Global Algorithm Trading Market, By Components (Solutions, Services), Trading Types (Foreign Exchange (FOREX), Stock Markets, Exchange-Traded Fund (ETF), Bonds, Cryptocurrencies, Others), Deployment Modes (On-premises, Cloud), Enterprise Size (Small and Medium-Sized Enterprises (SMEs), Large Enterprises), Country (U.S., Canada, Mexico, Brazil, Argentina, Rest of South America, Germany, Italy, U.K., France, Spain, Netherlands, Belgium, Switzerland, Turkey, Russia, Rest of Europe, Japan, China, India, South Korea, Australia, Singapore, Malaysia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific, Saudi Arabia, U.A.E, South Africa, Egypt, Israel, Rest of Middle East and Africa) Industry Trends and Forecast to 2028
Market Analysis and Insights ; Global Algorithm Trading Market
The algorithm trading market is expected to witness market growth at a rate of 12.10% in the forecast period of 2021 to 2028. Data Bridge Market Research report on algorithm trading market provides analysis and insights regarding the various factors expected to be prevalent throughout the forecast period while providing their impacts on the market’s growth. The rise in demand for demand for market surveillance is escalating the growth of algorithm trading market.
Algorithm trading is used to analyze every quote and trade in the stock market making use of predefined rules, back tested and placed at predefined levels. They assist in detecting opportunities for liquidity by turning knowledge into smart trading decisions. Cloud-based algorithmic trading platforms are highly being deployed as they offer maximum profit gains as these systems help traders automate their trading processes.
The increase in demand for fast, reliable and effective order execution across the globe acts as one of the major factors driving the growth of algorithm trading market. The presence favorable government regulations and high utilization of the system by institutional investors and big brokerage houses with the purpose of reducing costs associated with bulk trading accelerate the algorithm trading market growth. The growth in demand for market surveillance, rise in the need to decline transaction costs and increase in the deployment of cloud-based algorithmic trading because of various offered benefits such as effective management, easy trade data maintenance, cost-effectiveness and scalability further influence the algorithm trading market. Additionally, limited requirement of human interaction, high acceptance of advanced systems, expansion of small and medium-sized enterprises (SMEs), large enterprises and surge in investment positively affect the algorithm trading market. Furthermore, the integration of artificial intelligence (AI) and emergence of cryptocurrency extend profitable opportunities to the algorithm trading market players in the forecast period of 2021 to 2028.
On the other hand, lack of monitoring and rise in concerns regarding insufficient risk valuation capabilities act as the factors expected to obstruct the algorithm trading market growth. Issues with accuracy and consistency in algorithms are projected to challenge the algorithm trading market in the forecast period of 2021 to 2028.
This algorithm trading market report provides details of new recent developments, trade regulations, import export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on algorithm trading market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.
Algorithm Trading Market Scope and Market Size
The algorithm trading market is segmented on the basis of components, trading types, deployment modes and enterprise size. The growth among segments helps you analyze niche pockets of growth and strategies to approach the market and determine your core application areas and the difference in your target markets.
- On the basis of components, the algorithm trading market is segmented into solutions and services. Solutions are further segmented into platforms and software tools. Services are further segmented into professional services and managed services.
- On the basis of trading types, the algorithm trading market is segmented into foreign exchange (FOREX), stock markets, exchange-traded fund (ETF), bonds, cryptocurrencies and others. Others are further segmented into commodities, assets, credit default swaps, (CDS), interest rate swaps (IRS) and collateral mortgage.
- On the basis of deployment type, the algorithm trading market is segmented into on-premises and cloud.
- On the basis of enterprise size, the algorithm trading market is segmented into small and medium-sized enterprises (SMEs) and large enterprises.
Global Algorithm Trading Market Country Level Analysis
The algorithm trading market is analyzed and market size, volume information is provided by country, components, trading types, deployment modes and enterprise size as referenced above.
The countries covered in the global algorithm trading market report are the U.S., Canada and Mexico in North America, Brazil, Argentina and Rest of South America as part of South America, Germany, Italy, U.K., France, Spain, Netherlands, Belgium, Switzerland, Turkey, Russia, Rest of Europe in Europe, Japan, China, India, South Korea, Australia, Singapore, Malaysia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, South Africa, Egypt, Israel, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA).
North America dominates the algorithm trading market due to the rise in investments in trading technologies such as blockchain, government support for global trading, technological advancements, presence of algorithmic trading vendors and high usage various applications such as banks and financial institutions.
The country section of the report also provides individual market impacting factors and changes in regulation in the market domestically that impacts the current and future trends of the market. Data points like down-stream and upstream value chain analysis, technical trends and porter's five forces analysis, case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.
Competitive Landscape and Algorithm Trading Market Share Analysis
The algorithm trading market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies’ focus related to algorithm trading market.
The major players covered in the algorithm trading market report are Thomson Reuters, 63 moons technologies limited, VIRTU Financial Inc., Software AG, MetaQuotes Ltd, Symphony Limited, InfoReach, Inc., Argo Software Engineering, Kuberre Systems, Inc., Tata Consultancy Services Limited, QuantCore Capital Management, LLC, iRageCapital, Automated Trading Softtech Pvt. Ltd., Trading Technologies International, Inc, uTrade., Vela Labs, Inc., AlgoTrader among other domestic and global players. Market share data is available for global, North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA) and South America separately. DBMR analysts understand competitive strengths and provide competitive analysis for each competitor separately.
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