The global algorithmic trading market reached a value of US$ 13.0 Billion in 2021. Looking forward, IMARC Group expects the market to reach US$ 24.0 Billion by 2027, exhibiting a CAGR of 11.4% during 2022-2027. Keeping in mind the uncertainties of COVID-19, we are continuously tracking and evaluating the direct as well as the indirect influence of the pandemic. These insights are included in the report as a major market contributor.
Algorithmic trading, or Algo-trading, is the procedure of using computer programs with a pre-defined set of instructions to administer a trading activity. The instructions are based on prices, timing, quantity and numerous other parameters of a mathematical model. It aims to generate profits, reduce transactional costs and allow investors to take control of the trading process through a computer. Apart from this, algo-trading makes the market more flexible, as well as systematic, by ruling out any human influences. It is also used for high-frequency trading (HFT) that involves placing large trade orders across multiple markets and facilitate prompt decision-making.
Algo-trading enables quick profit generation and an increased frequency, which is practically impossible for any human trader. This benefit of algorithmic trading is the key factor driving the market growth. Enterprises are emphasizing on policies for building low-risk infrastructure and optimizing data management strategies through algorithmic trading. Furthermore, the emergence of Artificial Intelligence (AI) is acting as a major growth-inducing factor for the market. The AI assists in creating efficient trading opportunities through portfolio diversification and the global distribution of savings, along with risk sharing. In addition to this, the rising trend of cloud computing across both the developed and emerging nations is also catalyzing the growth of the market. Vendors offer cloud-based trading options to automate the trading process, reduce operational costs, and provide transactional flexibility to consumers. Dealers are also establishing risk management platforms with the aim to provide market surveillance monitoring and detect fraudulent activities in the automated trading system.
IMARC Group’s latest report provides a deep insight into the global algorithmic trading market covering all its essential aspects. This ranges from macro overview of the market to micro details of the industry performance, recent trends, key market drivers and challenges, SWOT analysis, Porter’s five forces analysis, value chain analysis, etc. This report is a must-read for industry players, investors, researchers, consultants, business strategists, and all those who have any kind of stake or are planning to foray into the algorithmic trading market in any manner.
Key Market Segmentation:
IMARC Group provides an analysis of the key trends in each sub-segment of the global algorithmic trading market, along with forecasts at the global and regional level from 2022-2027. Our report has categorized the market based on trading type, components, deployment model and organization size.
Breakup by Trading Type:
Foreign Exchange (FOREX)
Exchange-Traded Fund (ETF)
Breakup by Components:
Breakup by Deployment Model:
Breakup by Organization Size:
Small and Medium Enterprises
Breakup by Region:
Middle East and Africa
The report has also analyzed the competitive landscape of the market with some of the key players being 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, and 63 Moons Technologies Ltd. etc.
Key Questions Answered in This Report
1. What is the expected growth rate of the global algorithmic trading market during 2022-2027?
2. What are the key factors driving the global algorithmic trading market?
3. What has been the impact of COVID-19 on the global algorithmic trading market?
4. What is the breakup of the global algorithmic trading market based on the trading type?
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 is the breakup of the global algorithmic trading market based on the organization size?
8. What are the key regions in the global algorithmic trading market?
9. Who are the key players/companies in the global algorithmic trading market?