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Global Algorithmic Trading Market Research Report - Segmentation By Trading Type (FOREX, Stock Markets, ETF, Bonds, Cryptocurrencies); Component (Solutions, Services); Deployment Mode (Cloud, On-Premises); Application (Investment Banking, Funds, Personal Investors, Others); and Region - Forecast to 2027

Published: March, 2023
ID: 10297
Pages: 150
Formats: report pdf report excel report power bi report ppt

Algorithmic Trading Market Size (2021–2026)

The global algorithmic trading market is foreseen to progress from $11.1 billion in 2020 to $18.8 billion in 2026, recording an annual growth rate of 11.1% during the forecast period.

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 in order 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 offers 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.

Market Growth and Trends

Institutional investors should have a significant stake in Algorithmic Traders Market

  • 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 on a daily basis in volatile trading markets, succumbing to commercial influence and market makers. These techniques allow traders to reduce transaction costs and improve profitability.
  • These inverters have to perform high frequency numbers, which is not always possible. This helps them divide the total amount into smaller pieces and keep working at particular 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 trades execution. Therefore, only institutional investors are capable of implementing 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 effect the purchase and sale of assets.

Market Drivers and Restraints:

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.




Market Size Available

2020 – 2026

Base Year


Forecast Period

2022 - 2027



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 and Virtu Financial and Others.


Market Segmentation

Algorithmic Trading Market - By Trading Type

  • Stock Markets
  • ETF
  • Bonds
  • Cryptocurrencies

Algorithmic Trading Market - By Component

  • Solutions
  • Services

Algorithmic Trading Market - By Deployment Mode

  • Cloud

  • On-Premises

Algorithmic Trading Market - By Application

  • Investment Banking
  • Funds
  • Personal Investors
  • Others

Regional Analysis

Depending on the region, the global algorithmic trading market is segmented into:

  1. North America
  2. Europe
  3. Asia-Pacific
  4. Latin America
  5. Middle East and Africa.

The algorithmic trading market in North America contributed the largest share in 2018 due to technological advancements and the increasing application of algorithmic trading among various end-users such as banks and financial institutions in the area.

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.

Key Market Players

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.

Impact of Covid-19 on 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 of 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.

Recent Developments

  • February 2020 - German publicly traded FinTech company NAGA announced that it has 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 in Growing clients have direct access to the stock market listed on nine global stock exchanges.
  • March 2020: Algo Trader published about the release of its AlgoTrader 6.0, which includes the 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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