Algorithmic Trading Market
Algorithmic Trading Market (Component - Software (On-Premise, Cloud (Private and Public Cloud), Hybrid), Services (Managed Services, Professional Services (Maintenance, Integration and Consulting)); Trading Type - Forex, Stock Markets, Commodities, Bonds, Cryptocurrency) - Global Industry Analysis, Size, Share, Growth, Trends, and Forecast 2018 - 2026
Press Release :
Algorithmic Trading Market - Snapshot
Algorithmic trading is a process of using an automated computer programed to follow a defined set of trading instructions for placing a trade, accounting for factors such as time, price, and volume. Algorithmic trading or algo trading is a technology platform providing advantage of both artificial intelligence and human intelligence. Algorithmic trading helps in reducing transaction costs, allowing investment managers to take control of their own trading procedures. The main objective of such software is not just to maximize profits but also to control market risk and execution costs. The market for algorithmic trading is forecasted to grow to US$ 21,807.6Mn by 2026, recording a CAGR of 10.2%.
End users and prospective adopters are attracted to the several benefits that algorithmic trading over manual ones. Faster execution, less risk of errors, concurrent focus on several market conditions are some of the key benefits which is evident in high-frequency trading (HFT). In addition, adopters have been able to backtest their tradition system. Most importantly, the popularity of products in the algorithmic trading market has stemmed from the fact that it has been successful in taking more rationalized decision, the reason having to do with stripping the decisions of human emotions. Post the economic recession of 2008, rules-based decision-making was internalized in algorithmic trading strategies. Rise in different forms of trading has made people look toward the advantages of algorithmic trading. A slew of new strategies have emerged in the market attracting the attention of investment firms and traders of all size.
Key strategies in the marketplace include trend-following strategies, arbitrage opportunities, index fund rebalancing, and mathematical model-based strategies. However, some genuine concerns are worrying end users and market players. Since, a large part of the trading process is automated, this removes any scope of applying discretion in making choices, a key pillar of economic and financial decision-making. Moreover, system issues, such as power losses and connectivity problems, need to be constantly monitored so as to prevent any huge crash. Also, the need for high-end resources might hurt cost-sensitive consumers in the algorithmic trading market.
Moreover, there is a lack of agreement among regulators on how the algorithmic trading must be adopted and monitored, leading to some serious snags for adopters and industry players in the market. Moreover, since there always exist the possibility of irrationality in economic models, at times this type of trading may fall short. In the times of Covid-19 customer sentiment has reached an all-time low, hampering the prospect of substantive spending. This has also hurt the prospects of the algorithmic trading market. Nonetheless, last few months have also seen improvement in overall consumer spending, which will add momentum to the market.
The algorithm trading market has experienced substantial growth due to large number of financial firms opting for increasing automation in trading processes. Integrated financial markets or an open market economy such as the European Union helps local vendors in buying foreign assets with reduced risks. Contribution of several international markets has aided developing countries in generating opportunities for portfolio diversification, global distribution of savings, and also risk sharing.
The algorithmic trading market is driven by the emergence of AI and algorithms in the financial service sector. This in turn is boosting the algorithmic trading sector globally. Furthermore, increasing adoption of non-equity trading algorithms by institutional asset managers is enhancing the use of artificial intelligence in the financial services sector. The global algorithmic trading market is anticipated to grow significantly during the forecast period, attributed to rapidly growing demand for market surveillance. By using market surveillance technology, traders are able to keep track of their trading activities and investment pattern.The rising need to build an economy with global as well as regional interdependencies force key vendors to formulate effective marketing strategies and develop new solutions for market surveillance. In addition, many companies are inclined toward the use of algorithmic trading in order to reduce market risks and transaction cost.
However, stringent regulatory guidelines are affecting the large-scale use of algorithmic trading. To conduct algorithmic trading and high frequency trading (HFT), all trading companies should inform the national regulatory authority and submit an application for approval from the regulatory authority.The regulatory environment for algorithmic trading and HFT practices are not favorable in some of the major countries such as China. There are barriers to the widespread application of automated trading, specifically for high frequency trading in financial markets across the country. This is consequently restricting the growth of the algorithmic trading market across the Asia Pacific region, as China is one of the major markets for the stock exchange.
A key trend boosting market growth is the growing adoption of cloud based solutions. The technology is gaining popularity in capital markets due to its flexibility, scalability, cost-effectiveness, and massive processing power. Presently, capital markets and financial institutions are unceasingly adopting cloud-based applications in order to enhance their efficiency and productivity as well as providing better custom applications and security to their customers.
The algorithmic trading market is segmented on the basis of components and trading type. Based on components, the market is segmented into software (on premise, cloud (private and public cloud) hybrid) and services (managed services, professional services (maintenance, integration and consulting). Based on trading type, the market is segmented into forex, stock markets, commodities, bonds, and cryptocurrency.
From a geographical standpoint, North America is expected to hold a major share in the algorithmic trading market.Growth in this region is attributed to strong adoption and penetration of algorithmic trading platform, software and services, as well as considerable application of algorithm trading in different end-user segments across the region. Developed markets and emerging markets have embraced this technology in the securities market. Asia Pacific region is expected to witness lucrative growth due to rising adoption of such software from countries such as India, Japan, Philippines, and Singapore. Furthermore, the markets in Middle East and Africa (MEA) and South America regions are also expected to grow significantly during the forecast period.
Growing awareness and adoption of algorithmic trading across Asia Pacific and South America is offering new opportunities for key players operating in the global algorithmic trading market. The algorithmic commodity market in India is expected to expand at a faster pace during the forecast period, owing to SEBI’s efforts to ease algo trade rules in the commodity market. In April 2018, SEBI raised the limit of orders that can be processed per second by a user from 20 orders per second to 100 orders per second.
Attracted by this fast expanding market, underlying technological advancements, and rising trend of algorithmic trading, many players are driven to develop comprehensive suites of software and services for all trading types. Existing software providers are rapidly expanding their distribution network in order to reach the most distant customers.Some of the key players profiled in the algorithmic trading market report include Trading Technologies International, Inc., Argo Software Engineering, Inc., Automated Trading SoftTech Pvt. Ltd., InfoReach, Inc., Kuberre Systems, MetaQuotes Software Corp., Software AG, Thomson Reuters Corporation, uTrade, and Vela Trading Systems LLC (OptionsCity Software, Inc.).
Algorithmic Trading Market: Overview
The algorithmic trading market report provides analysis for the period 2016 – 2026, wherein the period from 2018 to 2026 is the forecast period and 2017 is the base year. The report covers all the major trends and technologies playing an influential role in the market’s growth over the forecast period. It also highlights the drivers, restraints, and opportunities for the analysis of market growth during the said period. The study provides a complete perspective on the evolution of the global algorithmic trading market throughout the above mentioned forecast period in terms of revenue (US$ Mn).
The market overview section of the report demonstrates market dynamics such as the drivers, restraints, and opportunities that influence the current nature and future statusof this market, key indicators, end-user adoption analysis, and trends of the market. Further, key market indicators included in the report provide significance of the factors which are capable of changing the market scenario. These indicators are expected to define the market position during the forecast period and provide an overview about the global algorithmic trading market. A market attractiveness analysis has also been provided for every segment in the report, in order to provide a thorough understanding of the overall scenario in the algorithmic trading market. The report also provides an overview of various strategies adopted by key players in the market.
Global Algorithmic Trading Market: Scope of the Report
The report segments the market on the basis of components - Software (on premise, cloud (private and public cloud) hybrid), and services (managed services, professional services (maintenance, integration and consulting). Based on trading type, the market is segmented into forex, stock markets, commodities, bonds, and cryptocurrency.The report provides in-depth segment analysis of the global algorithmic trading market, thereby providing valuable insights at the macro as well as micro levels.
The report also highlights the competitive landscape of the global algorithmic trading market, positioning all the major players according to their presence in different regions of the world and recent key developments initiated by them in the market. The comprehensive algorithmic trading market estimates are the result of our in-depth secondary research, primary interviews and in-house expert panel reviews. These market estimates have been analyzed by taking into account the impact of different political, social, economic, and technological factors along with the current market dynamics affecting the growth of the algorithmic trading market.
This report provides all the essential information required to understand the key developments in the algorithmic trading market, and growth trends of each segment and region. It also includes companies’ strategies, financial information, SWOT analysis, and developments under the company profile section. Also, the report provides insights related to trends and their impact on the market. Furthermore, Porter’s Five Forces analysis explains the five forces, namely buyers bargaining power, suppliers bargaining power, threat of new entrants, threat of substitutes, and degree of competition in the algorithmic trading market .The report also provides the comprehensive ecosystem analysis for the algorithmic trading market. It explains the various participants including software & platform vendors, system integrators, and trading platforms of the ecosystem in the market.
Global Algorithmic Trading Market: Research Methodology
The research methodology is a perfect combination of primary research, secondary research, and expert panel reviews. Secondary research sources such as annual reports, company websites, broker reports, financial reports, SEC filings and investor presentations, national government documents, internal and external proprietary databases, statistical databases, relevant patent and regulatory databases, market reports, government publications, statistical databases, World Bank database, and industry white papers are usuallyreferred.
Primary research involves telephonic interviews, e-mail interactions, and face-to-face interviews for detailed and unbiased reviews on the algorithmic tradingmarket,across geographies. Primary interviews are usually conducted on an ongoing basis with industry expertsand participants in order to get latest market insights and validate the existing data and analysis. Primary interviews offer firsthand information on important factors such as market trends, market size, competitive landscape,growth trends, and outlook, etc. These factors help to validate and strengthen secondary research findings and also help to develop the analysis team’s expertise and market understanding. Moreover, the data collected and analyzed from secondary and primary research is again discussed and examined by our expert panel.
Global Algorithmic Trading Market: Competitive Dynamics
The research study includes profiles of leading companies operating in the global algorithmic trading market. Some of the key players profiled in the algorithmic trading market include Trading Technologies International, Inc., Argo Software Engineering, Inc., Automated Trading SoftTechPvt. Ltd., InfoReach, Inc., Kuberre Systems, MetaQuotes Software Corp., Software AG, Thomson Reuters Corporation, uTrade, and Vela Trading Systems LLC (OptionsCity Software, Inc.).
The algorithmic trading market has been segmented as below:
Market Segmentation: Global Algorithmic Trading Market
By Trading Type