A recent report published by Infinium Global Research on the algorithmic trading market provides an in-depth analysis of segments and sub-segments in the global as well as the regional algorithmic trading market. The study also highlights the impact of drivers, restraints, and macro indicators on the global and regional algorithmic trading market over the short term as well as long term. The report is a comprehensive presentation of trends, forecast, and dollar values of the global algorithmic trading market. According to the report, the global algorithmic trading market is projected to grow at a CAGR of 12.0% over the forecast period of 2020-2026.
Algorithmic trading is used for executing securities trading orders with the help of automated and pre-programmed trading instructions. In order to make decisions to buy or sell financial securities on an exchange, algorithmic trading use complex formulas, mathematical models, and human oversight. Algorithmic trading is used for a wide variety of applications including order execution, arbitrage, and trend trading strategies. Algorithmic trading saves the time required for scanning the markets and executing trades almost instantly. Institutional investors and big brokerage mainly use algorithmic trading houses to cut down on costs associated with trading. This type of trading is especially beneficial for large order sizes that may comprise as much as 10% of the overall trading volume. It also allows faster and easier execution of orders, making it attractive for exchanges. This, in turn, enables traders and investors to quickly book profits off small changes in price.
The novel coronavirus (COVID-19) pandemic has a fairly positive effect on the algorithmic trading market. The financial markets have witnessed drastic fluctuation over the pandemic period. The demand for algorithmic trading particularly from the currency market increased during the pandemic. The growth in trading volumes is concentrated on some clients such as fund managers, who are turning to automation during lockdowns due to the difficulties trading from home. Furthermore, as extreme volatility had persisted over an extended period during the crisis, algorithms have learned and adapted according to the market trends. Latest machines are also able to keep up with orders and feed them into different trading platforms to achieve better prices.
The growing trading activities across the major stock exchanges are the major driving factors for the growth of the algorithmic trading market. The volume of securities in these exchanges has also increased augmenting the demand for automated solutions in order to gain better margins. Moreover, the growing adoption of cloud-based services by traders is anticipated to boost the market further. Traders use cloud-based solutions for various applications including backtesting, trading strategies, and run-time series analysis to execute the trade. Traders prefer cloud services as they are cost-efficient than building separate data centers for services such as data storage, backup and recovery, data management, and trading networks. However, a lack of risk valuation capabilities and inadequate monitoring policies is anticipated to hamper the market growth. Nevertheless, the development of AI-based solutions for the financial sector is anticipated to support the growth of algorithmic trading over the forecast period. Trading activities in combination with AI adapt to the market conditions, learn from experiences, and make trade decisions accordingly.
In terms of geography, North America generated the highest revenue in the global algorithmic trading market. The domination of the North American region in the global algorithmic trading market is mainly due to the higher adoption of advanced technologies by the end-users. Moreover, the market players in the region are developing innovative trading algorithms in order to gain higher profit margins. Furthermore, the presence of major market players including Thomson Reuters, InfoReach, Virtu Financial, Vela, and others are further supporting the growth of the North America algorithmic trading market. On the other hand, the Asia Pacific region is anticipated to grow with the fastest CAGR over the forecast period in the global algorithmic trading market. The heavy investment by the public and private sector in technology development for trading is majorly driving the growth of the Asia Pacific algorithmic trading market.
The report on the global algorithmic trading market covers segments such as component and trading type. On the basis of component, the sub-markets include software, cloud, and services. On the basis of trading type, the sub-markets include stock markets, commodities, forex, cryptocurrency, and bonds.
The report provides profiles of the companies in the market such as Trading Technologies International, Inc., uTrade Solutions Private Ltd., Vela Trading Technologies LLC, MetaQuotes Software Corp., Kuberre Systems, Inc., InfoReach, Inc., Automated Trading SoftTech Pvt. Ltd., ARGO GROUP, Thomson Reuters Corporation, and Software AG.
The report provides deep insights into the demand forecasts, market trends, and micro and macro indicators. In addition, this report provides insights into the factors that are driving and restraining the growth in this market. Moreover, The IGR-Growth Matrix analysis given in the report brings an insight into the investment areas that existing or new market players can consider. The report provides insights into the market using analytical tools such as Porter's five forces analysis and DRO analysis of the algorithmic trading market. Moreover, the study highlights current market trends and provides forecast from 2020-2026. We also have highlighted future trends in the market that will affect the demand during the forecast period. Moreover, the competitive analysis given in each regional market brings an insight into the market share of the leading players.