Algorithmic Trading Market Size, Share & Trends Analysis Report By Component (Solution, Service), By Deployment (Cloud, On-premise), By Trading Types, By Type of Traders, By Region, And Segment Forecasts, 2025 - 2030

Algorithmic Trading Market Size, Share & Trends Analysis Report By Component (Solution, Service), By Deployment (Cloud, On-premise), By Trading Types, By Type of Traders, By Region, And Segment Forecasts, 2025 - 2030


Algorithmic Trading Market Growth & Trends

The global algorithmic trading market size is expected to reach USD 42.99 billion by 2030, registering a CAGR of 12.9% from 2025 to 2030, according to a new report by Grand View Research, Inc. The growth can be attributed to the increasing demand for effective, reliable, fast order execution and reduced transaction costs. Algorithmic trading solutions are widely used to process orders using pre-programmed and automated trading instructions to account for variables such as timing, price, and volume.

Investors and algorithmic traders regularly use high-frequency trading technology, enabling their firms to carry out tens of thousands of trades per second. Moreover, algorithmic trading solutions are widely used by investors and algorithmic traders in a wide variety of conditions, including arbitrage, order execution, and trend trading strategies, among others. Furthermore, the increasing trading volumes put pressure on trading desks to efficiently improve execution performance. This, as a result, is expected to create demand for algorithmic trading solutions.

The increasing use of algorithmic trading platforms by brokerage houses and institutional investors to cut down on costs associated with trading is expected to propel market growth over the forecast period. Brokerage houses and institutional investors are using these platforms to trade large order sizes. Furthermore, businesses across the globe use these platforms to create liquidity.

The COVID-19 outbreak is anticipated to impact the market positively. The increasing shift towards algorithmic trading solutions for making trade decisions at a rapid pace by eliminating human errors is further expected to propel market growth. Moreover, the Reserve Bank of Australia stated that the impact of the COVID-19 pandemic had advanced the industry’s shift toward electronic trading. These aforementioned factors are expected to propel market growth over the forecast period.

Algorithmic Trading Market Report Highlights
  • Investors and traders widely adopt algorithmic trading software tools to ensure the accurate and effective execution of trade orders. As a result, the software tools segment is expected to witness significant growth over the forecast period
  • The managed services segment is expected to register the highest CAGR throughout the projection period. The growth is attributed to the ability of managed services to provide traders with support, maintenance, and infrastructure management for efficiently developing trading strategies
  • The increasing adoption of cloud-based algorithmic trading solutions owing to their scalability, cost-effectiveness, effective management, and easy trade data maintenance capabilities is expected to propel the segment growth over the forecast period
  • The cryptocurrencies segment is anticipated to register significant growth during the forecast period. The rising awareness among traders in cryptocurrency trading is expected to create growth opportunities for segment growth over the forecast period
  • The short-term traders segment is expected to register the highest CAGR over the forecast period. Short-term traders are widely adopting algorithmic trading platforms to make it smooth and easy for the financial markets to sell and purchase their stocks at reasonable prices
  • North America dominated the algorithmic trading industry in 2024. The regional growth can be attributed to the increasing investments in trading technologies and the presence of many algorithmic trading companies in the region. Moreover, growing government support for international trade is anticipated to fuel the growth
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Chapter 1. Methodology and Scope
1.1. Market Segmentation and Scope
1.2. Research Methodology
1.2.1. Information Procurement
1.3. Information or Data Analysis
1.4. Methodology
1.5. Research Scope and Assumptions
1.6. Market Formulation & Validation
1.7. Country Based Segment Share Calculation
1.8. List of Data Sources
Chapter 2. Executive Summary
2.1. Market Outlook
2.2. Segment Outlook
2.3. Competitive Insights
Chapter 3. Algorithmic Trading Market Variables, Trends, & Scope
3.1. Market Lineage Outlook
3.2. Market Dynamics
3.2.1. Market Driver Analysis
3.2.2. Market Restraint Analysis
3.2.3. Industry Challenge
3.3. Algorithmic Trading Market Analysis Tools
3.3.1. Industry Analysis - Porter’s
3.3.1.1. Bargaining power of the suppliers
3.3.1.2. Bargaining power of the buyers
3.3.1.3. Threats of substitution
3.3.1.4. Threats from new entrants
3.3.1.5. Competitive rivalry
3.3.2. PESTEL Analysis
3.3.2.1. Political landscape
3.3.2.2. Economic and social landscape
3.3.2.3. Technological landscape
3.4. Pain Point Analysis
Chapter 4. Algorithmic Trading Market: Component Estimates & Trend Analysis
4.1. Segment Dashboard
4.2. Algorithmic Trading Market: Component Movement Analysis, 2024 & 2030 (USD Million)
4.3. Solution
4.3.1. Solution Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
4.3.1.1. Platforms
4.3.1.1.1. Platforms Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
4.3.1.2. Software Tools
4.3.1.2.1. Software tools Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
4.4. Services
4.4.1. Services Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
4.4.1.1. Professional Services
4.4.1.1.1. Professional Services Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
4.4.1.2. Managed Services
4.4.1.2.1. Managed Services Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
Chapter 5. Algorithmic Trading Market: Deployment Estimates & Trend Analysis
5.1. Segment Dashboard
5.2. Algorithmic Trading Market: Deployment Movement Analysis, 2024 & 2030 (USD Million)
5.3. Cloud
5.3.1. Cloud Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
5.4. On-premise
5.4.1. On-premise Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
Chapter 6. Algorithmic Trading Market: Trading Types Estimates & Trend Analysis
6.1. Segment Dashboard
6.2. Algorithmic Trading Market: Trading Types Movement Analysis, 2024 & 2030 (USD Million)
6.3. Foreign Exchange (FOREX)
6.3.1. Foreign Exchange (FOREX) Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
6.4. Stock Markets
6.4.1. Stock Markets Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
6.5. Exchange-Traded Fund (ETF)
6.5.1. Exchange-Traded Fund (ETF) Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
6.6. Bonds
6.6.1. Bonds Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
6.7. Cryptocurrencies
6.7.1. Cryptocurrencies Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
6.8. Others
6.8.1. Others Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
Chapter 7. Algorithmic Trading Market: Type of Traders Estimates & Trend Analysis
7.1. Segment Dashboard
7.2. Algorithmic Trading Market: Type of Traders Movement Analysis, 2024 & 2030 (USD Million)
7.3. Institutional Investors
7.3.1. Institutional Investors Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
7.4. Long-Term Traders
7.4.1. Long-Term Traders Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
7.5. Short-Term Traders
7.5.1. Short-Term Traders Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
7.6. Retail Investors
7.6.1. Retail Investors Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
Chapter 8. Algorithmic Trading Market: Regional Estimates & Trend Analysis
8.1. Algorithmic Trading Market Share, By Region, 2024 & 2030 (USD Million)
8.2. North America
8.2.1. North America Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.2.2. U.S.
8.2.2.1. U.S. Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.2.3. Canada
8.2.3.1. Canada Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.2.4. Mexico
8.2.4.1. Mexico Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.3. Europe
8.3.1. Europe Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.3.2. UK
8.3.2.1. UK Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.3.3. Germany
8.3.3.1. Germany Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.3.4. France
8.3.4.1. France Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.4. Asia Pacific
8.4.1. Asia Pacific Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.4.2. China
8.4.2.1. China Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.4.3. Japan
8.4.3.1. Japan Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.4.4. India
8.4.4.1. India Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.4.5. South Korea
8.4.5.1. South Korea Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.4.6. Australia
8.4.6.1. Australia Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.5. Latin America
8.5.1. Latin America Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.5.2. Brazil
8.5.2.1. Brazil Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.6. Middle East and Africa
8.6.1. Middle East and Africa Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.6.2. UAE
8.6.2.1. UAE Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.6.3. KSA
8.6.3.1. KSA Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
8.6.4. South Africa
8.6.4.1. South Africa Algorithmic Trading Market Estimates and Forecasts, 2018 - 2030 (USD Million)
Chapter 9. Competitive Landscape
9.1. Company Categorization
9.2. Company Market Positioning
9.3. Company Heat Map Analysis
9.4. Company Profiles/Listing
9.4.1. BNP Paribas Leasing Solutions
9.4.1.1. Participant’s Overview
9.4.1.2. Financial Performance
9.4.1.3. Product Benchmarking
9.4.1.4. Strategic Initiatives
9.4.2. AlgoTrader
9.4.2.1. Participant’s Overview
9.4.2.2. Financial Performance
9.4.2.3. Product Benchmarking
9.4.2.4. Strategic Initiatives
9.4.3. Argo Software Engineering
9.4.3.1. Participant’s Overview
9.4.3.2. Financial Performance
9.4.3.3. Product Benchmarking
9.4.3.4. Strategic Initiatives
9.4.4. InfoReach, Inc.
9.4.4.1. Participant’s Overview
9.4.4.2. Financial Performance
9.4.4.3. Product Benchmarking
9.4.4.4. Strategic Initiatives
9.4.5. Kuberre Systems, Inc.
9.4.5.1. Participant’s Overview
9.4.5.2. Financial Performance
9.4.5.3. Product Benchmarking
9.4.5.4. Strategic Initiatives
9.4.6. MetaQuotes Ltd.
9.4.6.1. Participant’s Overview
9.4.6.2. Financial Performance
9.4.6.3. Product Benchmarking
9.4.6.4. Strategic Initiatives
9.4.7. Symphony
9.4.7.1. Participant’s Overview
9.4.7.2. Financial Performance
9.4.7.3. Product Benchmarking
9.4.7.4. Strategic Initiatives
9.4.8. Tata Consultancy Services Limited
9.4.8.1. Participant’s Overview
9.4.8.2. Financial Performance
9.4.8.3. Product Benchmarking
9.4.8.4. Strategic Initiatives
9.4.9. VIRTU Finance Inc.
9.4.9.1. Participant’s Overview
9.4.9.2. Financial Performance
9.4.9.3. Product Benchmarking
9.4.9.4. Strategic Initiatives
9.4.10. AlgoBulls Technologies Private Limited
9.4.10.1. Participant’s Overview
9.4.10.2. Financial Performance
9.4.10.3. Product Benchmarking
9.4.10.4. Strategic Initiatives

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