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The global algorithmic trading market size was valued at USD 2.03 billion in 2022 and is projected to grow from USD 2.19 billion in 2023 to USD 3.56 billion by 2030, exhibiting a CAGR of 7.2% during the forecast period.
In the scope, we have considered algorithmic trading platforms provided by companies such as Tradetron, Wyden, TradeStation, Symphony, and FXCM Group. Algorithmic type of trading is a method of buying and selling orders using a computer programmed to follow a defined set of instructions for inserting a trade to make profits at a higher speed and frequency. It is also known as black-box trading, automated trading, or algo trading. These algorithms help to buy, create, and automatically send orders to the market via the brokerage platform.
On the other hand, the Security and Exchange Board of India (SEBI) has created several opportunities for stock brokers by offering trading services to investors via unregulated platforms. These unregulated platforms bid for algo trading services to stakeholders for the automatic execution of trades. Such strategies and services are being marketed with "claims" of high returns on investment. For instance,
Rise in Remote Working amid Pandemic to Fuel Market Growth
The COVID-19 pandemic had an average impact on the global market, as the implementation of these trading solutions has risen in the face of unprecedented situations. The pandemic has enhanced the growth rate of the market, due to the augmented change toward algo trading for making decisions quickly by decreasing human errors. Additionally, the market players introduced advanced products during the pandemic to safeguard better serving of the increased trading volumes. Furthermore, the global market came under severe stress due to the COVID-19 pandemic. Volatility, message traffic, and trading volumes increased significantly above recent averages and remained elevated for several weeks.
On the other hand, several market SROs and participants were enforced to modify their supervisory, operational, and compliance protocols to accommodate their trading and support personnel working from home or backup facilities. For instance,
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Emergence of AI and ML in Financial Services to Boost Market Growth
Most financial services are using Machine Learning (ML) and Artificial Intelligence (AI) to aid data from digitally-driven channels. It is used by numerous companies operating in different areas such as insurance, asset management, and banking. This is due to the recent decade's rising trend of data-driven investments. This, in turn, fueled the demand for such trading or high-frequency platforms. Such AI-driven trading organizations analyze huge volumes of data faster than people would.
Therefore, increasing adoption of AI and ML in financial services plays a vital role in the algorithmic trading market growth.
Adoption of Algorithmic Trading in Financial Institutions to Foster Market Growth
Algorithms are the most cost-effective for low-maintenance trades and have meant head-count reductions and shifts on sales desks. The capability to capitulate orders automatically to exchanges directly rather than brokers has been a crucial innovation in lowering the cost of trading. Back office functions and post-trade services such as settlement and clearing have also benefited from automation. Furthermore, broker-dealers use algorithms to match buy and sell orders without publishing quotes. By controlling leakage information and taking both the offer and bid sides of the trade, pricing on shares for the client, broker algorithms allow improved liquidity and higher commissions to brokers.
Additionally, it is assumed that the increase in utilization of automated trading software by banking organizations, the growing consumption of cloud-based solutions, and an expansion in the requirement for market monitoring software are all contributing to market development.
Lack of Appropriate Risk Valuation Capabilities to Hinder the Market Growth
Algorithm trading is prone to risks and uncertainties wherein losses escalate quickly without proper controls. High-frequency trading is a method of algorithmic financial trading that uses electronic trading tools and fast-frequency financial data to trade at high turnover rates, high speeds, and high order-to-trade ratios. Investment companies withdraw orders that compromise risk management thresholds. Moreover, algorithmic High-frequency Trading (HFT) brings concerns, including increasing systemic risk. Also, unfamiliar market volatility erodes many investors’ faith in the market’s integrity.
Thus, lack of risk valuation capabilities in algorithmic trading systems hinders the market growth.
Increase in Demand for Stock Market to Drive Demand for Traders
The market is categorized into stock market, foreign exchange, exchange-traded funds, bonds, cryptocurrencies, and others.
The stock market segment captured the maximum revenue share in 2022. Algorithms are gaining popularity on online trading platforms, and many big customers demand them. These mathematical algorithms examine every price and trade on the stock market, recognize liquidity opportunities, and transform the information into intelligent trading results. Algorithmic trading reduces trading costs and permits stock managers to manage their trading processes. Algorithm modernization continues to offer returns for firms with the scale to absorb the prices and reap the benefits.
Cryptocurrencies segment is projected to experience significant growth during the forecast period. It is a defined set of instructions for making trades to make a profit at speeds and frequencies that are unrealistic for human traders. The main advantage of automated trading is that it allows users to execute certain crypto trades at lightning speed on multiple indicators, including target prices. Strategy Builders can create trading algorithms using the web-based strategy builder. Once a user creates an algorithm, it will be listed on an exchange and investors can subscribe to it and make these trades on their existing brokerage accounts.
Adoption of Cloud-based Solutions to Fuel the Product Demand
By deployment, the market is bifurcated into cloud and on premise. Cloud segment holds the maximum algorithmic trading market share and is also anticipated to grow at the highest CAGR during the forecast period, owing to financial organizations' adoption of cloud-based applications to increase their productivity and efficiency. Additionally, cloud-based solutions are gaining popularity among traders as they ensure the effective automation of processes, data maintenance, and cost-friendly management. These factors further propel the growth of the cloud-based algo trading software during the forecast period.
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Investment Strategies among Short-term Traders to Foster the Market Growth
By end-user, the market is categorized into short-term traders, long-term traders, retail investors, and institutional investors. Within end-user, the short-term traders segment would grow at the highest CAGR during the forecast period. Short-term traders focus primarily on price movements rather than the long-term fundamentals of an asset. This trading style looks for market volatility in terms of key economic company earnings, data releases, and political events as it seeks to profit from rapid movements in market prices.
The institutional investors segment held the largest share of the market in 2022. Institutional investors are managed by a group or institution's account. These investors also purchase and sell stocks on their behalf. Mutual fund families, pension funds, exchange-traded funds, and insurance firms are institutional investors. Therefore, large brokerage businesses and institutional investors mostly use these to save trading costs. Large order sizes benefit significantly from algorithmic trading.
North America Algorithmic Trading Market Size, 2022 (USD Billion)
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Geographically, the market has been studied across North America, South America, Europe, the Middle East & Africa, and Asia Pacific.
North America is expected to dominate the revenue share during the forecast period. It is anticipated to lead in algorithmic trading solution development and adoption due to its vast number of market participants, making it a competitive industry. This led to enormous investments in trading technologies and improved government support for global trade. The extensive use of algorithm trading in financial institutions, substantial technology enhancements, and banks boost industry expansion.
Asia Pacific is projected to witness notable growth in the forecast period due to substantial investments by private and public sectors to improve their trading technologies, driving the demand for solutions to automate trading processes. Additionally, the increasing deployment of algo trading technology by trading companies is introducing lucrative opportunities for the key players in the market. Furthermore, the rising adoption of cloud-based technologies in this region is contributing to regional market growth.
Europe is expected to showcase a steady growth rate. The European market is examined across Germany, France, the U.K., Italy, and others. The usage of trading approaches and novel infrastructures in the field has increased owing to regulatory platforms, technological development, and increased participant competition in the trading market, which drives the trading industry. Additionally, the government is also implementing special rules and regulations to endorse security and performance, which nurtures the market growth. For instance,
The Middle East trading market is slowly gathering speed as Turkey has become the latest country to activate a system that enables traders to buy and sell in the blink of an eye. Additionally, the Istanbul Stock Exchange embraced algorithms trading, also known as “Robo-trading,” enabling the automatic trading of bonds, stocks, and currencies. These strategies enable high-frequency trading, in which algorithms trade on data quickly for a human trader to react.
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South America to showcase significant CAGR during the forecast period. The trading software enhances and automates trading capabilities for financial instruments, including equities, digital assets, securities, currency, and more. It bids a full set of algorithms in Brazil, including Time-weighted average price (TWAP), Volume-weighted average price (VWAP), Participate, and Custom Navigator, which aims to decrease market impact, maximize execution quality, and recover trading performance based on the particulars of each market.
Growing Emphasis on Global Expansion to Strengthen Market Positions
The top players are focused on expanding their geographical boundaries by introducing industry-specific solutions. These players strategically collaborate and acquire local players to gain a strong regional grip. Innovations and new product launches attract a vast customer base, thus improving revenue. These companies are concentrating on creating effective marketing strategies and developing new solutions for maintaining and growing their market share. The growing global trading volume is expected to create lucrative opportunities for the market players. Consequently, leading market players focus on numerous strategic initiatives such as mergers & acquisitions, and partnerships, to stay competitive.
An Infographic Representation of Algorithmic Trading Market
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The study on the market includes prominent areas worldwide to get a better knowledge of the industry. Furthermore, the report provides insights into the most recent industry and market trends, as well as an analysis of technologies that are being adopted quickly worldwide. It also emphasizes some of the growth-stimulating restrictions and elements, allowing the reader to obtain a thorough understanding of the industry.
ATTRIBUTE | DETAILS |
Study Period | 2019-2030 |
Base Year | 2022 |
Estimated Year | 2023 |
Forecast Period | 2023-2030 |
Historical Period | 2019-2021 |
Growth Rate | CAGR of 7.2% from 2023 to 2030 |
Unit | Value (USD billion) |
By Type |
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By Deployment |
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By End-user |
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By Region |
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The market is projected to reach USD 3.56 billion by 2030.
In 2022, the market stood at USD 2.03 billion.
The market is projected to grow at a CAGR of 7.2% in the forecast period (2023-2030).
By deployment, the cloud segment is likely to lead the market.
The growing adoption of algorithmic trading across financial institutions is anticipated to foster the market growth.
, Tradetron, Inc., Tickblaze LLC., Wyden, TradeStation, InfoReach, Inc., Symphony, ALGOTRADERS, Argo Software Engineering, FXCM Group, and Tata Consultancy Services Limited are the top players in the market.
North America is expected to hold the highest market share.
By end-user, the short-term traders segment is expected to grow with the highest CAGR.
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