Global Algorithmic Trading Market size was valued at USD 15.76 Bn. in 2023 and the total Algorithmic Trading revenue is expected to grow by 10.6 % from 2024 to 2030, reaching nearly USD 31.90 Bn.
Algorithmic Trading Market Overview:
In the Algorithmic Trading Market, the solution category dominated the market and accounted largest market share in the year 2023. The lack of human participation as well as rapid and precise trade order placement has reduced transaction costs, which contributed to the market's rise. Participants in the market are providing innovative algorithmic trading solutions to meet the different needs of the customers. Because the extensive acceptance of professional services among end-users guarantees the successful and seamless operation of algorithmic trading solutions. The services segment is expected to gain popularity during the forecast period. The adoption of professional services is rising among end-users to ensure the effective running of trading solutions throughout the process.
Foreign Exchange (FOREX), Stock Markets, Exchange-Traded Funds (ETF), Bonds, Cryptocurrencies, and other financial instruments make up the market. The Exchange-Traded Funds (ETF) Market segment dominated the market and held the highest revenue share of 33% in the year 2023. Owing to the fact that it offers traders low average cost and permits them to maximize earnings from ETFs. The stock market segment is the second largest market in the year 2023 and is expected to dominate the market during the forecast period. The stock market is considered one of the leading asset classes for trading, a managed, and controlled environment. Whereas the cryptocurrencies segment is expected to witness important growth throughout the forecast period. Interest of trading professionals is rising in cryptocurrency trading which leads to market growth.
Algorithmic Trading Market Key Players
1. Algo Trader GmbH (Switzerland)
2. Trading Technologies (USA)
3. Info Reach (USA)
4. Tethys Technology (USA)
5. Lime Brokerage LLC (USA)
6. Flex Trade Systems (USA)
7. Tower Research Capital (USA)
8. Virtu Financial (USA)
9. Hudson River Trading (USA)
10. Citadel (USA)
11. Technologies International (USA)
12. Argo Software Engineering (USA)
13. Automated Trading Soft-Tech (India)
14. Kuberre Systems (USA)
15. Meta Quotes Software Corp. (Cyprus)
16. Software AG (Germany)
17. Thomson Reuters Corporation (Canada)
18. uTrade (India)
19. Vela Trading Systems LLC (USA)
Key questions answered in the Algorithmic Trading Market are:
- What is Algorithmic Trading ?
- What was the Algorithmic Trading market size?
- What is the growth rate of the Algorithmic Trading Market?
- Which are the factors expected to drive the Algorithmic Trading market growth?
- What are the different segments of the Algorithmic Trading Market?
- What growth strategies are the players considering to increase their presence in Algorithmic Trading ?
- What are the upcoming industry applications and trends for the Algorithmic Trading Market?
- What are the recent industry trends that can be implemented to generate additional revenue streams for the Algorithmic Trading Market?
- Who are the leading companies and what are their portfolios in Algorithmic Trading Market?
- What segments are covered in the Algorithmic Trading Market?
- Who are the key players in the Algorithmic Trading market?
Key Offerings:
- Past Market Size and Competitive Landscape
- Past Pricing and price curve by region
- Market Size, Share, Size Forecast by different segment |
- Market Dynamics – Growth Drivers, Restraints, Opportunities, and Key Trends by Region
- Market Segmentation – A detailed analysis by segment with their sub-segments and Region
- Competitive Landscape – Profiles of selected key players by region from a strategic perspective
- Competitive landscape – Market Leaders, Market Followers, Regional player
- Competitive benchmarking of key players by region
- PESTLE Analysis
- PORTER’s analysis
- Value chain and supply chain analysis
- Legal Aspects of Business by Region
- Lucrative business opportunities with SWOT analysis
- Recommendations
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