NEW YORK, Feb. 6, 2024 /PRNewswire/ -- The global algorithmic trading market size is estimated to grow by USD 11.19 billion from 2022 to 2027, according to Technavio. The market is estimated to grow at a CAGR of 12.23% during the forecast period. The algorithmic trading market is experiencing growth propelled by high demand for market surveillance. Compliance requirements are increasing, driving the need for tracking investment patterns and trading activities. Top players are optimizing data management strategies to address system shortcomings. Market surveillance aids in detecting manipulation and fraudulent behavior, fostering market growth by enhancing equity market infrastructure and risk management platforms to meet client needs.
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63 moons Technologies Ltd., AlgoBlocks, AlgoBulls Technologies Pvt. Ltd., AlpacaDB Inc., Argo SE, Auros, CRYPTO TECHFIN SL, InfoReach Inc., iRageCapital Advisory Pvt. Ltd., MetaQuotes Ltd., QuantConnect Corp., QuantCore Capital Management LLC, Refinitiv, Software AG, Symphony Fintech Solutions Pvt. Ltd., Tata Consultancy Services Ltd., Thomson Reuters Corp., uTrade, Wyden AG, and VIRTU Financial Inc. are some of the major companies.
Technavio has segmented the market based on Component (Solutions and Services), End-user (Institutional investors, Retail investors, Long-term investors, and Short-term investors), and Geography (North America, APAC, Europe, South America, and Middle East and Africa).
- The solutions segment will be significant during the forecast period.
- North America will contribute 35% to the growth during the forecast period.
Insights on the contribution of various segments including country and region wise historical data (2017 to 2021), and forecast size (2023 to 2027) - Download a Sample Report
"Technological advancement is an emerging trend fueling growth, however, challenges including the lack of awareness may hamper the growth."
Insights on Drivers, trends, & Challenges, historic period(2017 to 2021), and forecast period(2023 to 2027)- Request a sample report!
What are the key data covered in this Algorithmic Trading Market report?
- CAGR during the forecast period
- Detailed information on factors that will drive the growth of the Algorithmic Trading Market between 2023 and 2027
- Precise estimation of the Algorithmic Trading Market size and its contribution to the parent market
- Accurate predictions about upcoming trends and changes in consumer behavior
- Growth of the Algorithmic Trading industry across North America, Europe, APAC, South America, and Middle East and Africa
- A thorough analysis of the competitive landscape and detailed information about vendors
- Comprehensive analysis of factors that will challenge the growth of Algorithmic Trading vendors
Technavio's SUBSCRIPTION platform
High-frequency trading and quantitative trading are driving the demand
The algorithmic trading industry is propelled by the increasing adoption of automated trading systems and algorithmic trading strategies. High-frequency trading and quantitative trading are driving the demand for algorithmic trading software and platforms. These technologies enhance market liquidity and facilitate financial market automation. Furthermore, the continuous development of trading algorithms fuels innovation in algorithmic trading, driving market growth and efficiency.
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Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging trends and provide actionable insights to help businesses identify opportunities and develop effective strategies to optimize their positions. With over 500 specialized analysts, Technavio's report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio's comprehensive coverage, extensive research, and actionable insights to identify opportunities in existing and potential markets and assess their competitive positions within changing scenarios.
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SOURCE Technavio
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