Algorithmic trading is also referred as black-box trading, automated trading, or algo-trading. It is a method that uses a computer program that follows a defined set of instructions or an algorithm to administer trading activity. An algorithm is fed into a computer program to automatically perform the trade whenever the command is met. An algorithm can be based on different number of input pointers such as price, quantity, timing, or other metrics. It offers several benefits to market participants such as it executes trades at the best possible prices; simultaneous automated checks on multiple market conditions; trades timed correctly and instantly; and reduced transaction costs due to lack of human intervention.
Factors such as rise in demand for reliable, fast, and effective order execution; emergence of favorable government regulations; and the need for market surveillance primarily drive the growth of the global algorithmic trading market. In addition, rise in demand for reducing the transaction costs fuels the demand for algorithmic trading. However, insufficient risk valuation capabilities may hamper the market growth to some extent. On the other hand, emergence of AI and algorithms in the financial services is expected to provide lucrative opportunities for the market growth during the forecast period. In addition, rise in demand for cloud-based solutions is anticipated to be opportunistic for the market growth during the forecast period.
The algorithmic trading market is segmented on the basis of component, type, deployment mode, type of traders, and region. On the basis of component, it is categorized into solution and services. On the basis of type, it is classified into stock markets, FOREX, ETF, bonds, and cryptocurrencies. As per the deployment mode, it is classified into cloud and on-premise. Depending on type of traders, it is divided into institutional investors, long-term traders, short-term traders, and retail investors. Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
The company profiles of algorithmic trading market players included in this report are 63MOONS, Virtu Financial, Software AG, Refinitiv Ltd. MetaQuotes Software Corp. Symphony Fintech Solutions Pvt Ltd. Argo SE, Tata Consultancy Services, Algo Trader AG, and Tethys.
KEY BENEFITS FOR STAKEHOLDERS
- The study provides an in-depth analysis of the algorithmic trading market along with current trends and future estimations to elucidate imminent investment pockets.
- Information about key drivers, restrains, and opportunities and their impact analysis on the market size is provided in the report.
- Porter's five forces analysis illustrates the potency of buyers and suppliers operating in the industry.
- The quantitative analysis of algorithmic trading market for the period 2020-2027 is provided to determine the market potential.

KEY MARKET SEGMENTS
BY COMPONENT
- Solution
- Services

BY TYPE
- Stock Markets
- FOREX
- ETF
- Bonds
- Cryptocurrencies
- Others

BY DEPLOYMENT MODE

- Cloud
- On-Premise

BY TYPE OF TRADERS

- Institutional Investors
- Long-Term Traders
- Short-Term Traders
- Retail Investors



BY REGION
- North America
o U.S.
o Canada

- Europe
o UK
o Germany
o France
o Spain
o Rest of Europe

- Asia-Pacific
o China
o India
o Japan
o Australia
o South Korea
o Rest of Asia-Pacific

- LAMEA
o Latin America
o Middle East
o Africa


KEY MARKET PLAYERS
- 63MOONS
- Virtu Financial
- Software AG
- Refinitiv Ltd.
- MetaQuotes Software Corp.
- Symphony Fintech Solutions Pvt Ltd.
- Argo SE,
- Tata Consultancy Services
- Algo Trader AG
- Tethys
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