Algorithmic Trading Market Research Report: Information by Component (Solution and Services), Type (Stock Markets, FOREX, ETF, Bonds, Cryptocurrencies), Deployment Mode (Cloud and On-Premise), and Type of Traders (Institutional Investors, Long-Term Traders, Short-Term Traders, and Retail Investors), Organization Size (Small and Medium Enterprises and Large Enterprise) and Region (North America, Europe, Asia-Pacific, and Rest of the World)—Forecast till 2030

Algorithmic Trading Market Overview

The global Algorithmic Trading market size is projected to grow at a CAGR of 13.1% from 2021 to 2030.

Algorithmic trading, also known as automated trading or black-box trading, is a form of computer automation in which algorithms are used to generate orders without the intervention of humans. These programs are commonly used by online traders who want to execute large quantities of transactions quickly and efficiently. Algorithmic traders allow investors to trade multiple markets and take advantage of short-term price movements by sending buy or sell orders based on specific criteria such as volume and price changes. For example, a trader could program an algorithmic trader to automatically buy one share at $30 whenever the price rises above that level for 5 minutes and sell it five minutes later at $31 if the price rises further. This type of software allows users to eliminate human error from their strategies.

COVID-19 Impact Analysis

The COVID-19 outbreak has had little impact on the growth of the algorithmic trading market. The adoption of algorithmic trading solutions has increased in the face of unprecedented circumstances. The COVID-19 pandemic has significantly fueled the growth rate of the algorithmic trading market, owing to the increased shift toward algo trading for taking decisions at a very rapid pace by reducing human errors. For example, the Reserve Bank of Australia, in its recent publication stated that they may have only furthered the industry’s shift toward electronic trading.

Market Dynamics

Market growth for algorithmic trading is primarily driven by demand for reliable, fast, and effective order execution; the emergence of favorable regulatory policies; and requirements for market monitoring. However, shortcomings in risk valuation may slow down the industry growth to some extent. On the other hand, the emergence of Artificial Intelligence and algorithms in financial services provides an opportunity for development during the forecast period.

Drivers

• Increasing demand for efficient Algorithmic Trading

Algorithmic trading is rapidly being used by big brokerage houses as well as institutional investors to cut down on costs associated with trading. This rapid use is attributed to the fact that algorithmic trading makes it easier and faster to execute orders, making it attractive for exchanges. In addition, it enables traders and investors to quickly book profits off small changes in price. Therefore, the rise in demand for effective trade drives the growth of the algorithmic trading market, as it enables users to quickly execute trades.

Restraint:

• Strict regulations and low acceptance across many countries

Regulatory authorities across the world have been tightening their grip on the use of algorithmic trading in the financial sector to make sure that their market is secure and beneficial for the clients. With the increase in the adoption of automated systems to conduct trading activities, there is a greater need for regulators to step in and check for potential loopholes that could be exploited via the system. If a market will be technologically advanced, there will be a greater need for advanced risk management solutions as well, which is a necessity for the market to grow.

Opportunity:

• Rapid Adoption of AI in Financial Services

There is a high adoption rate of Artificial Intelligence and Machine Learning among data-driven companies which are operating in the banking, insurance, and asset management industry, and is using AI for their digital distribution platforms for managing customer information and cryptocurrency trading. This has resulted in a rapidly growing demand for the adoption of automated data analytics in the investment sector over the forecast timeline by emerging new developments in the field. Consequently, increasing market penetration of these advanced technologies at a faster pace will increase its demand substantially while bringing fresh opportunities to clients.

Segment Overview

By Component

Based on Components, the global algorithmic trading market has been divided into solutions and services. The solution segment held the largest share in the global algorithmic trading market for the year 2021 and is anticipated to maintain its dominance throughout the forecast period.

By Type

Based on type, the global algorithmic trading market has been divided into Stock Markets, FOREX, ETF, Bonds, Cryptocurrencies, and Others. The ETF segment is anticipated to experience highest growth in the global algorithmic trading market in the coming years, owing to the increasing demand for automated trading across the globe.

By Type of Traders

By type of traders, the global algorithmic trading market has been segmented into Institutional Investors, Long-Term Traders, Short-Term Traders, and Retail Investors. The Institutional Investors segment held the largest market share in the global algorithmic trading market for the year 2021. Algorithmic trading is used by institutional investors and large brokerage firms as a way to reduce trading expenses.  It is particularly helpful for high-volume orders.

By Deployment Mode

On the basis of deployment mode, the global Algorithmic Trading market has been segmented as Cloud and On-Premise. The Cloud segment is estimated hold the largest market share in the global Algorithmic Trading market for the year 2022 as it helps the vendors gain maximum profits and effectively automate the trading process.

By Organization Size

The global Algorithmic Trading market has been segmented into Small and Medium Enterprises and Large Enterprises. The Large Enterprises segment is expected to hold the largest market share in the global Algorithmic Trading market for the year 2022. However, the Small and Medium Enterprises are expected to witness the highest CAGR in the forecast years as the number of such enterprises is increasing rapidly.

Regional Analysis

By region, the global Algorithmic Trading market has been divided into North America, Europe, Asia-Pacific, and the Rest of the World. North America accounted for the largest market. Asia Pacific is projected to exhibit the highest CAGR during the review period.

Asia-Pacific Market

The Asia-Pacific region is expected to witness the most growth during the forecast period. The region is widely considered one of the most booming and upcoming regions in the world right now. There is a massive influx of foreign investment in many countries into sectors such as real estate and technology, but especially technology - and it is no surprise that algorithmic trading will see a boom and progress here due to this high standard of investments available.

North America Market

North America dominates the market on all fronts when it comes to trading and investing. The region has a lot of money to invest in new technologies and tools, which means a lot of people have money to use when they're gambling online or making asset purchases; and a government that backs them up with copious funds. In addition, there are many agencies based here, that have access to limited amounts of personal data making it easier for them to funnel funds into their own businesses and thus enabling them to grow at an even faster rate than usual.

Competitive Landscape

The market comprises tier-1, tier-2, and local players. The tier-1 and tier-2 players have presence across the globe with diverse product portfolios. Companies such as Thomson Reuters (US), 63 moons (India), Virtu Financial (US), and Software AG (Germany), dominate the global algorithmic trading market due to product differentiation, financial stability, and strategic developments, and diversified regional presence. The players are focused on investing in research and development. Furthermore, they adopt strategic growth initiatives, such as expansion, product launches, joint ventures, and partnerships, to strengthen their market position and capture a large customer base.

Prominent players in the global algorithmic trading market include 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), and AlgoTrader (Switzerland)

Scope of the Report

Global Algorithmic Trading Market, by Component

• Solution


• Services

Global Algorithmic Trading Market, by Deployment Mode

• Cloud


• On-Premise

Global Algorithmic Trading Market, by Type of Trader

• Institutional Investors


• Long-Term Traders


• Short-Term Traders


• Retail Investors

Global Algorithmic Trading Market, by Type

• Stock Markets


• FOREX


• ETF


• Bonds


• Cryptocurrencies


• Others

Global Algorithmic Trading Market, by Organization Size

• Small and Medium Enterprises


• Large Enterprises

Global Algorithmic Trading Market, by Region

• 
  North America
  
  
  
  • US
  
  
  • Canada
  
  
  
  


• 
  Europe
  
  
  
  • UK
  
  
  • Germany
  
  
  • France
  
  
  • Italy
  
  
  • Spain
  
  
  • Rest of Europe
  
  
  
  


• 
  Asia-Pacific
  
  
  
  • China
  
  
  • India
  
  
  • Japan
  
  
  • Australia and New Zealand
  
  
  • Rest of Asia-Pacific
  
  
  
  


• 
  Rest of the World
  
  
  
  • South America
  
  
  • Middle East
  
  
  • Africa
  
  
  
  

Objectives of the Study

The objectives of the study are summarized in 5 stages. They are as mentioned below:

Market Size and Forecast:

To identify and estimate the market size for the global Algorithmic Trading market segmented by product type, material type, category, shape, and distribution channel by value (in US dollars). Also, to understand the consumption/ demand created by consumers of Algorithmic Trading from 2019 to 2030

Market Landscape and Trends:

To identify and infer, the drivers, restraints, opportunities, and challenges for the global Algorithmic Trading market

Market Influencing Factors:

To find out the factors which are affecting the sales of Algorithmic Tradings among consumers

Impact of COVID-19:

To identify and understand the various factors involved in the global Algorithmic Trading market affected by the pandemic

Company Profiling:

To provide a detailed insight into the major companies operating in the algorithmic trading market. The profiling will include the financial health of the company past 2-3 years with segmental and regional revenue breakup, product offering, recent developments, SWOT analysis, and key strategies.

Intended Audience

• Algo Traders


• Enterprises


• Governments, Associations, and Industrial Bodies


• Investors and Trade Experts