The Global Algorithmic Trading Market size to grow from USD 11.1 billion in 2019, at a Compound Annual Growth Rate (CAGR) of 11.10% during the forecast period. The global algorithmic trading market reached a value of US$ 13.0 Billion in 2021 and is expected to reach US$ xx.xx Billion by 2027; the rise in the integration of financial markets and market surveillance is providing thrust to the algorithm trading market. The growth in the financial institution and rise in investments is creating a positive impact on the market growth. Algorithmic trading is a form of automation, where, a computer program is executed on a defined set of instructions that includes the buying or selling of an asset. Traditionally, traders keep track of their trading activities and investment portfolio by using market surveillance technology.

Benefits of Algorithmic Trading

Algo-trading provides the following benefits:

1. Trades are executed at the best possible prices.

2. Trade order placement is instant and accurate (there is a high chance of execution at the desired levels).

3. Trades are timed correctly and instantly to avoid significant price changes.

4. Reduced transaction costs.

5. Simultaneous automated checks on multiple market conditions.

6. Reduced risk of manual errors when placing trades.

7. Algo-trading can be backtested using available historical and real-time data to see if it is a viable trading strategy.

8. Reduced the possibility of mistakes by human traders based on emotional and psychological factors.

Segment Review

The algorithmic trading market is segmented on the basis of component, type, deployment mode, type of traders, and region. On the component, it is categorized into solution and services. On the basis of type, it is classified into stock markets, FOREX, ETF, bonds, cryptocurrencies, and others. 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.

Regional Analysis

The demand in the Asia Pacific region is largely fulfilled by China, India, and Japan. Asia Pacific (APAC) is expected to grow at the highest CAGR during the forecast period. In APAC, the highest growth rate can be attributed to the heavy investments made by private and public sectors for enhancing their trading technologies, resulting in an increased demand for algorithmic trading solutions used for automating the trading process.

In 2018, the North American market accounted for the majority of the global algorithm trading market, and it is expected to continue to lead the market all through the forecast timeframe. The market's rise may be attributed to the high level of technical knowledge required to create the algorithm using Python, MATLAB, C++, Perl, and JAVA. North America heads the algorithmic trading market for a variety of reasons, including massive investments in trading technologies and increased government support for global trading. Furthermore, the region's extensive presence of top algorithmic trading vendors propels market growth.

Key players profiled in the global algorithmic trading market report includes

Thomson Reuters (US), 63 moons (India), Virtu Financial (US), Software AG (Germany), MetaQuotes Software (Cyprus), Symphony Fintech (India), InfoReach (US), Argo SE (US), Kuberre Systems (US), Tata Consultancy Services (India), QuantCore Capital Management (China), iRageCapital (India), Automated Trading SoftTech (India), Tethys (US), Trading Technologies (US), uTrade (India),Vela (US), AlgoTrader (Switzerland).

Critical questions the report answers

1. What are the current trends that are driving the algorithmic trading market?

2. In which trading type most of the financial institutions are deploying algorithmic trading?

3. Where will all these developments take the industry in the mid- to long-term?

4. Who are the top vendors in the market and what is their competitive analysis?

5. What are the drivers and challenges of the algorithmic trading market?