Global Algorithmic Trading Market Size, Share, Trends, COVID-19 Impact & Growth Forecast Report – Segmented By Trading Type (FOREX, Stock Markets, ETF, Bonds and Cryptocurrencies), Component (Solutions and Services), Deployment Mode (Cloud and On-Premises), Application (Investment Banking, Funds, Personal Investors, Others) and Region (North America, Europe, Asia-Pacific, Latin America, Middle East and Africa) – Industry Analysis from 2024 to 2029

Updated On: January, 2024
ID: 10297
Pages: 150

Global Algorithmic Trading Market Size (2024 to 2029)

The global algorithmic trading market is anticipated to grow at a CAGR of 11.1% from 2024 to 2029 and the global market size is anticipated to be worth USD 28.62 billion by 2029 from USD 16.91 billion in 2024.

Algorithmic trading, automated trading, or black box trading is a technological advancement in the stock market. It is a programmed process that runs on a computer that follows a specific set of instructions to complete a trade to generate profits at a speed and frequency that human traders cannot. Traditionally, traders keep track of their trading activity and investment portfolio with the help of market surveillance. Applications like algorithmic trading offer the intelligence to seek out opportunities that exist in the market, based on performance and other user-defined criteria. Factors such as favorable government regulations, growing demand for fast, reliable, and efficient order execution, increasing demand for market surveillance and reduced transaction costs are expected to spearhead the market's need for algorithmic trading.

Global Algorithmic Trading Market Drivers:

The growing usage of algorithmic trading by the institutional investors is driving the global market growth. Institutional investors mainly comprise of banks, credit unions, insurance companies, hedge funds, investment advisers, and mutual fund companies, who pool their money to buy securities, real estate, or any other type of investment asset. Institutional investors use multiple computer-controlled algorithmic strategies daily in volatile trading markets, succumbing to commercial influence and market makers. These techniques allow traders to reduce transaction costs and improve profitability. These investors must perform high-frequency numbers, which is not always possible. This helps them divide the total amount into smaller pieces and keep working at time intervals or according to specific strategies. For example, instead of placing 1,00,000 shares at once, an e-commerce technique can push 1,000 shares every 15 seconds and gradually place small amounts on the market over the period or all day. Since HF traders perform a large number of trades per day, automated trades are required using software and artificial intelligence, primarily to speed up trade execution. Therefore, only institutional investors can implement this technology and encompasses an unfair advantage to profit from the value, which is based on millisecond arbitrage. Following trends is among the most used techniques by traders, which is based on algorithms. The approach identifies specific patterns used to affect the purchase and sale of assets.

The growing demand for AI-based services in the financial industry is driving the growth of the global algorithmic trading market. In algorithmic trading, AI helps to adopt market conditions, learn from experiences, and make trading decisions accordingly. Trading houses like Blackrock, Renaissance Technologies, and Two Sigma, among others, use AI to select stocks. Therefore, the increasing adoption of AI in the financial industry is expected to drive the growth of the algorithmic trading market during the forecast period. Additionally, the increasing adoption of stockless trading algorithms by institutional asset managers is another growth driver in the global algorithmic trading market.

Global Algorithmic Trading Market Restraints:

Regulatory constraints and compliance challenges are primarily hampering the growth of the global algorithmic trading market. Systemic risk concerns in financial markets, technology infrastructure limitations and high costs of implementing algorithmic trading systems are hindering the global algorithmic trading market growth. Lack of transparency and accountability, cybersecurity threats and data breaches are further inhibiting the growth rate of the global market.

Impact of COVID-19 on the global algorithmic trading market:

Due to the outbreak of the coronavirus, the stock markets collapsed in March 2020, triggering circuit breakers that interrupted trading in the market on several occasions. Algorithm trading helped the market recover from the March lows. As a result, forex algorithmic execution tools have grown significantly since March 2020. According to the latest JPMorgan survey, over 60% of trades for ticket sizes over $ 10 million were executed in March using an algorithm. This compared to less than 50% a year ago. Hedge funds and real money accounts dominate the end-user industry. In addition, a report on algorithmic trading by the National Institute of Financial Management, submitted to the Department of Economics in May 2010, found that algorithms accounted for half of the orders on the NSE and the ESB.




Market Size Available

2023 to 2029

Base Year


Forecast Period

2024 to 2029



Segments Covered

By Trading Type, Component, Deployment Mode, Application, and Region


Various Analyses Covered

Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities

Regions Covered

North America, Europe, APAC, Latin America, Middle East & Africa


 Market Leaders Profiled

AlgoTrader GmbH, Trading Technologies International, Inc., Tethys Technology, Inc., Tower Research Capital LLC, Lime Brokerage LLC, InfoReach, Inc., FlexTrade Systems, Inc., Hudson River Trading LLC, Citadel LLC, Virtu Financial, and others


This research report on the global algorithmic trading market has been segmented and sub-segmented based on trading type, component, deployment mode, application and region.

Global Algorithmic Trading Market - By Trading Type:


  • Stock Markets

  • ETF
  • Bonds
  • Cryptocurrencies

Global Algorithmic Trading Market - By Component:

  • Solutions
  • Services

Global Algorithmic Trading Market - By Deployment Mode:

  • Cloud
  • On-Premises

Global Algorithmic Trading Market - By Application:

  • Investment Banking
  • Funds
  • Personal Investors
  • Others

Global Algorithmic Trading Market – By Region:

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East and Africa

The algorithmic trading market in North America contributed the largest share in 2023 due to technological advancements and the increasing application of algorithmic trading among various end-users such as banks and financial institutions in the North American region.  North America is supposed to hold its dominant size in the global algorithmic trading market through the adoption and expansion of algorithmic trading. Increasing investments in trading technologies like blockchain, the growing presence of algorithmic trading providers, and growing government support for global trade are the main factors contributing to the growth of the market during the outlook period. Furthermore, significant technological advances and the considerable application of trading algorithms in various applications such as banks and financial institutions in the locale are expected to drive market growth.


Some of the major players operating in the global algorithmic trading market include AlgoTrader GmbH, Trading Technologies International, Inc., Tethys Technology, Inc., Tower Research Capital LLC, Lime Brokerage LLC, InfoReach, Inc., FlexTrade Systems, Inc., Hudson River Trading LLC, Citadel LLC and Virtu Financial.


  • In February 2020, German publicly traded FinTech company NAGA announced that it had improved its overall trading experience with the recent deployment of the MetaTrader 5 platform. The company expanded its multi-asset offering to provide its solutions to Growing clients who have direct access to the stock market listed on nine global stock exchanges.
  • In March 2020, Algo Trader published the release of its AlgoTrader 6.0, which includes crypto exchange adapters like Deribit, Huobi, Kraken, and Bithumb. It delivers full support for Level II order book information for all data adapters on the market. The new Order Book widget in the AlgoTrader UI shows the user all of the BUY and SELL orders.

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Frequently Asked Questions

What is the current size of the global algorithmic trading market?

The global algorithmic trading market is anticipated to be worth USD 16.91 billion in 2024.

Which regions contribute the most to the global algorithmic trading market share?

Major financial hubs such as North America, Europe, and Asia-Pacific contribute significantly to the global algorithmic trading market share, with the United States being a key player.

What factors are driving the growth of algorithmic trading market globally?

The growth of algorithmic trading is driven by factors such as increased market efficiency, reduced trading costs, advancements in technology, and the need for faster and more precise trading decisions.

How has the COVID-19 pandemic influenced algorithmic trading market?

The COVID-19 pandemic has led to increased volatility in financial markets, impacting algorithmic trading strategies. Some strategies have adapted to market fluctuations, while others faced challenges.

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