Key Highlights

• The requirement for the algorithmic trading industry is anticipated to be driven by elements including favourable governmental rules, rising need for quick, dependable, and efficient order execution, rising demand for market monitoring, and declining transaction costs. Algorithmic trading is used by large brokerage firms and institutional investors to reduce the expenses of bulk trading.


• In recent years, especially in the last ten years, FinTech technologies have been developed to increase the capacity of the financial sector, and algorithmic trading has dominated the capital markets, particularly the trading business. Several market entry barriers were lowered as a result of the digital revolution. The entire population now has access to data science tools, high-speed internet, and computing power. The proliferation of online trading platforms and applications has increased the accessibility of trading financial items. It now only takes a few mouse clicks to trade stocks, futures, and currencies.


• Using automatic, pre-programmed trading instructions, algorithmic trading—also referred to as algo trading, black-box trading, or automated trading—is a process for carrying out trade orders. The algorithms gradually release pieces of the order to the market while taking into account a number of factors, including time, price, and volume.


• The financial services industry's use of AI, ML, and big data is anticipated to play a significant role in the market growth for algorithmic trading. Because of the advancements in technology, regulators are also beginning to pay attention to the ways that people engage with the market. Some of the biggest institutions in the world began implementing such technology to advance algorithmic trading.


• A renowned investment bank, JP Morgan, revealed in April 2021 that the rise in fixed income futures algorithmic trading surged dramatically in 2020 as THE buy-side traders flocked to the firm's machine-learning enabled algos to deal with the extreme market volatility.

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Key Market Trends

Institutional Investors Expected to Hold Major Share

• A group or institution's accounts are managed by institutional investors, who also purchase and sell equities on their behalf. Pension funds, mutual fund families, insurance companies, and exchange-traded funds are examples of institutional investors (ETFs). To lower trading costs, institutional investors and large brokerage firms primarily use algorithmic trading. High order sizes benefit greatly from algorithmic trading.


• In the turbulent trading markets that power the stock market, institutional investors employ several computer-driven algorithmic tactics on a regular basis. These strategies give investors the potential to lower trade expenses and increase their profitability.


• These investors must execute high-frequency numbers, which isn't 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 thanks 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 researched throughout the period or the full day rather than depositing 100,000 shares at once.


• Due to the huge volume of trades made by high-frequency traders each day, automated trading leveraging software and artificial intelligence is necessary, primarily to accelerate trade execution. Therefore, this technology may only be purchased by institutional investors. Additionally, they gain the benefit of value, which is based on millisecond arbitrage, to profit from it. Additionally, institutional-based investors use algorithmic trading by adhering to the arbitrage strategy when they aim to profit from various sporadic minor price discrepancies in the stock available on two different exchanges.

Expectations are for North America to rule the market.

• In the industry under study, North America is anticipated to have the most market growth. The main drivers of market growth throughout the projection period are the rising investments in trading technologies (such blockchain), the growing presence of algorithmic trading suppliers, and the expanding government backing for international trading.


• Around 60–73% of all US equities trading is made up of algorithmic trading (source: Wall Street). The largest and most liquid financial markets worldwide, according to Select USA, are found in the US. A hedge fund run by Sentient Technologies, an AI company with US headquarters, has created an algorithm that analyses millions of data points to identify trading patterns and predict trends.


• The likelihood that algorithmic trading methods, such as high-frequency trading (HFT) tactics, would have a negative influence on the market and company stability has increased as these strategies have become more common in the US securities markets.

Competitive Landscape

Due to the existence of several market participants worldwide, such as Virtu Financial, Inc., Algo Trader AG, MetaQuotes Software Corp., and Refinitiv Ltd., the global algorithmic trading industry is fairly fragmented. To preserve and grow their market share, key firms concentrate on producing innovative solutions and successful marketing plans.

• In June 2021, Tastytrade, a brokerage and investor education platform, was fully acquired by IG Group. IG Group agreed to pay an initial cash payment of USD 300 million and to issue 61 million new IG Group shares at a price of USD 11.47 per share as part of a deal that was begun in January 2021. The purchase was valued at USD 1 billion. In order to finalise the transaction, IG Group completed all prerequisites and got all required regulatory and antitrust clearances; the operator had applied for the additional shares.


• Refinitiv and Pio-Tech announced their alliance in November 2021 with the goal of offering smart, modern solutions with a variety of unique business benefits to both firms' banking clients throughout the Middle East and Africa. The goal of this alliance is to increase the effectiveness of different internal anti-money laundering (AML) operations across all banking departments.