par with the fast-changing tech environment. According to an article in Share India, SEBI (Securities and Exchange Board of India) introduced algorithmic trading in India on 3rd April 2008. It did that by providing institutions with Direct Market Access (DMA) facilities. The implementation of various measures to make financial markets more transparent, fair, and honest has also increased the trust in trading. There are international rules that ensure standard regulations in different countries, which enhance the exportation of goods and services across the world, thus driving the algorithmic trading market insights. In this regard, the enforcement of severe compliance regulations has forced companies to set up proficient risk management models, which end up making the sector more reliable. These regulatory frameworks have safeguarded the interests of investors and have also played a substantial and cumulative role in the stability and growth of the algorithmic trading industry. For instance, on June 10, 2022, SEBI issued a circular on performance/return claimed by an unregulated platform offering algorithmic strategies for trading as it came to the notice of SEBI that stockbrokers provide algorithmic trading facilities to investors through such platforms to prevent any mis-selling and to protect the interest of investors in the security market. This is further bolstering the algorithmic trading market growth rate.

Growing demand for efficiency and cost reduction

The industry is currently experiencing high demand for resource use optimization and cost decrease. The need for productivity and a budget cut in the financial industry is one of the major causes. Conventional trading practices involving manual procedures are very time-consuming and rife with human error. While algorithmic trading, by its nature, accounts for the speed of execution and lowers the risk of mistakes, manual trading relies heavily on the human element. This decision, based on automation, also leads to reducing the cost of handling large amounts of trade without a corresponding increase in expenses, thereby influencing the algorithmic trading market revenue. According to the International Trade Government, foreign direct investment in manufacturing in the United States represents 40.1% of all FDI in the United States and automation plays a key role in attracting investment and creating jobs. Besides that, the speed of data processing and fast trading usage equals high market liquidity and small spreads. Efficient removal of transaction costs and increase in profit by employing smart strategies aids the expansion towards the wider financial sector. For instance, on June 14, 2023, GAO released its 13th annual report highlighting opportunities to reduce fragmentation, overlap, and duplication in federal programs as well as chances to save money and increase revenue. This is expected to boost the algorithmic trading market forecast over the coming years.

Continuous technological advancements

The industry's growth is significantly determined by the astonishing technological advances in the capability to process data and power computing. These sophistications enabled performing the life-like execution of basic and complex mathematical models and algorithms during run-time. Those speculative platforms with extensive computing capacity have reduced latency, thus, traders have been able to make rapid decisions in a fraction of a second. Furthermore, the explosive growth in cloud computing and AI is leading to the design of more elaborate trading strategies that enable a trader to achieve targets in different market conditions and invest in a particular direction which is further propelling the algorithmic trading market value. For instance, in November 2023, AMD and Microsoft featured how AMD products, including the upcoming AMD Instinct MI300X accelerator, AMD EPYC CPUs and AMD Ryzen CPUs with AI engines, are enabling new services and compute capabilities across cloud and generative AI, Confidential Computing, Cloud Computing and smarter, more intelligent PCs. Also, algorithms become more effective and accessible, be they simple analytics or complex trading operations, this empowers small companies as well which leads to growth and development.

Algorithmic Trading Industry Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the global algorithmic trading market report, along with forecasts at the global and regional levels from 2024-2032. Our report has categorized the market based on trading type, components, deployment model and organization size.

Breakup by Trading Type:

Foreign Exchange (FOREX)

Stock Markets

Exchange-Traded Fund (ETF)

Bonds

Cryptocurrencies

Others

The report has provided a detailed breakup and analysis of the market based on the trading type. This includes foreign exchange (FOREX), stock markets, exchange-traded fund (ETF), bonds, cryptocurrencies, and others.

The stock market operates in the industrial environment, where several factors influence the dynamics of the stock market. Furthermore, the contribution of technology is essential, and trading algorithms of high frequency as well as infrastructure continuously form the basis of the changing facet. Macroeconomic factors, such as interest rates, GDP growth, and geopolitical developments, in turn from investor sentiment and trigger market fluctuations. Moreover, the ongoing developments in regulatory regimes can disrupt or bolster the landscape of algorithmic trading, shifting market participants' strategies. Liquidity conditions, as well as trading volumes, directly affect the stock market within the industry by either making the execution of trades smooth or influencing the price movements.

On the other hand, in the crypto industry, regulation and government policy greatly influence the currency. Beyond that, technological progress, for example, blockchain innovations and scalability solutions, is effectively a determinant for the market direction. Moreover, macroeconomic determinants such as inflation rates and global economic trends stimulate investor's feelings and ground their demand for digital assets. Furthermore, such factors as news events, market sentiment, and social media discussions produce such rapid fluctuations on the price. Experienced computer-aided traders of cryptocurrencies cannot do without observing and evaluating these important factors attentively to look for chances and control risks in times of volatility.

Breakup by Components:

Solutions

Platforms

Software Tools

Services

Professional Services

Managed Services

Solutions dominates the market

A detailed breakup and analysis of the market based on the components have also been provided in the report. This includes solutions (platforms, and software tools), and services (professional services, and managed services). According to the report, solutions represented the largest segment.

Algorithmic trading software and infrastructure are going through an innovation phase driven by the solutions component. As technology progresses, traders constantly look for more advanced systems and platforms that can maximize their win. Moreover, regulatory changes and compliance requirements greatly affect solutions sort, for the traders should guarantee their systems are in line with corresponding laws and regulations. It is also driven by algorithmic trading market demand for advanced algorithmic solutions for risk management, trading automation, and more efficient execution. Moreover, massive amounts of data and the progress of advanced data analytics techniques allow the trading market to build more perfect trading algorithms. On the other hand, cost-effective and scalable solutions are vital for traders since they are looking for a solution that will enable them to meet their unique needs at a cost-effective and scalable rate.

Breakup by Deployment Model:

On-Premises

Cloud

Cloud dominates the market

The report has provided a detailed breakup and analysis of the market based on the deployment model. This includes on-premises and cloud. According to the report, cloud represented the largest segment.

In the industry, the cloud deployment model is driven by various market drivers that shape its adoption and growth. Along with this, scalability and flexibility are significant drivers, as the cloud allows traders to easily scale their computational resources based on market demands and adjust their strategies accordingly. In addition, cost-effectiveness plays a pivotal role, as cloud-based solutions often offer a more economical approach compared to traditional on-premises infrastructures, especially for smaller firms and startups. In addition, the escalating volume and complexity of financial data necessitate robust data storage and processing capabilities, which cloud services can readily provide. Moreover, geographic reach and low-latency capabilities offered by cloud providers cater to global trading operations, enabling faster trade execution and reduced network latency. Additionally, the cloud's security measures and compliance offerings align with the stringent regulatory requirements in the financial industry. These factors collectively drive the adoption of cloud deployment models in the algorithmic trading sector, empowering market research and consulting companies to establish themselves as thought leaders in this domain.

Breakup by Organization Size:

Small and Medium Enterprises

Large Enterprises

A detailed breakup and analysis of the market based on the organization size have also been provided in the report. This includes small and medium enterprises and large enterprises.

In the industry, small and medium enterprises (SMEs) are driven by advancements in technology. Additionally, the growing availability of data and analytics services empowers SMEs to make informed trading decisions based on real-time market insights. Along with this, regulatory changes and initiatives that aim to level the playing field in the financial markets create opportunities for SMEs to compete with larger players. In addition, the rising demand for niche trading strategies and customized solutions presents a fertile ground for SMEs to carve out specialized market niches. Additionally, cost-effectiveness is a crucial driver, as cloud-based services and outsourcing options allow SMEs to access cutting-edge technologies without substantial upfront investments.

On the other hand, large enterprises in the industry are driven by their established market presence and brand reputation to provide credibility and attract potential clients and partners. In confluence with this, large enterprises benefit from economies of scale, enabling them to negotiate better pricing and access exclusive data and research services. Furthermore, regulatory compliance and risk management capabilities are critical drivers, ensuring adherence to evolving financial regulations and minimizing potential risks. These market drivers, coupled with authoritative market research and consulting services, cement large enterprises' position as influential players in the algorithmic trading domain.

Breakup by Region:

North America

Europe

Asia Pacific

Latin America

Middle East and Africa

North America exhibits a clear dominance, accounting for the largest algorithmic trading market share

The report has also provided a comprehensive analysis of all the major regional markets, which include North America, Europe, Asia Pacific, Latin America, and the Middle East and Africa. According to the report, North America represented the largest share.

The algorithmic trading industry in North America is propelled by the region's advanced technological infrastructure and expertise fostering innovation and development in strategies and tools. North America's strong financial markets and well-established regulatory environment create an attractive ecosystem for algorithmic trading firms seeking stability and compliance. Additionally, the region's robust data availability and analytics capabilities offer valuable insights to algorithmic traders, facilitating more informed decision-making. Moreover, the presence of diverse industries and financial instruments in North America allows for the development of specialized algorithmic trading strategies catering to specific market segments. Furthermore, the increasing adoption of cloud-based solutions and artificial intelligence in the region enhances algorithmic trading efficiency and scalability. These market drivers, in conjunction with authoritative market research and consulting services, position North America as a leading hub for innovation and expertise in the algorithmic trading domain.

Competitive Landscape:

The global algorithmic trading market is experiencing significant growth due to continuous advancements in technology, including high-speed computing, sophisticated algorithms, and artificial intelligence. Along with this, evolving financial regulations and market structure reforms influence the adoption and operation of algorithmic trading strategies. Compliance with regulatory requirements is crucial for market participants to ensure fairness and transparency. In addition, the emergence of cost-effective solutions compared to traditional manual trading methods, making it attractive to market participants seeking to optimize operational costs is also impacting the market. Apart from this, the widespread adoption of algorithmic trading for precise risk management and implementing pre-defined risk parameters is significantly supporting the market. Furthermore, the availability of vast amounts of real-time market data allows algorithmic traders to develop sophisticated strategies based on comprehensive and up-to-date information, which contributes to the market.

The report has provided a comprehensive analysis of the competitive landscape in the global algorithmic trading market. Detailed profiles of all major companies have also been provided. Some of the key players in the market include:

Vela Trading Systems LLC

Meta-Quotes Limited

Trading Technologies International Inc.

Software AG

AlgoTrader

uTrade Solutions Private Limited

Automated Trading SoftTech Private Limited

Kuberre Systems Inc.

InfoReach Inc.

Virtu Financial Inc.

Tata Consultancy Services

Argo Group International Holdings Limited

Thomson Reuters Corporation

iRageCapital Advisory Private Limited

63 Moons Technologies Ltd.

(Please note that this is only a partial list of the key players, and the complete list is provided in the report.)

Recent Developments:

In June 2023, Meta-Quotes Limited offered a tool to increase trading volume and a customer base in MetaTrader 5. The improved service will help brokers execute their businesses more effectively.

In March 2023, Trading Technologies International Inc. announced the purchase of London-based AxeTrading by the company. With a significant expansion into full coverage of corporate, government, municipal, and emerging market bonds as well as over-the-counter (OTC) interest rate swaps, the acquisition significantly broadens TT's multi-asset capabilities and reinforces TT's dominant position in fixed income derivatives and U.S. Treasury securities.

In February 2022, AlgoTrader continued its innovative approach to digital asset growth by raising a total of around USD 4.9 million in the pre-Series B fundraising round. Fenbushi Capital and SBI Investment, two East Asian venture capital firms, participated in the pre-Series B fundraising that was co-led by Credit Suisse Entrepreneur Capital and C3 EOS VC Fund.

Key Questions Answered in This Report

  • 1. What was the size of the global algorithmic trading market in 2023?
  • 2. What is the expected growth rate of the global algorithmic trading market during 2024-2032?
  • 3. What are the key factors driving the global algorithmic trading market?
  • 4. What has been the impact of COVID-19 on the global algorithmic trading market?
  • 5. What is the breakup of the global algorithmic trading market based on the components?
  • 6. What is the breakup of the global algorithmic trading market based on the deployment model?
  • 7. What are the key regions in the global algorithmic trading market?
  • 8. Who are the key players/companies in the global algorithmic trading market?

Table of Contents

1 Preface

2 Scope and Methodology

  • 2.1 Objectives of the Study
  • 2.2 Stakeholders
  • 2.3 Data Sources
    • 2.3.1 Primary Sources
    • 2.3.2 Secondary Sources
  • 2.4 Market Estimation
    • 2.4.1 Bottom-Up Approach
    • 2.4.2 Top-Down Approach
  • 2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

  • 4.1 Overview
  • 4.2 Key Industry Trends

5 Global Algorithmic Trading Market

  • 5.1 Market Overview
  • 5.2 Market Performance
  • 5.3 Impact of COVID-19
  • 5.4 Market Breakup by Trading Type
  • 5.5 Market Breakup by Components
  • 5.6 Market Breakup by Deployment Model
  • 5.7 Market Breakup by Organization Size
  • 5.8 Market Breakup by Region
  • 5.9 Market Forecast

6 Market Breakup by Trading Type

  • 6.1 Foreign Exchange (FOREX)
    • 6.1.1 Market Trends
    • 6.1.2 Market Forecast
  • 6.2 Stock Markets
    • 6.2.1 Market Trends
    • 6.2.2 Market Forecast
  • 6.3 Exchange-Traded Fund (ETF)
    • 6.3.1 Market Trends
    • 6.3.2 Market Forecast
  • 6.4 Bonds
    • 6.4.1 Market Trends
    • 6.4.2 Market Forecast
  • 6.5 Cryptocurrencies
    • 6.5.1 Market Trends
    • 6.5.2 Market Forecast
  • 6.6 Others
    • 6.6.1 Market Trends
    • 6.6.2 Market Forecast

7 Market Breakup by Components

  • 7.1 Solutions
    • 7.1.1 Market Trends
    • 7.1.2 Major Types
      • 7.1.2.1 Platforms
      • 7.1.2.2 Software Tools
    • 7.1.3 Market Forecast
  • 7.2 Services
    • 7.2.1 Market Trends
    • 7.2.2 Major Types
      • 7.2.2.1 Professional Services
      • 7.2.2.2 Managed Services
    • 7.2.3 Market Forecast

8 Market Breakup by Deployment Model

  • 8.1 On-Premises
    • 8.1.1 Market Trends
    • 8.1.2 Market Forecast
  • 8.2 Cloud
    • 8.2.1 Market Trends
    • 8.2.2 Market Forecast

9 Market Breakup by Organization Size

  • 9.1 Small and Medium Enterprises
    • 9.1.1 Market Trends
    • 9.1.2 Market Forecast
  • 9.2 Large Enterprises
    • 9.2.1 Market Trends
    • 9.2.2 Market Forecast

10 Market Breakup by Region

  • 10.1 North America
    • 10.1.1 Market Trends
    • 10.1.2 Market Forecast
  • 10.2 Europe
    • 10.2.1 Market Trends
    • 10.2.2 Market Forecast
  • 10.3 Asia Pacific
    • 10.3.1 Market Trends
    • 10.3.2 Market Forecast
  • 10.4 Middle East and Africa
    • 10.4.1 Market Trends
    • 10.4.2 Market Forecast
  • 10.5 Latin America
    • 10.5.1 Market Trends
    • 10.5.2 Market Forecast

11 SWOT Analysis

  • 11.1 Overview
  • 11.2 Strengths
  • 11.3 Weaknesses
  • 11.4 Opportunities
  • 11.5 Threats

12 Value Chain Analysis

13 Porter's Five Forces Analysis

  • 13.1 Overview
  • 13.2 Bargaining Power of Buyers
  • 13.3 Bargaining Power of Suppliers
  • 13.4 Degree of Competition
  • 13.5 Threat of New Entrants
  • 13.6 Threat of Substitutes

14 Competitive Landscape

  • 14.1 Market Structure
  • 14.2 Key Players
  • 14.3 Profiles of Key Players
    • 14.3.1 Vela Trading Systems LLC
    • 14.3.2 Meta-Quotes Limited
    • 14.3.3 Trading Technologies International Inc.
    • 14.3.4 Software AG
    • 14.3.5 AlgoTrader
    • 14.3.6 uTrade Solutions Private Limited
    • 14.3.7 Automated Trading SoftTech Private Limited
    • 14.3.8 Kuberre Systems Inc.
    • 14.3.9 InfoReach Inc.
    • 14.3.10 Virtu Financial Inc.
    • 14.3.11 Tata Consultancy Services
    • 14.3.12 Argo Group International Holdings Limited
    • 14.3.13 Thomson Reuters Corporation
    • 14.3.14 iRageCapital Advisory Private Limited
    • 14.3.15 63 Moons Technologies Ltd.

List of Figures

  • Figure 1: Global: Algorithmic Trading Market: Major Drivers and Challenges
  • Figure 2: Global: Algorithmic Trading Market: Sales Value (in Billion US$), 2018-2023
  • Figure 3: Global: Algorithmic Trading Market: Breakup by Trading Type (in %), 2023
  • Figure 4: Global: Algorithmic Trading Market: Breakup by Components (in %), 2023
  • Figure 5: Global: Algorithmic Trading Market: Breakup by Deployment Model (in %), 2023
  • Figure 6: Global: Algorithmic Trading Market: Breakup by Organization Size (in %), 2023
  • Figure 7: Global: Algorithmic Trading Market: Breakup by Region (in %), 2023
  • Figure 8: Global: Algorithmic Trading Market Forecast: Sales Value (in Billion US$), 2024-2032
  • Figure 9: Global: Algorithmic Trading Industry: SWOT Analysis
  • Figure 10: Global: Algorithmic Trading Industry: Value Chain Analysis
  • Figure 11: Global: Algorithmic Trading Industry: Porter's Five Forces Analysis
  • Figure 12: Global: Algorithmic Trading (Foreign Exchange- FOREX) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 13: Global: Algorithmic Trading (Foreign Exchange- FOREX) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 14: Global: Algorithmic Trading (Stock Markets) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 15: Global: Algorithmic Trading (Stock Markets) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 16: Global: Algorithmic Trading (Exchange-Traded Fund- ETF) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 17: Global: Algorithmic Trading (Exchange-Traded Fund- ETF) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 18: Global: Algorithmic Trading (Bonds) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 19: Global: Algorithmic Trading (Bonds) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 20: Global: Algorithmic Trading (Cryptocurrencies) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 21: Global: Algorithmic Trading (Cryptocurrencies) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 22: Global: Algorithmic Trading (Other Trading Types) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 23: Global: Algorithmic Trading (Other Trading Types) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 24: Global: Algorithmic Trading (Solutions) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 25: Global: Algorithmic Trading (Solutions) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 26: Global: Algorithmic Trading (Services) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 27: Global: Algorithmic Trading (Services) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 28: Global: Algorithmic Trading (On-Premises) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 29: Global: Algorithmic Trading (On-Premises) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 30: Global: Algorithmic Trading (Cloud) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 31: Global: Algorithmic Trading (Cloud) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 32: Global: Algorithmic Trading (Small and Medium Enterprises) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 33: Global: Algorithmic Trading (Small and Medium Enterprises) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 34: Global: Algorithmic Trading (Large Enterprises) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 35: Global: Algorithmic Trading (Large Enterprises) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 36: North America: Algorithmic Trading Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 37: North America: Algorithmic Trading Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 38: Europe: Algorithmic Trading Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 39: Europe: Algorithmic Trading Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 40: Asia Pacific: Algorithmic Trading Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 41: Asia Pacific: Algorithmic Trading Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 42: Middle East and Africa: Algorithmic Trading Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 43: Middle East and Africa: Algorithmic Trading Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 44: Latin America: Algorithmic Trading Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 45: Latin America: Algorithmic Trading Market Forecast: Sales Value (in Million US$), 2024-2032

List of Tables

  • Table 1: Global: Algorithmic Trading Market: Key Industry Highlights, 2023 and 2032
  • Table 2: Global: Algorithmic Trading Market Forecast: Breakup by Trading Type (in Million US$), 2024-2032
  • Table 3: Global: Algorithmic Trading Market Forecast: Breakup by Components (in Million US$), 2024-2032
  • Table 4: Global: Algorithmic Trading Market Forecast: Breakup by Deployment Model (in Million US$), 2024-2032
  • Table 5: Global: Algorithmic Trading Market Forecast: Breakup by Organization Size (in Million US$), 2024-2032
  • Table 6: Global: Algorithmic Trading Market Forecast: Breakup by Region (in Million US$), 2024-2032
  • Table 7: Global: Algorithmic Trading Market Structure
  • Table 8: Global: Algorithmic Trading Market: Key Players