Algorithmic Trading Market – Growth, Trends, COVID-19 Impact, and Forecasts (2021 – 2027)

Algorithmic Trading Market was valued at US$ 11.66 Bn. in 2020 and is expected to reach US$ 23.60 Bn. by 2027, at a CAGR of 10.6% during a forecast period.

Algorithmic Trading Market Overview:

The systematic process of executing automatic pre-programmed trading instructions while analyzing variables such as volume, price, and time is known as algorithmic trading. It uses powerful mathematical techniques to aid in the decision-making process in the financial sector. It is utilized to provide traders an advantage over traditional human traders in terms of data processing speed. Algorithmic trading uses complex computations, mathematical models, and human oversight to make decisions about whether to buy or sell financial instruments on an exchange. Algorithmic traders commonly use high-frequency trading equipment, which allows a corporation to make tens of thousands of trades per second. Algorithmic Trading Market To know about the Research Methodology :- Request Free Sample Report The report has covered the market trends from 2016 to forecast the market through 2027. 2020 is considered a base year. Special attention is given to 2020 and effect of lockdown on the demand and supply, and also the impact of lockdown for next two years on the market. Some companies have done well in lockdown also and specific strategic analysis of those companies is done in the report.

COVID-19 Impact Analysis:

The COVID-19 pandemic has no impact on the algorithmic trading market's growth, as the adoption of algorithmic trading solutions has risen in the face of unprecedented circumstances. Because of the rising movement toward algorithmic trading for making judgments at a very rapid pace while decreasing human errors, the COVID-19 pandemic has considerably boosted the growth rate of the algorithmic trading market. In a recent paper, the Reserve Bank of Australia indicated that the COVID-19 outbreak may have simply accelerated the industry's shift toward electronic trading. Furthermore, during the pandemic, market participants created innovative algorithmic trading products to better serve the higher trade volumes. This aspect is what propels the market forward. Cowen, an American international independent investment bank and financial services corporation, for example, launched an algorithmic trading solution in March 2021 to assist institutional clients in navigating market fluctuations created by rising retail trading volumes.

Algorithmic Trading Market Dynamics:

The global Algorithmic Trading Market is primarily driven by factors such as technological advancements, which have resulted in an increase in demand for cloud-based solutions, consequently adding to the market's growth. Growing awareness and adoption of algorithmic trading around the world is providing new opportunities for important players in the global Algorithmic Trading Market. Furthermore, huge brokerage firms and institutional investors are increasingly turning to algorithmic trading to reduce trading expenses. As a result, algorithmic trading allows for smoother and faster order execution, making it appealing to exchanges, which will drive the Algorithmic Trading Market forward over the forecast period. Algorithmic Trading Market DynamicsFurthermore, the rise of the Algorithmic Trading Market is expected to be aided by the emergence of AI in the financial services sector. During the forecast period, the market will be fueled by the advent of stringent government regulations and the growing requirement for market surveillance. However, the market's growth is being stifled by a lack of risk valuation capabilities and observation. Top Impacting Factor: The surge in need for reliable, rapid, and effective order execution; the advent of favorable government rules; and the necessity for market surveillance are all driving forces in the global algorithmic trading industry. Furthermore, the need for algorithmic trading is being fueled by growth in the desire for lower transaction costs. Inadequate risk valuation capabilities, on the other hand, may limit market growth to some extent. During the forecast period, however, the advent of AI and algorithms in financial services is expected to give the profitable potential for market growth.

Algorithmic Trading Market segment analysis:

Based on component, the market is divided into two categories: solutions and services. In the Algorithmic Trading Market, the solution category accounted largest market share of xx% in 2020. Reduced transaction costs due to the lack of human participation, as well as rapid and precise trade order placement, contributed to the market's rise. In addition, market participants are providing innovative algorithmic trading solutions to meet their customers' different needs. However, due to the widespread acceptance of professional services among end-users, which guarantees the successful and seamless operation of algorithmic trading solutions, the services category is likely to develop significantly during the forecast period. Based on trading type, Foreign Exchange (FOREX), Stock Markets, Exchange-Traded Funds (ETF), Bonds, Cryptocurrencies, and other financial instruments make up the market. The exchange-traded fund segment is expected to increase significantly throughout the forecast period, owing to the fact that it offers traders low average cost, allowing them to maximize earnings from ETFs. Algorithmic Trading Market

Algorithmic Trading Market Regional Insight:

The North America region held the largest market share of xx% in 2020. The primary factors driving market growth throughout the forecast period include increased investments in trading technologies (such as blockchain), the growing presence of algorithmic trading suppliers, and growing government backing for global trading. Furthermore, market growth is likely to be stimulated by significant technology advancements and widespread deployment of algorithm trading in various applications such as banks and financial institutions across the area. Algorithmic trading accounts for 60-73 % of all stock trading in the United States. According to Select USA, the financial markets in the United States are the world's largest and most liquid. Sentient Technologies, a hedge fund run by an AI startup based in the United States, developed an algorithm that analyses millions of data points to uncover trading patterns and forecast trends. Sentient's algorithms analyses trillions of simulated trading scenarios to find and combine successful trading patterns and develop new techniques. Not only does this save time and effort, but it also ensures the highest level of accuracy. Recent Developments: • Investment Technology Group, a global financial technology company that helps top brokers and asset managers increase returns for customers around the world, was acquired by Virtu Financial in March 2019. For Virtu Financial's broker-neutral client offerings, the acquisition would adopt a Client Information Security Program (CISP). • Algo Trader announced the release of AlgoTrader 6.0 in March 2020. AlgoTrader 6.0 now provides crypto exchange adapters for Deribit, Huobi, Kraken, and Bithumb, in addition to the previous crypto adapters. For all market data adapters, AlgoTrader 6.0 provides full support for Level II Order Book data. The new AlgoTrader UI Order Book widget displays all available BUY and SELL orders at each price level to the user. The objective of the report is to present a comprehensive analysis of the Algorithmic Trading market to the stakeholders in the industry. The past and current status of the industry with the forecasted market size and trends are presented in the report with the analysis of complicated data in simple language. The report covers all the aspects of the industry with a dedicated study of key players that include market leaders, followers, and new entrants. PORTER, PESTEL analysis with the potential impact of micro-economic factors of the market have been presented in the report. External as well as internal factors that are supposed to affect the business positively or negatively have been analyzed, which will give a clear futuristic view of the industry to the decision-makers. The report also helps in understanding the Algorithmic Trading market dynamics, structure by analyzing the market segments and projects the Algorithmic Trading market size. Clear representation of competitive analysis of key players by product, price, financial position, product portfolio, growth strategies, and regional presence in the Algorithmic Trading market make the report investor’s guide.

Algorithmic Trading Market Scope: Inquire before buying

Algorithmic Trading Market

Algorithmic Trading Market, by Region

• North America • Europe • Asia Pacific • Middle East and Africa • South America

Algorithmic Trading Market Key Players

• Algo Trader GmbH • Trading Technologies • Info Reach • Tethys Technology • Lime Brokerage LLC • Flex Trade Systems • Tower Research Capital • Virtu Financial • Hudson River Trading • Citadel • Technologies International • Argo Software Engineering • Automated Trading Soft Tech • Kuberre Systems • Meta Quotes Software Corp. • Software AG • Thomson Reuters Corporation • u Trade • Vela Trading Systems LLC Frequently Asked Questions: 1. Which region has the largest share in Algorithmic Trading Market? Ans: North America region holds the highest share in 2020. 2. What is the growth rate of Algorithmic Trading Market? Ans: The Algorithmic Trading Market is growing at a CAGR of 10.6 % during forecasting period 2021-2027. 3. What segments are covered in Algorithmic Trading market? Ans: Algorithmic Trading Market is segmented into component, trending type and region. 4. Who are the key players in Algorithmic Trading market? Ans: The important key players in the Algorithmic Trading Market are – AlgoTrader GmbH, Trading Technologies International, Inc., InfoReach, Inc., Tethys Technology, Inc., Lime Brokerage LLC, FlexTrade Systems, Inc., Tower Research Capital LLC, Virtu Financial, Hudson River Trading LLC, Citadel LLC, Technologies International, Inc., Argo Software Engineering, Inc., Automated Trading SoftTech Pvt. Ltd. 5. What is the study period of this market? Ans: The Algorithmic Trading Market is studied from 2020 to 2027.
1. Global Algorithmic Trading Market: Research Methodology 2. Global Algorithmic Trading Market: Executive Summary 2.1. Market Overview and Definitions 2.1.1. Introduction to Global Algorithmic Trading Market 2.2. Summary 2.2.1. Key Findings 2.2.2. Recommendations for Investors 2.2.3. Recommendations for Market Leaders 2.2.4. Recommendations for New Market Entry 3. Global Algorithmic Trading Market: Competitive Analysis 3.1. MMR Competition Matrix 3.1.1. Market Structure by region 3.1.2. Competitive Benchmarking of Key Players 3.2. Consolidation in the Market 3.2.1 M&A by region 3.3. Key Developments by Companies 3.4. Market Drivers 3.5. Market Restraints 3.6. Market Opportunities 3.7. Market Challenges 3.8. Market Dynamics 3.9. PORTERS Five Forces Analysis 3.10. PESTLE 3.11. Regulatory Landscape by region • North America • Europe • Asia Pacific • The Middle East and Africa • Latin America 3.12. COVID-19 Impact 4. Global Algorithmic Trading Market Segmentation 4.1. Global Algorithmic Trading Market, by Component (2020-2027) • Solutions o Platforms o Software Tools • Services o Professional Services o Managed Services 4.2. Global Algorithmic Trading Market, by Trading Type (2020-2027) • Foreign Exchange (FOREX) • Stock Markets • Exchange-Traded Fund (ETF) • Bonds • Cryptocurrencies • Others 5. North America Algorithmic Trading Market(2020-2027) 5.1. North America Algorithmic Trading Market, by Component (2020-2027) • Solutions o Platforms o Software Tools • Services o Professional Services o Managed Services 5.2. North America Algorithmic Trading Market, by Trading Type (2020-2027) • Foreign Exchange (FOREX) • Stock Markets • Exchange-Traded Fund (ETF) • Bonds • Cryptocurrencies • Others 5.3. North America Algorithmic Trading Market, by Country (2020-2027) • United States • Canada • Mexico 6. European Algorithmic Trading Market (2020-2027) 6.1. European Algorithmic Trading Market, by Component (2020-2027) 6.2. European Algorithmic Trading Market, by Trading Type (2020-2027) 6.3. European Algorithmic Trading Market, by Country (2020-2027) • UK • France • Germany • Italy • Spain • Sweden • Austria • Rest Of Europe 7. Asia Pacific Algorithmic Trading Market (2020-2027) 7.1. Asia Pacific Algorithmic Trading Market, by Component (2020-2027) 7.2. Asia Pacific Algorithmic Trading Market, by Trading Type (2020-2027) 7.3. Asia Pacific Algorithmic Trading Market, by Country (2020-2027) • China • India • Japan • South Korea • Australia • ASEAN • Rest Of APAC 8. Middle East and Africa Algorithmic Trading Market (2020-2027) 8.1. Middle East and Africa Algorithmic Trading Market, by Component (2020-2027) 8.2. Middle East and Africa Algorithmic Trading Market, by Trading Type (2020-2027) 8.3. Middle East and Africa Algorithmic Trading Market, by Country (2020-2027) • South Africa • GCC • Egypt • Nigeria • Rest Of ME&A 9. Latin America Algorithmic Trading Market (2020-2027) 9.1. Latin America Algorithmic Trading Market, by Component (2020-2027) 9.2. Latin America Algorithmic Trading Market, by Trading Type (2020-2027) 9.3. Latin America Algorithmic Trading Market, by Country (2020-2027) • Brazil • Argentina • Rest Of Latin America 10. Company Profile: Key players 10.1. AlgoTrader GmbH 10.1.1. Financial Overview 10.1.2. Global Presence 10.1.3. Capacity Portfolio 10.1.4. Business Strategy 10.1.5. Recent Developments 10.2. Trading Technologies 10.3. InfoReach 10.4. Tethys Technology 10.5. Lime Brokerage LLC 10.6. FlexTrade Systems 10.7. Tower Research Capital 10.8. Virtu Financial 10.9. Hudson River Trading 10.10. Citadel 10.11. Technologies International 10.12. Argo Software Engineering 10.13. Automated Trading SoftTech 10.14. Kuberre Systems 10.15. MetaQuotes Software Corp. 10.16. Software AG 10.17. Thomson Reuters Corporation 10.18. uTrade 10.19. Vela Trading Systems LLC

About This Report

Report ID 29843
Category Information Technology & Telecommunication
Published Date May 2019
Updated Date Nov 2021
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