Algorithmic Trading Industry Overview
|Study Period:||2018 - 2028|
|Fastest Growing Market:||Asia Pacific|
|Largest Market:||North America|
*Disclaimer: Major Players sorted in no particular order
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Algorithmic Trading Market Analysis
The algorithmic trading market is anticipated to witness a CAGR of 10.5% during the forecast period. Traders have traditionally used market surveillance technology to keep track of their trading operations and investment portfolios. Applications with built-in intelligence, like algorithmic trading, can explore the market for various opportunities based on the yield and other parameters the user specifies.
- The need for the algorithmic trading industry is anticipated to be driven by favorable governmental rules, rising demand for quick, reliable, and efficient order execution, increasing demand for market surveillance, and declining transaction costs. Large brokerage firms and institutional investors use algorithmic trading to reduce the expenses of bulk trading. Additionally, it is anticipated that the development of artificial intelligence (AI) and financial service algorithms will create attractive market expansion opportunities. A rise in the demand for cloud-based solutions is also anticipated to support the growth of the algorithmic trading market.
- In recent years, especially in the last ten years, FinTech tools have been developed significantly to increase the capacity of the financial industry, and algorithmic trading has dominated the capital markets, particularly the trading business. The general public currently has access to data science tools, high-speed internet, and computing power. The proliferation of online trading platforms and apps has increased the accessibility of trading financial items. Trade stocks and currencies only take a few mouse clicks.
- The market growth for algorithmic trading is projected to be significantly influenced by the financial services industry's broad adoption of AI, ML, and big data. Technological improvements have caused regulators to pay attention to how consumers interact with the market. Some of the global central banks began employing such technologies for advancing Algo trading. Moreover, algorithmic trading can maintain exceptionally high market liquidity due to quick buy and sell orders placed without human interaction. The increased application of algorithms across asset classes, particularly cross-asset automation, has been a trend over the past two years.
- As per TRADE's January 2022 Algorithmic Trading Survey, hedge funds increasingly use algorithms to trade most of their portfolios. For a multi-asset portfolio, hedge funds highly depend on a more significant number of suppliers for this. Algorithm providers are emphasizing multi-asset solutions to address the demand from hedge funds. The survey found that implementation insufficiency - single stock (53.14%), VWAP (54.71%), and dark liquidity seeking (72.94%) were the three most employed types of algos. Furthermore, some of the primary reasons behind the utilization of the algos include increased trader productivity (10.32%), reduced market impact (10.45%), consistency of execution performance (10.19%), ease of use (12.04%), and low commission rates (8.69%). There has also been a noticeable rise in the overall amount of automation and electronification. Moreover, the market volatility increase has maximized the need for algorithmic trading services and solutions.
- Algorithmic trading has increased because of the volatile market circumstances, large trading volume, and need for quick digital transformation to deal with distant working environments. The necessity for algo trading expanded during the COVID-19 pandemic since there was no way for geographically diversified trading to function effectively without the requirement for more advanced routing and electronic algos to assist and offer liquidity for traders. Moreover, due to a growing tendency toward algorithmic trading to make quick decisions while minimizing human mistakes, the pandemic had a positive effect on the growth rate of the algorithmic trading sector.
Algorithmic Trading Industry Segments
Algorithmic trading, also known as automated trading, algo-trading, or black-box trading, is a method of implementing trade orders with the assistance of automated pre-programmed trading instructions. Considering variables like volume, price, and time, the programs send small slices of the order to the market over a period.
The algorithmic trading market is segmented by types of traders (institutional investors, retail investors, long-term traders, and short-term traders), by components (solutions (platforms, software tools) and services), by deployment (on-cloud and on-premise), by organization size (small and medium enterprises and large enterprises), and geography (North America, Europe, Asia-Pacific, Latin America, and the Middle East and Africa).
The market sizes and forecasts are provided in terms of value (USD billion) for all the above segments.
|By Types of Traders|
|By Organization Size|
|Small and Medium Enterprises|
|Middle East and Africa|
Algorithmic Trading Market Trends
This section covers the major market trends shaping the Algorithmic Trading Market according to our research experts:
Institutional Investors Expected to Hold Major Share
- A group or institution's accounts are managed by institutional investors, who also buy and sell stocks on their behalf. Pension funds, mutual fund families, insurance companies, and exchange-traded funds are institutional investors. Institutional investors and large brokerage firms primarily use algorithmic trading to save trading costs. Large order sizes benefit significantly from algorithmic trading.
- Institutional investors employ several computer-driven algorithmic tactics daily in the volatile trading markets that power the stock market. These strategies allow investors to lower trade expenses and increase their profitability.
- These investors must execute high-frequency numbers, which is not always achievable. Institutional investors can divide a large sum of money into smaller portions and continue to trade according to predetermined time frames or strategies due to algorithmic trading. For instance, an algorithmic trading strategy may push 1,000 shares out every 15 seconds and progressively place modest quantities into the market studied throughout the period or the entire day rather than depositing 100,000 shares at once.
- Due to the massive volume of trades made by high-frequency traders daily, automated trading leveraging software and artificial intelligence is necessary, primarily to accelerate trade execution. Therefore, this technology may only be purchased by institutional investors. Moreover, they gain the benefit of value based on millisecond arbitrage to profit from it. Additionally, institutional-based investors use algorithmic trading by adhering to the arbitrage strategy when they want to benefit from various occasional tiny market price discrepancies.
- Institutional investors are very concerned about their capital. Thus, they require a system capable of making wise choices. Automation of processes reduces overtrading dramatically because some traders buy and sell at the first indication of a trade window opening. These techniques lessen the possibility of errors brought on by people. It responds to marketing conditions in a split second, making it a desired investment option.
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North America Expected to Dominate the Market
- North America is anticipated to have the most significant market share in the market studied. The main drivers of market growth throughout the forecast period are the rising investments in trading technologies (such as blockchain), the growing presence of algorithmic trading suppliers, and the expanding government backing for international trading.
- According to Wall Street data, algorithmic trading accounts for around 60-73% of the overall US equity trading. As per Select USA, the US financial markets are the largest and most liquid globally. Sentient Technologies, an AI company based in the United States, operates a hedge fund that built an algorithm processing millions of data points to find trading patterns and forecast trends.
- Modern technology is rapidly transforming the formats of conventional investment models by automating all associated trading procedures, enabling the development of a secure and effective ecosystem that will be accessible to all potential investors. In February 2022, a group of developers established the Dex Finance ecosystem. Dex Finance developed a low-risk algorithmic trading model that almost anyone can utilize by automating sophisticated trading tactics and encouraging investors to leave their deposits within the protocol.
- In order to compete with one another, businesses are offering low pricing in the highly competitive financial market. Stankevicius Group launched quant finance algorithmic trading services with no advance payments leading to success-based fees exclusively. The business has been researching and creating advanced financial services like algorithmic trading. The Stankevicius Quant Financial algorithm can trade numerous pairs simultaneously in bullish and bearish markets. Professional traders also monitor trading activities, and in case of unexpected mistakes or defaults, admin-side human contact is enabled to stop losses.
- Most traders trade based on tips and gut feeling, as they are limited by current platforms and are often blindsided by market movements against them that create unexpected losses. Streak, a supplier of algorithmic trading and strategy building for retail investors, announced the launch of its Streak application in the United States to address this issue. It is anticipated that the company, which already serves more than 300,000 retail investors and has handled over half a billion in trading turnover, will soon give American users access to a broad range of advanced trading capabilities for various asset classes. This will enable them to develop new trading ideas and strategies and quickly seize new trading opportunities.
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Algorithmic Trading Market Competitor Analysis
Due to numerous market participants worldwide, such as Virtu Financial Inc., Algo Trader AG, MetaQuotes Software Corp., and Refinitiv Ltd, the global algorithmic trading industry is moderately fragmented. Key firms primarily focus on producing innovative solutions and successful marketing plans to maintain and grow their market share.
In May 2022, PlatinX secured USD 5 million in funding to help bolster the success of its Algo Trading Software. PTX Algo, an AI-based Low Latency software developed by Plantix technology, a prop desk management and trading software development company, provides a one-stop solution for the virtual digital assets ecosystem.
In February 2022, Software AG partnered with the largest rural lifestyle retailer in the United States, Tractor Supply, to manage customer demand and enhance the shopping experience. Tractor Supply utilizes Software AG's integration and APIs solution to allow its customers to connect experiences across the store, mobile, and click-and-collect channels. Software AG solutions improve its operational excellence by integrating the supply chain from supplier to customer.
Algorithmic Trading Market Top Players
63 Moons Technologies Limited
MetaQuotes Software Corp.
Algo Trader AG
Virtu Financial Inc.
*Disclaimer: Major Players sorted in no particular order
Algorithmic Trading Market Recent Developments
- October 2022: Multi Commodity Exchange of India Limited (MCX) partnered with 63 Moons Technologies for software technology services for three months to continue to enjoy a seamless trading experience.
- June 2022: Fernhill Corp. declared that its digital asset trading division, MainBloq, a revolutionary digital asset trading platform serving both hedge funds and banks, signed a multi-year agreement to provide smart order routing, automated algorithmic trading, and customized trading solutions to optimize the overall trading performance across multiple strategies for India based CryptoWire.
- February 2022: AlgoTrader raised a total sum of about USD 4.9 million in the pre-Series B funding round to continue its unique digital asset growth strategy. East Asian venture capital companies Fenbushi Capital and SBI Investment joined the pre-Series B funding, which was co-led by Credit Suisse Entrepreneur Capital and C3 EOS VC Fund.
Algorithmic Trading Market Report - Table of Contents
1.1 Study Assumptions and Market Definition
1.2 Scope of the Study
2. RESEARCH METHODOLOGY
3. EXECUTIVE SUMMARY
4. MARKET INSIGHTS
4.1 Market Overview
4.2 Industry Attractiveness - Porter's Five Forces Analysis
4.2.1 Threat of New Entrants
4.2.2 Bargaining Power of Buyers/Consumers
4.2.3 Bargaining Power of Suppliers
4.2.4 Threat of Substitute Products
4.2.5 Intensity of Competitive Rivalry
4.3 Impact of COVID-19 on the Market
4.4 Technology Snapshot
4.4.1 Algorithmic Trading Strategies
18.104.22.168 Momentum Trading
22.214.171.124 Arbitrage Trading
126.96.36.199 Trend Following
188.8.131.52 Execution-based Strategies
184.108.40.206 Sentiment Analysis
220.127.116.11 Index-fund Rebalancing
18.104.22.168 Mathematical Model-based Strategies
22.214.171.124 Other Algorithmic Trading Strategies
5. MARKET DYNAMICS
5.1 Market Drivers
5.1.1 Rising Demand for Fast, Reliable, and Effective Order Execution
5.1.2 Growing Demand for Market Surveillance Augmented by Reduced Transaction Costs
5.2 Market Restraints
5.2.1 Instant Loss of Liquidity
6. MARKET SEGMENTATION
6.1 By Types of Traders
6.1.1 Institutional Investors
6.1.2 Retail Investors
6.1.3 Long-term Traders
6.1.4 Short-term Traders
6.2 By Component
126.96.36.199 Software Tools
6.3 By Deployment
6.4 By Organization Size
6.4.1 Small and Medium Enterprises
6.4.2 Large Enterprises
6.5 By Geography
6.5.1 North America
6.5.4 Latin America
6.5.5 Middle East and Africa
7. COMPETITIVE LANDSCAPE
*List Not Exhaustive
7.1 Company Profiles
7.1.1 Thomson Reuters
7.1.2 Jump Trading LLC
7.1.3 Refinitiv Ltd
7.1.4 63 Moons Technologies Limited
7.1.5 Virtu Financial Inc.
7.1.6 MetaQuotes Software Corp.
7.1.7 Symphony Fintech Solutions Pvt. Ltd
7.1.8 Info Reach Inc.
7.1.9 ARGO SE
7.1.10 IG Group
7.1.11 Kuberre Systems Inc.
7.1.12 Algo Trader AG
8. INVESTMENT ANALYSIS
9. MARKET OPPORTUNITIES AND FUTURE TRENDS
Algorithmic Trading Market Research FAQs
What is the study period of this market?
The Algorithmic Trading Market is studied from 2018 - 2028.
What is the growth rate of Algorithmic Trading Market?
The Algorithmic Trading Market is growing at a CAGR of 10.5% over the next 5 years.
Which region has highest growth rate in Algorithmic Trading Market?
Asia Pacific is growing at the highest CAGR over 2018 - 2028.
Which region has largest share in Algorithmic Trading Market?
North America holds highest share in 2021.
Who are the key players in Algorithmic Trading Market?
63 Moons Technologies Limited, MetaQuotes Software Corp., Algo Trader AG, Refinitiv Ltd, Virtu Financial Inc. are the major companies operating in Algorithmic Trading Market.
Algorithmic Trading Industry Reports
In-depth industry statistics and market share insights of the Algorithmic Trading sector for 2020, 2021, and 2022. The Algorithmic Trading research report provides a comprehensive outlook of the market size and an industry growth forecast for 2023 to 2028. Available to download is a free sample file of the Algorithmic Trading report PDF.